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@misc{Jin2020DevelopingaNovelTacti,
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@misc{Castiglione2019PreventingaThoughtfro,
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@misc{Chang2019EvaluationofArtifactS,
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@misc{Delorme2019TheOpenEEGLABPortal,
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@misc{Efrati2019Adolescentscompulsive,
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@misc{Efrati2019TheEffectofEarlyLife,
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@misc{Kappel2019EarEEGforwardmodels,
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@misc{Keehn2019Spontaneityanddiversit,
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@misc{Kowalewska2019Whichdimensionsofhuma,
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@misc{LewStarowicz2019Compulsivesexualbehavi,
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@misc{Marini2019Acomparativeevaluation,
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@misc{MariniF2019Datasetof24subjectEE,
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@misc{MartnezCancinoR2019Measuringtransientphas,
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@misc{MichelCM2019InMemoriamFernandoLo,
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@misc{Nakanishi2019Facilitatingcalibration,
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@misc{NguyenLT2019Thetaandalphabandosc,
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@misc{Nowakowska2019Changesintheaddiction,
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@misc{PionTonachini2019ICLabelAnautomatedel,
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  author = {Pion-Tonachini, L., Kreutz-Delgado, K. and Makeig, S},
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}

@misc{PionTonachini2019ICLabelAnautomatedel2,
  title = {ICLabel: An automated electroencephalographic independent component classifier, dataset, and website},
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@misc{PionTonachiniL2019TheICLabeldatasetofe,
  title = {The ICLabel dataset of electroencephalographic (EEG) independent component (IC) features},
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}

@misc{Randau2019Attenuatedmismatchnega,
  title = {Attenuated mismatch negativity in patients with first-episode antipsychotic-naive schizophrenia using a source-resolved method},
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}

@misc{Siddharth2019AWearableMultimodalB,
  title = {A Wearable Multi-modal Bio-sensing System Towards Real-world Applications},
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}

@misc{SLKappel2019EarEEGforwardmodels,
  title = {Ear-EEG forward models: Improved head-models for Ear-EEG},
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}

@misc{Somon2019Evaluationofperformanc,
  title = {Evaluation of performance monitoring ERPs through difficulty manipulation in a response-feedback paradigm},
  author = {Somon, B., Campagne, A., Delorme, A., Berberian, B. (},
  year = {2019},
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@misc{Somon2019HumanornothumanPerf,
  title = {Human or not human? Performance monitoring ERPs during human agent and machine supervision},
  author = {Somon, B., Campagne, A., Delorme, A., Berberian, B. (},
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}

@misc{Sundby2019Thefunctionalroleofr,
  title = {The functional role of response suppression during an urge to relieve pain},
  author = {Sundby, K. K, Wagner, J., Aron, A. R. (},
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}

@misc{Tanaka2019Crosscorrelationtaskr,
  title = {Cross-correlation task-related component analysis (xTRCA) for enhancing evoked and induced responses of event-related potentials},
  author = {Tanaka, H., Miyakoshi, M. (},
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@misc{Tsai2019Eyefixationrelatedfro,
  title = {Eye fixation-related fronto-parietal neural network correlates of memory retrieval},
  author = {Tsai, P.Y., She, H-C, Chen, S-C, Huang, L-Y, Chou, W-C, Duann, JR, Jung, T-P. Eye fixation-related fronto-parietal neural network correlates of memory retrieval . Int J Psychophysiol . 138:57-70},
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}

@misc{WagnerJ2019HighdensityEEGmobile,
  title = {High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task},
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@misc{WagnerJ2019Trialbytrialsourcere,
  title = {Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation},
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}

@misc{Wagner2019Canoscillatoryalphaga,
  title = {Can oscillatory alpha-gamma phase-amplitude coupling be used to understand and enhance TMS effects?},
  author = {Wagner, J., Makeig, S., Hoopes, D., & Gola, M. (},
  year = {2019},
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}

@misc{Wagner2019Singletrialsourcereso,
  title = {Single-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation},
  author = {Wagner, J., Martinez-Cancino, R., Makeig, S., “ Single-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation .” NeuroImage , June 7},
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}

@misc{Wahbeh2019TheNoeticExperiencean,
  title = {The Noetic Experience and Belief Scale: A validation and reliability study},
  author = {Wahbeh, H., Yount, G., Vieten, C., Radin, D., Delorme, A. (},
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@misc{ArtoniF2018Applyingdimensionreduc,
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@misc{BurgosPI2018Visuomotorcoordination,
  title = {Visuomotor coordination and cortical connectivity of modular motor learning},
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@misc{ChenCF2019Unravelingthespatiotem,
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  author = {Chen C.F., Kreutz-Delgado K., Sereno M.I., Huang R.S.(},
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@misc{Chang2018EvaluationofArtifactS,
  title = {Evaluation of Artifact Subspace Reconstruction for Automatic EEG Artifact Removal},
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  year = {2018},
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}

@misc{Chiang2018CrossSubjectTransferL,
  title = {Cross-Subject Transfer Learning Improves the Practicality of Real-World Applications of Brain-Computer Interfaces},
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@misc{DelormeA2018Whenthemeditatingmind,
  title = {When the meditating mind wanders, Current Opinion in Psychology},
  author = {Delorme A., Brandmeyer T. (},
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@misc{Delorme2018BrieflyFlashedScenesC,
  title = {Briefly Flashed Scenes Can Be Stored in Long-Term Memory},
  author = {Delorme, A., Poncet, M., Fabre-Thorpe, M. (},
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@misc{Efrati2018Understandingandpredic,
  title = {Understanding and predicting profiles of compulsive sexual behavior among adolescents},
  author = {Efrati, Y., & Gola, M. (},
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}

@misc{Efrati2018Treatingcompulsivesexu,
  title = {Treating compulsive sexual behavior},
  author = {Efrati, Y. & Gola, M. (},
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@misc{Fonseca2018Brainnetworkchangesin,
  title = {Brain network changes in fatigued drivers: a longitudinal study in a real-world environment based on the effective connectivity analysis and actigraphy data},
  author = {Fonseca, A., Kerick, S., King, J-T., Lin, C-T, Jung, T-P. “ Brain network changes in fatigued drivers: a longitudinal study in a real-world environment based on the effective connectivity analysis and actigraphy data ,” Frontiers in Human Neuroscience, Nov. 12},
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}

@misc{Gola2018VentralStriatalReactiv,
  title = {Ventral Striatal Reactivity in Compulsive Sexual Behaviors},
  author = {Gola, M., & Draps, M. (},
  year = {2018},
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}

@misc{Gola2018Promotingeducationalc,
  title = {Promoting educational, classification, treatment, and policy initiatives: Commentary on: Compulsive sexual behaviour disorder in the ICD-11},
  author = {Gola, M., & Potenza, M. N. (},
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}

@misc{Gola2018TheProofofthePudding,
  title = {The Proof of the Pudding Is in the Tasting: Data Are Needed to Test Models and Hypotheses Related to Compulsive Sexual Behaviors},
  author = {Gola, M. & Potenza, M. (},
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@misc{Gouraud2018Influenceofautomation,
  title = {Influence of automation on mind wandering frequency in sustained attention. Consciousness and Cognition},
  author = {Gouraud, J., Delorme, A., Berberian, B. (},
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@misc{Gouraud2018OutoftheLoopinYour,
  title = {Out of the Loop, in Your Bubble: Mind Wandering Is Independent From Automation Reliability, but Influences Task Engagement},
  author = {Gouraud, J., Delorme, A., Berberian, B. (},
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@misc{Hsu2018Modelingbraindynamics,
  title = {Modeling brain dynamic state changes with adaptive mixture independent component analysis},
  author = {Hsu, S.H., Pion-Tonachini, L., Palmer, J., Miyakoshi, M., Makeig, S., Jung, T.P. (},
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@misc{HuangC2018Investigationofvagala,
  title = {Investigation of vagal afferent functioning using the Heartbeat Event Related Potential},
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@misc{Huang2018Neuraloscillationcorre,
  title = {Neural oscillation correlates chemistry decision-making},
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@misc{Huang2018Spatiotemporalintegrati,
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@misc{Kim2018Ngoggle2018Headmoun,
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@misc{Kowalewska2018Neurocognitivemechanism,
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@misc{Motoi2018Phaseamplitudecoupling,
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@misc{Nakanishi2018TransferringSharedResp,
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@misc{Nakanishi2018EnhancingdetectionofS,
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@misc{Okruszek2018Workingmemorycognition,
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@misc{Papp2018BrainZapsAnUnderappr,
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@misc{PionTonachini2018OnlineAutomaticArtifac,
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@misc{Vieten2018Futuredirectionsinmed,
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@misc{Wei2018SubjectTransferFramewo,
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@misc{Wordecha2018Pornographicbingesas,
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@misc{Wu2018SpatialFilteringforEE,
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@misc{Efrati2018Compulsivesexualbehavi,
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@misc{Gola2017PolishadaptationofSex,
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@misc{Gola2017Canpornographybeaddic,
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@misc{GouraudJ2017AutopilotMindWanderin,
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@misc{Huang2017Mappingthecomplextopo,
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@misc{KhoshnoudS2017Differentcorticalsourc,
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@misc{KoLW2017SustainedAttentioninR,
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@misc{Lewczuk2017Treatmentseekingforpr,
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@misc{Lin2017ImprovingEEGBasedEmot,
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@misc{Molina2017Electroencephalographic,
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@misc{Nakanishi2017Detectingglaucomawith,
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@misc{JAPalmer2016JAPalmerSMakeig,
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@misc{Gola2016GolaMLewczukK,
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@misc{Gola2016GolaM2016Decrease2,
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@misc{Gola2016DOI1012740PPOnlineF,
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@misc{Gola2016Canpornographybeaddic,
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@misc{Wichniak2016WichniakAJarkiewicz,
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@misc{Gola2015GolaMMiyakoshiM,
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@misc{Wierzba2015WierzbaMRiegelM,
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@misc{Winkielman2015WinkielmanPOlszanow,
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@misc{Gola2015GolaMKowalewskaE,
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@misc{sccnGolaMWordechaM,
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@misc{Gola2015GolaMWordechaM,
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@misc{Gola2016GolaM2016Oneorm,
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@misc{Gola2016GolaMLewStarowicz,
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@misc{sccnGolaMPotenzaM,
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@misc{sccnGolaMinpressMec,
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@misc{sccnGolaMinpressTer,
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@misc{sccnGolaMinpressPsy,
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@misc{YutakaNonodaMakotoMiyakoshiAlejandroOjedaScottMakeigCsabaJuhszSandeepSoodEishiAsano2016YutakaNonodaMakotoM,
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@misc{CaterinaPiazzaChiaraCantianiZeynepAkalinAcarMakotoMiyakoshiAprilABenasichGianluigiReniAnnaMariaBianchiScottMakeig2016CaterinaPiazzaChiara,
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@misc{CaterinaPiazzaMakotoMiyakoshiZeynepAkalinAcarChiaraCantianiGianluigiReniAnnaMariaBianchiScottMakeig2016CaterinaPiazzaMakoto,
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@misc{Rissling2014RisslingAJMiyakosh,
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@misc{Tsai2014TsaiACJungTP,
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@misc{Wu2014WuYCCoulsonSCo,
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@misc{Patel2014PatelADIversenJ,
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@misc{Chen2014ChenSCSheHCC,
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@misc{Lin2014LinYPYangYHJ,
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@misc{Grandchamp2014GrandchampRBraboszc,
  title = {Grandchamp, R., Braboszcz, C., Delorme, A. Oculometric variations during mind wandering. F},
  author = {Grandchamp, R., Braboszcz, C., Delorme, A. Oculometric variations during mind wandering. Frontiers in Psychology},
  year = {2014},
  note = {Grandchamp, R., Braboszcz, C., Delorme, A. Oculometric variations during mind wandering. Frontiers in Psychology, 2014, doi: 10.3389/fpsyg.2014.00031.}
}

@misc{Ojeda2014OjedaABigdelyShaml,
  title = {Ojeda, A., Bigdely-Shamlo, N., Makeig, S. “MoBILAB: An open source toolbox for analysis an},
  author = {Ojeda, A., Bigdely-Shamlo, N., Makeig, S. “MoBILAB: An open source toolbox for analysis and visualization of mobile brain/body imaging data,” Frontiers in Human Neuroscience, 5;8:121, doi: 10.3389/fnhum},
  year = {2014},
  note = {Ojeda, A., Bigdely-Shamlo, N., Makeig, S. “MoBILAB: An open source toolbox for analysis and visualization of mobile brain/body imaging data,” Frontiers in Human Neuroscience, 5;8:121, doi: 10.3389/fnhum.2014.00121, 2014.}
}

@misc{Zao2014ZaoJKGanTTYou,
  title = {Zao, J.K., Gan,T-T., You, C-K., Rodríguez Méndez, S.C., Chung, C-E., Wang, Y-T., Mullen, T},
  author = {Zao, J.K., Gan,T-T., You, C-K., Rodríguez Méndez, S.C., Chung, C-E., Wang, Y-T., Mullen, T., Kothe, C., Yu, C., Hsiao, C-T., Chu, S., Shieh, C-K., Jung, T-P. Pervasive Brain Monitoring and Data Sharing based on Multi-tier Distributed Computing and Linked Data Technology, Frontiers in Human Neuroscience},
  year = {2014},
  note = {Zao, J.K., Gan,T-T., You, C-K., Rodríguez Méndez, S.C., Chung, C-E., Wang, Y-T., Mullen, T., Kothe, C., Yu, C., Hsiao, C-T., Chu, S., Shieh, C-K., Jung, T-P. Pervasive Brain Monitoring and Data Sharing based on Multi-tier Distributed Computing and Linked Data Technology, Frontiers in Human Neuroscience, 2014 Jun 3;8:370. doi: 10.3389/fnhum.2014.00370.}
}

@misc{Artoni2014ArtoniFMenicucciD,
  title = {Artoni, F., Menicucci, D., Delorme, A., Makeig, S., Micera, S. “RELICA: A method for estim},
  author = {Artoni, F., Menicucci, D., Delorme, A., Makeig, S., Micera, S. “RELICA: A method for estimating the reliability of independent components,” NeuroImage},
  year = {2014},
  note = {Artoni, F., Menicucci, D., Delorme, A., Makeig, S., Micera, S. “RELICA: A method for estimating the reliability of independent components,” NeuroImage, 2014. pii: S1053-8119(14)00752-6. doi: 10.1016/j.neuroimage.2014.09.010.}
}

@misc{Lin2014LinYPDuannJR,
  title = {Lin, Y-P., Duann, J-R., Feng, W., Chen, J-H., Jung, T-P. Revealing Spatio-spectral Electro},
  author = {Lin, Y-P., Duann, J-R., Feng, W., Chen, J-H., Jung, T-P. Revealing Spatio-spectral Electroencephalographic Dynamics of Musical Mode and Tempo Perception by Independent Component Analysis, Journal of Neural Engineering and Rehabilitation, 11:18},
  year = {2014},
  note = {Lin, Y-P., Duann, J-R., Feng, W., Chen, J-H., Jung, T-P. Revealing Spatio-spectral Electroencephalographic Dynamics of Musical Mode and Tempo Perception by Independent Component Analysis, Journal of Neural Engineering and Rehabilitation, 11:18, 2014. doi:10.1186/1743-0003-11-18.}
}

@misc{Zhang2014ZhangZJungTPM,
  title = {Zhang, Z., Jung, T-P., Makeig, S., Rao, B.D., Pi, Z. Spatiotemporal Sparse Bayesian Learni},
  author = {Zhang, Z., Jung, T-P., Makeig, S., Rao, B.D., Pi, Z. Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals, IEEE Transactions on Neural Systems & Rehabilitation Engineering},
  year = {2014},
  note = {Zhang, Z., Jung, T-P., Makeig, S., Rao, B.D., Pi, Z. Spatiotemporal Sparse Bayesian Learning with Applications to Compressed Sensing of Multichannel Physiological Signals, IEEE Transactions on Neural Systems & Rehabilitation Engineering, 2014. doi: 10.1109/TNSRE.2014.2319334.}
}

@misc{Chou2014ChouWCSheHCL,
  title = {Chou, W-C., She, H-C., Lai, K., Gramann, K., Jung, T-P. Temporal Dynamics and Cortical Net},
  author = {Chou, W-C., She, H-C., Lai, K., Gramann, K., Jung, T-P. Temporal Dynamics and Cortical Networks Engaged in Biological Concepts Encoding. Journal of Neuroscience and Neuroengineering, 3(1), 21–35},
  year = {2014},
  note = {Chou, W-C., She, H-C., Lai, K., Gramann, K., Jung, T-P. Temporal Dynamics and Cortical Networks Engaged in Biological Concepts Encoding. Journal of Neuroscience and Neuroengineering, 3(1), 21–35, 2014. doi:10.1166/jnsne.2014.1093.}
}

@misc{Gramann2014GramannKJungTP,
  title = {Gramann, K., Jung, T-P., Ferris, D.P., Lin, C-T., Makeig, S. Toward a new cognitive neuros},
  author = {Gramann, K., Jung, T-P., Ferris, D.P., Lin, C-T., Makeig, S. Toward a new cognitive neuroscience: modeling natural brain dynamics, Frontiers in Human Neuroscience},
  year = {2014},
  note = {Gramann, K., Jung, T-P., Ferris, D.P., Lin, C-T., Makeig, S. Toward a new cognitive neuroscience: modeling natural brain dynamics, Frontiers in Human Neuroscience, 2014, Jun 19;8:444. doi: 10.3389/fnhum.2014.00444.}
}

@misc{Balkan2015BalkanOKreutzDelga,
  title = {Balkan, O., Kreutz-Delgado, K., Makeig, S. “Covariance-domain Dictionary Learning for Over},
  author = {Balkan, O., Kreutz-Delgado, K., Makeig, S. “Covariance-domain Dictionary Learning for Overcomplete EEG Source Identification,” submitted to IEEE Transactions on Biomedical Engineering},
  year = {2015},
  note = {Balkan, O., Kreutz-Delgado, K., Makeig, S. “Covariance-domain Dictionary Learning for Overcomplete EEG Source Identification,” submitted to IEEE Transactions on Biomedical Engineering, 2015.}
}

@misc{Light2015LightGAMakeigS,
  title = {Light, G.A., Makeig, S. “EEG Biomarkers of Psychosis, Present and Future,” Biological Psyc},
  author = {Light, G.A., Makeig, S. “EEG Biomarkers of Psychosis, Present and Future,” Biological Psychiatry},
  year = {2015},
  note = {Light, G.A., Makeig, S. “EEG Biomarkers of Psychosis, Present and Future,” Biological Psychiatry, 2015.}
}

@misc{Liao2015LiaoYAkalinAcarZ,
  title = {Liao, Y., Akalin Acar, Z., Makeig, S., Deak, G. EEG imaging of toddlers during dyadic turn},
  author = {Liao, Y., Akalin Acar, Z., Makeig, S., Deak, G. EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions, NeuroImage, 112:52-60},
  year = {2015},
  note = {Liao, Y., Akalin Acar, Z., Makeig, S., Deak, G. EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions, NeuroImage, 112:52-60, 2015.}
}

@misc{Winkielman2015WinkielmanPOlszanow2,
  title = {Winkielman, P., Olszanowski, M., Gola, M. Faces in between: Evaluative responses to faces },
  author = {Winkielman, P., Olszanowski, M., Gola, M. Faces in between: Evaluative responses to faces reflect the interplay of features and task-dependent fluency, Emotion, 15(2), 232-242},
  year = {2015},
  note = {Winkielman, P., Olszanowski, M., Gola, M. Faces in between: Evaluative responses to faces reflect the interplay of features and task-dependent fluency, Emotion, 15(2), 232-242, 2015.}
}

@misc{Chen2015ChenXWangYGao2,
  title = {Chen, X., Wang, Y., Gao, S., Jung, T-P., Gao, X. Filter bank canonical correlation analysi},
  author = {Chen, X., Wang, Y., Gao, S., Jung, T-P., Gao, X. Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface, Journal of Neural Engineering, 12 046008},
  year = {2015},
  note = {Chen, X., Wang, Y., Gao, S., Jung, T-P., Gao, X. Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface, Journal of Neural Engineering, 12 046008, 2015. doi:10.1088/1741-2560/12/4/046008}
}

@misc{Delorme2015DelormeAMiyakoshi,
  title = {Delorme, A., Miyakoshi, M., Jung, T-P., Makeig, S. “Grand average ERP-image plotting and s},
  author = {Delorme, A., Miyakoshi, M., Jung, T-P., Makeig, S. “Grand average ERP-image plotting and statistics: A method for comparing variability in event-related single-trial EEG activities across subjects and conditions,” Frontiers in Human Neuroscience},
  year = {2015},
  note = {Delorme, A., Miyakoshi, M., Jung, T-P., Makeig, S. “Grand average ERP-image plotting and statistics: A method for comparing variability in event-related single-trial EEG activities across subjects and conditions,” Frontiers in Human Neuroscience, 2015.}
}

@misc{Lin2015LinCTPalNRW,
  title = {Lin, C-T., Pal, N. R., Wu, S-L., Liu, Y-T., Lin, Y-Y. An Interval Type-2 Neural Fuzzy Syst},
  author = {Lin, C-T., Pal, N. R., Wu, S-L., Liu, Y-T., Lin, Y-Y. An Interval Type-2 Neural Fuzzy System for Online System Identification and Feature Elimination. IEEE Transactions on Neural Networks and Learning Systems},
  year = {2015},
  note = {Lin, C-T., Pal, N. R., Wu, S-L., Liu, Y-T., Lin, Y-Y. An Interval Type-2 Neural Fuzzy System for Online System Identification and Feature Elimination. IEEE Transactions on Neural Networks and Learning Systems, 2015. 26(7), 1442–1455. doi:10.1109/TNNLS.2014.2346537.}
}

@misc{Zhang2015ZhangXWangYTW,
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  author = {Zhang, X., Wang, Y-T., Wang, Y., Jung, T-P., Huang, M., Cheng, C-K., Mandell, A.J. Ultra-Slow Frequency Bands Reflecting Potential Coherence Between Neocortical Brain Regions, Neuroscience},
  year = {2015},
  note = {Zhang, X., Wang, Y-T., Wang, Y., Jung, T-P., Huang, M., Cheng, C-K., Mandell, A.J. Ultra-Slow Frequency Bands Reflecting Potential Coherence Between Neocortical Brain Regions, Neuroscience, 2015. doi:10.1016/j.neuroscience.2014.12.050.}
}

@misc{Loo2015LooSLentarowiczA,
  title = {Loo, S., Lentarowicz, A., Makeig, S. “Use of EEG in child psychiatry research: Current sta},
  author = {Loo, S., Lentarowicz, A., Makeig, S. “Use of EEG in child psychiatry research: Current state and future directions,” Journal of Clinical Child Psychiatry},
  year = {2015},
  note = {Loo, S., Lentarowicz, A., Makeig, S. “Use of EEG in child psychiatry research: Current state and future directions,” Journal of Clinical Child Psychiatry, 2015.}
}

@misc{ChiaoYiWu2014ChiaoYiWuJiaYingSe,
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  note = {Chiao-Yi Wu, Jia Ying Serene Koh, Moon-Ho Ringo Ho, Makoto Miyakoshi, Toshiharu Nakai, Shen-Hsing Annabel Chen. (2014) Age-related differences in effective connectivity of brain regions involved in Japanese kanji processing with homophone judgment task. Brain and Language, 135: 32-41.}
}


@article{Wang202642065981,
  title = {Unified Online Adaptation Framework for Correlation Analysis-based Spatial Filtering Methods in SSVEP-based BCIs.},
  author = {Wang, Z and Shen, L and Mi, X and Cheng, L and Yang, Y and Wang, B and Jung, TP and Wan, F},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2026},
  doi = {10.1109/JBHI.2026.3689883},
  pmid = {42065981},
  url = {https://pubmed.ncbi.nlm.nih.gov/42065981/},
  abstract = {Online adaptation is a promising technique for achieving calibration-free recognition in user-friendly brain-computer interfaces (BCIs) but remains underexplored for steady-state visual evoked potential (SSVEP) recognition. In our previous work on online multi-stimulus canonical correlation analysis (OMSCCA), we introduced a state-of-the-art scheme for the online adaptation of SSVEP spatial filters. Despite its effectiveness, this approach can not be directly extended to other advanced spatial filtering methods, thereby seriously limiting the broader development of calibration-free algorithms. To address this limitation, we propose a unified online adaptation frame work for correlation analysis (CA)-based spatial filtering methods, encompassing both spatial filter computation and utilization. Specifically, we extend the least-squares (LS) unified framework originally designed for full calibration with large amounts of training data to the online adaptation scenario without any pre-calibration, thereby enabling continuous updates of spatial filters. Moreover, to sufficiently utilize spatial filters, we introduce a cross-stimulus transfer method for online adaptation of the common impulse response and generation of user-specific templates for all stimuli using limited online unlabeled data. Finally, leveraging the proposed unified framework, we adapt three advanced spatial filtering methods from their calibration based counter parts to online adaptation paradigms and validate their performance through simulation studies. Our results demonstrate the framework's effectiveness in promoting the development ofzero-calibration SSVEP-based BCIs. Compared to the OMSCCA, the proposed online adaptation methods canimprove the recognition performance by more than 12%. This work provides a generalizable approach for transforming existing calibration-based methods into adaptive, user-friendly solutions for practical BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Kim202641784410,
  title = {Three-ball cascade juggling as a paradigm to study complex motor task execution using mobile brain-body imaging (EEG).},
  author = {Kim, H and Miyakoshi, M and Kambara, H and Yoshimura, N and Makeig, S and Iversen, JR},
  journal = {Proceedings. Biological sciences},
  year = {2026},
  doi = {10.1098/rspb.2025.0823},
  pmid = {41784410},
  url = {https://pubmed.ncbi.nlm.nih.gov/41784410/},
  abstract = {Mobile brain-body imaging (MoBI) using EEG and motion capture allows us to study brain activity during natural tasks. While MoBI research has focused on gait and walking, we introduce three-ball cascade juggling as a new paradigm to explore sensorimotor brain dynamics. Successful juggling depends on tracking ball trajectories to guide motor planning. Since jugglers emphasize the apex position during learning, we hypothesized that trial-to-trial variations in apex position relate to brain activity, particularly in superior parietal regions involved in spatial attention. Our findings support this: variations in apex position correlated with 10-15 Hz alpha and low beta power in sources compatible with superior parietal cortex. The precise frequency band and timing varied across the three spatial directions. Additionally, lateral apex variations were encoded in a mirror-symmetric manner relative to the body midline. This study demonstrates the feasibility of using MoBI to investigate brain dynamics in complex motor tasks and provides insight into how the brain represents the critical ball apex position, laying the foundation for future research on its role in motor control and catch timing.},
  note = {PubMed query source: Scott Makeig}
}

@article{Momsen202641887027,
  title = {The influence of co-speech gestures on speech envelope tracking.},
  author = {Momsen, JP and Wu, YC and Coulson, S},
  journal = {Brain and language},
  year = {2026},
  doi = {10.1016/j.bandl.2026.105745},
  pmid = {41887027},
  url = {https://pubmed.ncbi.nlm.nih.gov/41887027/},
  abstract = {Here we investigate how co-speech gesture kinematics impact speech tracking - a neural index that captures the brain's sensitivity to acoustic parameters of continuous speech, especially low-frequency fluctuations in the amplitude of the speech envelope. To do this, we recorded EEG from 36 healthy adults as they watched a series of multimodal discourse clips, wherein the speaker's movements and gestures were either congruent or incongruent with their speech. Next, we constructed temporal response functions (TRFs) to decode speech amplitude information from EEG recorded as participants watched the discourse clips. Our analyses revealed a significant reduction in decoder performance for models trained on speech presented with incongruent gestures relative to congruent ones, suggesting the fidelity of the neural representation of the speech envelope was greater for speech accompanied by congruent gestures. Next, because the spatial and temporal properties of the forward TRF can be interpreted in a similar way to traditional event-related potentials, we constructed forward models of EEG elicited by the speech envelope. These analyses revealed that weights from the forward models began to diverge across conditions 200 ms after changes to the speech envelope as TRFs to speech paired with congruent gestures were suppressed relative to TRFs from incongruent speech-gesture pairings. Results from the current study indicate that bodily gestures influence cortical tracking of the acoustic envelope of continuous speech. These gesture congruity effects may result because expressive movements of the body influence the amplitude and pitch of accompanying speech, and the brain actively exploits their informativity for speech prosody.},
  note = {PubMed query source: Ying Wu}
}

@article{Kos202642295117,
  title = {The Development of the Paraphilic Disorders Short Screen (PDSS) and Its Examination in Diverse Populations: A Large, Multi-Nation Study.},
  author = {Koós, M and Nagy, L and Kraus, SW and Potenza, MN and Demetrovics, Z and Fuss, J and Klein, V and Chen, YL and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Sungkyunkwan University's research team and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Sexual abuse : a journal of research and treatment},
  year = {2026},
  doi = {10.1177/10790632261438676},
  pmid = {42295117},
  url = {https://pubmed.ncbi.nlm.nih.gov/42295117/},
  abstract = {To date, there is no reliable and valid screening tool for paraphilic disorders (PDs) based on the diagnostic criteria of the International Classification of Diseases (ICD-11). The present study aimed to develop and cross-culturally examine the cross-cultural applicability of a new screening tool for PDs following the ICD-11 guidelines. Top-down item development was conducted with expert practitioners in the field. Data were collected in 26 languages across 42 countries ( N  = 82,243; 39.5% men; 57.0% women; 3.4% gender-diverse;  M age  = 32.39 years,  SD  = 12.52). Cut-off scores were established per ICD-11 guidelines, and at-risk groups were compared with low-risk groups along theoretically relevant correlates (e.g., depression, anxiety). The Paraphilic Disorders Short Screen (PDSS) assesses seven paraphilias via 21 items. Voyeurism was most common paraphilic interest (PI) (19.42% of the total sample;  n  = 15,970), which also had the highest number of participants meeting the ICD-11 diagnostic cut-off (3.24%;  n  = 2,662). PI and PD groups consistently demonstrated more severe depression and anxiety symptoms than others. The PDSS is a reliable and valid screening tool that follows the latest ICD-11 guidelines; therefore, it has the capacity to enhance clinical practice and research by identifying individuals at risk.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Nagy202640099831,
  title = {Sexual Assertiveness Across Cultures, Genders, and Sexual Orientations: Validation of the Short Sexual Assertiveness Questionnaire (SAQ-9).},
  author = {Nagy, L and Koós, M and Kraus, DSW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Chen, JK and Ciocca, G and Corazza, O and Csako, R and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University’s Research Team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino, SM and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP and Claire Van Hout, M and Bőthe, B},
  journal = {Assessment},
  year = {2026},
  doi = {10.1177/10731911241312757},
  pmid = {40099831},
  url = {https://pubmed.ncbi.nlm.nih.gov/40099831/},
  abstract = {Sexual assertiveness (SA) is an important concept in understanding sexual well-being and decision-making. However, psychometric evaluation of existing measures of SA in diverse populations is largely lacking, hindering cross-cultural and comparative studies. This study validated the short version of the Sexual Assertiveness Questionnaire (SAQ-9) and examined its measurement invariance across several languages, countries, genders, sexual orientations, and relationship statuses among 65,448 sexually-active adults ( M age  = 32.98 years,  SD  = 12.08, 58% women, 2.74% gender-diverse individuals) taking part in the International Sex Survey. The scale demonstrated adequate psychometric properties. Measurement invariance tests indicated that the SAQ-9 is suitable for comparing individuals from different cultures, genders, sexual orientations, and relationship statuses, and significant group differences were also noted (e.g., gender-diverse individuals reported the highest levels of SA). Findings suggest that the SAQ-9 is a reliable and valid measure of SA and appropriate for use in diverse populations, with specific populations exhibiting varying levels of SA.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wen202641317874,
  title = {Satiety modulates reward processing in food addiction: Evidence from event-related potentials.},
  author = {Wen, Y and Zeng, Y and Zhou, X and Gola, M and Dong, X and Li, Y},
  journal = {Appetite},
  year = {2026},
  doi = {10.1016/j.appet.2025.108395},
  pmid = {41317874},
  url = {https://pubmed.ncbi.nlm.nih.gov/41317874/},
  abstract = {This study investigates the neural correlates of reward processing deficits in food addiction (FA), focusing on the anticipation and feedback phases under different metabolic states. Fifty-four participants (individuals with FA and healthy controls, HC) completed a food and monetary reward task during hungry and satiated states, with electroencephalography (EEG) recording. We specifically measured two event-related potentials (ERPs) associated with anticipation and feedback of reward: Stimulus-Preceding Negativity (SPN) and Feedback-Related Negativity (FRN). In addition, Yale Food Addiction Scale (YFAS) scores assessed addiction severity. Repeated-measures ANOVA and correlation analyses examined group differences and neural-behavioral associations. Behavioral data showed heightened food reward anticipation in individuals with FA during satiety. Participants with FA exhibited larger SPN for food rewards in the satiated state compared to HC, indicating persistent reward anticipation, while FRN was attenuated across both metabolic states in the FA group, reflecting persistent feedback deficits. Monetary rewards showed no group differences between HC and FA. The FRN amplitude correlated with YFAS scores, linking feedback impairment to addiction severity. These results highlight that FA is characterized by food-specific reward processing deficits, particularly exacerbated in satiety. Impaired FRN emerged as a key ERP marker of these deficits and correlated with addiction severity. These findings underscore the critical role of dysregulated reward feedback processing in FA, offering FRN as a potential target for diagnostic and therapeutic interventions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Zhao202642224752,
  title = {Safety guardrails in patient-facing large language model systems for chronic disease self-management: a realist review.},
  author = {Zhao, Y and Miao, Y and Luo, Y and Guo, R and Wang, H and Wu, Y},
  journal = {International journal of medical informatics},
  year = {2026},
  doi = {10.1016/j.ijmedinf.2026.106513},
  pmid = {42224752},
  url = {https://pubmed.ncbi.nlm.nih.gov/42224752/},
  abstract = {Patient-facing large language model (LLM) systems are increasingly proposed as scalable tools for chronic disease self-management support. In this setting, safety depends not only on factual accuracy but also on whether outputs are interpretable, trusted, and used safely over time. To explain how safety guardrails shape outcomes in patient-facing LLM-supported self-management across different task-risk, user, and interaction contexts. We conducted a realist review of LLM-based or LLM-enabled generative conversational systems used for self-management of long-term physical health conditions. Searches of PubMed, Web of Science Core Collection, IEEE Xplore, ACM Digital Library, and arXiv covered all indexed years to 1 April 2026 and used terms for chronic disease or self-management, patient-facing conversational systems, and LLMs or generative AI, identifying 1,154 records before deduplication. The core evidence base comprised 21 studies and 38 context-mechanism-outcome configurations (CMOCs). The patient-facing self-management task, rather than disease label, was the unit of synthesis. At the study level, the dominant patient-facing task was coded as low risk in 6 studies, moderate risk in 11, and high risk in 4; 17 studies evaluated mainly single-turn interactions and 4 included multi-turn, sequential, or simulated-consultation elements. Most evidence concerned simulated or expert-judged patient-facing tasks rather than sustained real-world deployment. Three patterns recurred. Provenance-related safeguards improved transparency and checkability more consistently than they ensured safe downstream action. Communication-oriented safeguards improved readability or perceived comprehensibility while leaving recurring gaps in completeness or actionability. Boundary-control strategies, including source-bounded retrieval, clinician deferral, and escalation support, became more important as task actionability and interaction complexity increased. In patient-facing chronic disease self-management, safety cannot be judged adequately by answer plausibility alone. This review develops a refined programme theory and a risk-linked, theory-generating heuristic framework, but many proposed mechanisms remain indirect and require real-world, longitudinal, multi-turn testing before deployment.},
  note = {PubMed query source: Ying Wu}
}

@article{Lim202642339284,
  title = {Prefrontal fNIRS hemodynamic correlates of attentional load during rapid serial visual presentation tasks.},
  author = {Lim, S and Dong, SY and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2026},
  doi = {10.3389/fnhum.2026.1843879},
  pmid = {42339284},
  url = {https://pubmed.ncbi.nlm.nih.gov/42339284/},
  abstract = {Despite the growing interest in functional near-infrared spectroscopy (fNIRS) for practical brain-computer interface (BCI) applications, prefrontal hemodynamic responses during rapid serial visual presentation (RSVP) tasks remain poorly characterized, even though these tasks demand sustained attentional engagement under fast-paced visual streams. We examined prefrontal cortex (PFC) activation and functional connectivity as indices of attentional monitoring during an RSVP task using a 15-channel prefrontal fNIRS device in 50 participants. Trials either contained one target image among nontargets or consisted entirely of nontarget images. Eleven statistical activation features from oxygenated (HbO) and deoxygenated (HbR) hemoglobin changes, and Fisher's r-to-z transformed inter-channel connectivity values were compared between conditions using paired-samples t-tests with false discovery rate correction. Response time and exploratory correlations between behavioral latency and hemodynamic features were also analyzed. The nontarget condition showed slightly higher HbO activation, mainly in amplitude-related features such as max and mean, suggesting increased sustained processing demands when target absence had to be confirmed. In contrast, HbR differences were more strongly characterized by distributional and transient-related features, including kurtosis, skewness, and peak-related features, suggesting complementary HbO and HbR sensitivity to task conditions. Connectivity analysis revealed condition-dependent inter-channel coupling patterns, with generally stronger HbO connectivity in the nontarget condition and a partially different HbR pattern. Response times were significantly longer in the nontarget condition and were more closely associated with temporal and distributional hemodynamic features than with amplitude-based features. These findings provide an initial exploratory characterization of condition-dependent prefrontal activation and connectivity differences during RSVP tasks, highlighting the potential of fNIRS as a practical tool for attentional monitoring and informing future multimodal neuroimaging approaches.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wei202641605144,
  title = {Predicting Attention Decline: An Integrated Beta-Band and SSVEP Approach for Visual Brain-Computer Interfaces.},
  author = {Wei, S and Huang, Y and Yu, H and Meng, J and Xu, R and Jung, TP and Xu, M and Ming, D},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2026},
  doi = {10.1109/TNSRE.2026.3658740},
  pmid = {41605144},
  url = {https://pubmed.ncbi.nlm.nih.gov/41605144/},
  abstract = {Real-time monitoring of sustained attention fluctuations during continuous complex tasks is vital for enhancing task performance and preventing accidents. Attention modulates neurons in the visual cortex in various ways to improve the visual sensitivity at an attended location. EEG-based brain-computer interfaces (BCIs) offer one of the most effective approaches for monitoring the state of human individuals. Whether transient responses evoked by brief stimuli, steady-state responses elicited by prolonged stimuli, or spontaneous neural oscillations, researchers can extract recognized electrophysiological features that reflect attention levels. However, unimodal features face inherent limitations, such as the low signal-to-noise ratio of transient responses and susceptibility of spontaneous rhythms to electrophysiological interference. Nevertheless, few studies have explored multimodal feature fusion for attention state monitoring. Here, we developed an innovative continuous go/no-go task to concurrently evoke both event-related potential (ERP) and steady-state visual evoked potential (SSVEP), while modulating spontaneous oscillatory activities through attentional engagement. To maximize the attentional modulation effect, we integrated the contrast-response functions of the modulation effect of attention on SSVEP and implemented 12 stimulus contrast levels to identify optimal visual stimulation intensity. Results from 25 subjects demonstrated that the decline in sustained attention during a continuous task was predictable before behavioral mistakes. Classification performance peaked at 31.60% stimulus contrast condition using the fused features combining spontaneous beta-band oscillations and SSVEP responses (average: 74.48%; best: 90.83%). These findings advance the development of more robust real-time attention monitoring systems based on BCI technology.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hoxha202642070681,
  title = {Modality-specific predictive templates in pre-stimulus EEG activity.},
  author = {Hoxha, I and Chevallier, S and Delorme, A and Amorim, MA},
  journal = {Neuropsychologia},
  year = {2026},
  doi = {10.1016/j.neuropsychologia.2026.109486},
  pmid = {42070681},
  url = {https://pubmed.ncbi.nlm.nih.gov/42070681/},
  abstract = {Perceptual decision-making is a combination of sensory information and prior beliefs. In order to perform actions in a timely fashion, it is necessary to anticipate the timing at which events occur, but also what event is more likely than the other. While EEG signatures of anticipation have been identified it is less clear whether classifiers trained on informative (cued) trials generalize to uncued trials and whether such decoded templates predict trial-by-trial shifts in decision strategy (e.g., drift-rate or starting-point changes in a Diffusion Decision Model). This study aimed to determine whether human participants anticipated a visual or auditory stimulus at the single-trial level in both cued and uncued trials. We found that pre-stimulus brain activity contains information about the expected upcoming stimulus and that this information can be successfully extracted from single-trial brain activity. Behavioral analyses revealed a connection between correct anticipation and shifts in decision strategy, while also validating the classification of uncued trials. Importantly, the classification of uncued trials confirms that expectations build even in the absence of triggers. These findings highlight the presence of single-trial, stimulus-specific neural signatures of anticipation, offering new insights into trial-to-trial variability in decision-making and advancing our understanding of cognitive processes.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Sun202641223103,
  title = {Joint-Shrinkage Pattern Matching for Small-Sample and Imbalanced ERP Decoding in Brain-Computer Interfaces.},
  author = {Sun, J and Meng, J and Wang, H and He, F and Jung, TP and Xu, M and Yu, H and Ming, D},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2026},
  doi = {10.1109/TBME.2025.3632096},
  pmid = {41223103},
  url = {https://pubmed.ncbi.nlm.nih.gov/41223103/},
  abstract = {Event-related potential (ERP)-based brain-computer interface (BCI) systems are approaching sub-microvolt-level resolution, enabling detailed decoding of sophisticated cognitive processes. This progress has increased the demand for robust classifiers. Current algorithms encounter two fundamental challenges when decoding ERPs: data scarcity and class imbalance. To address these challenges, we propose a joint-shrinkage pattern matching (JSPM) algorithm consisting of two modules. First, a novel joint-shrinkage spatial filter is constructed by integrating shrinkage-based regularization with the $\\mathcal\{\{l\}\}_\{2,\{\\bm\{p\}\}\}$-norm. This regularization approach effectively bridges the gap between complex structured regularization and implementation simplicity, which introduces automated regularization to enhance module robustness under data-scarce conditions. The $\\mathcal\{\{l\}\}_\{2,\{\\bm\{p\}\}\}$-norm provides a flexible feature distance measurement, enabling adaptation to data quality variability. Second, a weighted template matching module mitigates decision boundary shift caused by class imbalance. Using error-related potentials (ErrPs) as representative signals, we validated the algorithm through comprehensive comparisons. JSPM significantly outperformed 14 state-of-the-art classifiers on one self-collected and two public ErrP datasets. With only 40 imbalanced training samples, it achieved up to 14.84% higher average balanced accuracy (bAcc) than competing methods, maintaining a 4.88% average bAcc advantage over its nearest competitor. Notably, JSPM significantly enhanced inter-class discriminability for ErrP features with approximately 1 μV amplitude, achieving a maximum bAcc enhancement of 8.80% compared to deep learning methods. Overall, JSPM effectively addresses small-sample and imbalanced ERP decoding in BCI systems, facilitating the transition from laboratory research to real-world applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wahbeh202641985271,
  title = {Genomic correlates of self-reported psychic experiences: An exploratory analysis.},
  author = {Wahbeh, H and Delorme, A and Cannard, C and Rossner, R and Yount, G and Radin, D},
  journal = {Explore (New York, N.Y.)},
  year = {2026},
  doi = {10.1016/j.explore.2026.103416},
  pmid = {41985271},
  url = {https://pubmed.ncbi.nlm.nih.gov/41985271/},
  abstract = {Psychic experiences are widely reported across cultures, yet their potential biological underpinnings remain poorly understood. Survey research suggests such experience may run in families, raising the possibility of genetic contributions. This study explored associations between genomic variation and self-reported psychic experiences. Participants (N = 102) were English-speaking adults with at least one psychic experience and access to direct-to-consumer genetic data. Self-report measures assessed psychic experiences, paranormal beliefs, mental health, and personality. Raw genetic microarray files were standardized, quality-controlled, and analyzed using a Random Forest classifier to distinguish participants with low versus high psychic experience scores. Feature importance was assessed using permutation-based out-of-bag error, with p-values estimated from 200,000 random permutations and corrected using the false discovery rate (FDR). Participants were predominantly educated Caucasian females from the United States, reporting high paranormal beliefs and moderate levels of psychic experiences. Most first experiences occurred before age 24, and 82% reported family members with similar experiences. Genomic analysis identified 212 single-nucleotide polymorphisms significantly associated with psychic experience scores (FDR < 0.05). The strongest association was observed for rs10410488, mapping to ARHGEF18, a gene involved in calcium-dependent dendritic growth. Other significant RSIDs mapped to genes implicated in calcium signaling, brain structure, microtubule dynamics, estrogen pathways, and retinoic acid signaling. This exploratory study identified candidate genetic variants associated with self reported psychic experiences, but these findings should be considered preliminary. Future research with larger, more diverse cohorts and refined analytic methods will be essential to clarifying the genetic and neurobiological underpinnings of psychic phenomena.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Tao202642127061,
  title = {Fast BCIs: Leveraging Dual-Scale Time Windows with Test-Time Adaptation to Enhance Accuracy.},
  author = {Tao, W and Jia, Z and Yang, Y and Wong, CM and Li, C and Chen, X and Chen, CLP and Jung, TP and Wan, F},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2026},
  doi = {10.1109/TBME.2026.3692973},
  pmid = {42127061},
  url = {https://pubmed.ncbi.nlm.nih.gov/42127061/},
  abstract = {Brain-computer interfaces (BCIs) must deliver outputs rapidly in numerous practical applications. However, the decoding accuracy may decline significantly when the time window (TW) is too short, a challenge exacerbated by the increasing adoption of deep learning methods in BCIs. For fast yet accurate outputs, this paper introduces a dual-scale time window (DTW) strategy with test-time adaptation (TTA), wherein the short TW decoding benefits from long TW setting through the TTA mechanism. Specifically, this strategy employs two specialized networks trained on EEG data with a short TW and a long TW respectively: the Main Network (MainNet), optimized for fast recognition within the short TW, and the Auxiliary Network (AuxNet), which generates high-confidence pseudo-labels with the long TW to update the MainNet during testing. The AuxNet's assistance leads to more accurate outputs from the MainNet in the short TW. We evaluated the method across diverse paradigms, including motor imagery (MI), steady-state visually evoked potential (SSVEP), and event-related potential (ERP) tasks, covering both high and low signal-to-noise ratio (SNR) conditions. At a 0.5 s TW, DTW-TTA achieved 74.64 % accuracy and 29.69 bits/min ITR on BCI-IV 2b (MI), 80.15 % and 128.16 bits/min on GIGA (SSVEP) dataset, 91.86 % and 229.82 bits/min on Benchmark (SSVEP) dataset, and 92.13 % and 74.04 bits/min on a VR-ERP dataset, outperforming state-of-the-art baselines in all cases. These results demonstrate that DTW-TTA effectively stabilizes short TW decoding and can be seamlessly integrated into deep learning-based BCI systems across paradigms.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Delorme202642305856,
  title = {Exploring the mechanisms of biofield therapy through joint electrophysiological recordings in humans and mice.},
  author = {Delorme, A and Cusimano, A and Tran, M and Nguyen, P and Deng, D and Fields, C and Velíšek, L and Wagner, R and Yang, P and Cohen, L},
  journal = {IBRO neuroscience reports},
  year = {2026},
  doi = {10.1016/j.ibneur.2026.05.011},
  pmid = {42305856},
  url = {https://pubmed.ncbi.nlm.nih.gov/42305856/},
  abstract = {In this case study, a self-described biofield therapy (BT) therapist and a sham therapist participated in multiple (n = 24) treatment and control (non-treatment) sessions under double-blind conditions. During the treatment phases, BT and sham therapists attempted to influence mice with cancer and control mice, alternating BT with rest phases where no such efforts were made. Both the 64-channel EEG of the human participants and the simultaneous 3-channel EEG and 1-channel EMG of the mice were recorded. For human participants and for the analysis of human and mouse EEG comodulation, the EEG experimental setup was a 2 × 2 design, contrasting mouse type (cancer vs. control) against session type (BT vs. non-treatment; N = 8 in each of the four groups). For the mice EEG, the experimental setup was a 2x2x2 design, contrasting mouse type (cancer vs. control) against session type (treatment vs. non-treatment) and human participant (BT participant vs. sham participant). Although no changes in spectral power were detected in mice, a significant increase in theta band coherence indicates that this type of biofield therapy may influence large-scale neural coordination rather than localized activity. Concurrently, robust and reproducible alterations in the therapist's EEG across all frequency bands during treatment periods, irrespective of mouse condition, suggest a consistent physiological signature associated with the act of intentional BT. Treatment was associated with changes in EEG coherence and spectral correlation between human and mouse signals. In particular, we observed an interaction in which treatment differentially affected brain-to-brain coherence in cancer versus control mice. These findings describe condition-dependent alterations in coupled physiological measures and suggest a complex relationship between human and mouse neural activity during BT sessions, while remaining agnostic about the underlying mechanism. We also outline the study's limitations and potential for follow-up investigations, acknowledging that these exploratory physiological findings do not have any clinical implications and should not be interpreted as justification for cancer treatment or as a substitute for evidence-based medical care.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Yang202641201930,
  title = {Dual-Branch Attention-Based Frequency Domain Network for Cross-Subject SSVEP-BCIs.},
  author = {Yang, Y and Wang, Z and Jia, Z and Wang, B and Zhang, S and Wong, CM and Gao, X and Jung, TP and Wan, F},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2026},
  doi = {10.1109/JBHI.2025.3630249},
  pmid = {41201930},
  url = {https://pubmed.ncbi.nlm.nih.gov/41201930/},
  abstract = {Steady-state visual evoked potential-based brain-computer interfaces (SSVEP-BCIs) hold significant promise for enabling high-speed human-computer interaction in real-world scenarios. However, existing frequency-domain decoding methods treat frequency spectrum features (the real and imaginary spectrum features) as a single feature without considering their unique spatial and spectral characteristics, resulting in insufficient generalizable features and limited classification accuracy in cross-subject scenarios. To address this issue, we propose a Dual-Branch Attention-Based Frequency Domain Network (DB-AFDNet) to independently decode real and imaginary spectral components, aiming to acquire more discriminative and generalizable features for cross-subject applications. Specifically, we construct inter-branch attention similarity constraints to encourage the two branches to have similar attention properties, promoting to learn the consensus characteristics in the dual branches. Furthermore, we propose intra-branch orthogonality constraints to explore branch-specific discriminative features to learn generalizable features. Experimental studies on two public datasets, the Benchmark and Beta datasets, demonstrate that DB-AFDNet outperforms state-of-the-art methods in cross-subject classification, achieving a relative improvement of 1.36$\\%$ and 1.45$\\%$, respectively.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cho202641516730,
  title = {Decomposing Juggling Skill into Sequencing, Prediction, and Accuracy: A Computational Model with Low-Gravity VR Training.},
  author = {Cho, W and Kobayashi, M and Kambara, H and Tanaka, H and Kagawa, T and Sato, M and Kim, H and Miyakoshi, M and Makeig, S and Iversen, JR and Yoshimura, N},
  journal = {Sensors (Basel, Switzerland)},
  year = {2026},
  doi = {10.3390/s26010294},
  pmid = {41516730},
  url = {https://pubmed.ncbi.nlm.nih.gov/41516730/},
  abstract = {Juggling is a complex motor skill that requires multiple sub-skills and cannot be mastered without extensive practice. Although prior studies have quantified performance differences between novice and expert jugglers, none have attempted to quantitatively decompose these components or model their contribution to juggling performance. This longitudinal study presents a multimodal evaluation system that integrates computer vision, motion capture, and biosensing to quantify three key elements of juggling ability: Sequencing, Prediction, and Accuracy. Twenty beginners completed a 10-day, three-ball juggling experiment combining visuo-haptic virtual reality (VR) and real-world practice, with half training in reduced gravity, previously shown to enhance early-stage motor learning. The fitted Gamma-Log generalized linear model (GLM) indicated that Sequencing is the dominant factor of early skill acquisition, followed by Prediction and Accuracy. This study provides the first computational decomposition of juggling, demonstrates how multiple elements jointly contribute to performance, and results in a principled approach to characterizing motor learning in complex real-world tasks.},
  note = {PubMed query source: Scott Makeig}
}

@article{Liu202640864581,
  title = {Decoding Decision-Making and Feedback Interactions: Insights From EEG Activation Network.},
  author = {Liu, X and Shen, L and Wang, Z and Tao, W and Liu, S and Li, F and Xu, P and Jung, TP and Wan, F},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2026},
  doi = {10.1109/JBHI.2025.3602838},
  pmid = {40864581},
  url = {https://pubmed.ncbi.nlm.nih.gov/40864581/},
  abstract = {The interaction of the brain's decision-making and feedback stages is crucial for guiding human behavior. Previous studies mainly focused on the interaction immediately after the feedback, resulting in a limited understanding of brain communication dynamics during the interaction process. This study examined the communication dynamics of the brain network during decision-feedback interaction under various feedback conditions by employing a newly developed activation network approach to reveal its underlying neural mechanism. Thirty participants completed a decision-feedback task that involved a sequence of cue-induced predictions with highly predictable, somewhat predictable, and unpredictable feedback conditions. We constructed the activation network for all experimental stages using source-level EEG data in the alpha band. Notably, the brain exhibited the highest communication efficiency ($p < 0.05$) in receiving and integrating feedback with decision-making information during the feedback stage. Furthermore, the network-behavior correlations indicated that the brain tends to evaluate unexpected feedback under highly predictable conditions and expected feedback under unpredictable conditions, suggesting distinct neural strategies of the decision-feedback interaction process. Finally, we decoded the optimization process of decision-feedback interaction across the entire task. Although network correlations between the decision and feedback stages decreased over time (high predictable: $r = -0.447$, $p = 0.001$; unpredictable: $r = -0.305$, $p = 0.032$), classification accuracy significantly improved ($\{r = -0.448\}$, $p = 0.010$, best accuracy: 86.667% ) under the highly predictable condition, corresponding with enhanced prediction behavior. These results indicate the optimization process of the cognitive resources allocation that supports more efficient interaction and improved predictive performance. Our findings advance the understanding of the mechanisms of decision-feedback interaction.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{CastroCalvo202639560207,
  title = {Cross-Cultural Validation of the Sexual Desire Inventory (SDI-2) in 42 Countries and 26 Languages.},
  author = {Castro-Calvo, J and Beltrán-Martínez, P and Ballester-Arnal, R and Nagy, L and Koós, M and Kraus, SW and Demetrovics, Z and Potenza, MN and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Chen, L and Ciocca, G and Corazza, O and Csakó, R and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Hsieh, YP and Islam, S and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and Lopez-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosova, O and Orosz, G and Sungkyunkwan University's, RT and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Journal of sex research},
  year = {2026},
  doi = {10.1080/00224499.2024.2417023},
  pmid = {39560207},
  url = {https://pubmed.ncbi.nlm.nih.gov/39560207/},
  abstract = {Sexual desire is a complex construct with important implications for sexual functioning and well-being. In this research, we translated the Sexual Desire Inventory (SDI-2), a widely used scale for assessing sexual (desire), into 25 languages from English and used data from the International Sex Survey (ISS) to (a) investigate its psychometric properties (i.e. factorial structure, reliability, validity, and measurement invariance) and (b) explore the expression of sexual desire across different countries, genders, and sexual orientations. A total of 82,243 participants from 42 countries completed the SDI-2, along with other sexuality-related scales. Confirmatory factor analysis supported a three-factor solution for the SDI-2 (CFI = .980; RMSEA = .060), encompassing the domains of "Partner-related," "Attractive-person-related," and "Solitary" sexual desire. The reliability of the total score and subscales were excellent. Likewise, correlations with other sexuality-related variables were positive yet weak-to-moderate in effect size. Measurement invariance tests supported its use across countries, languages, genders, and sexual orientations. Analysis of SDI-2 scores according to these variables supported its ability to capture group-based differences in sexual desire. In sum, the SDI-2 constitutes a psychometrically robust measure for the assessment of sexual desire in non-clinical samples with utility in large-scale cross-cultural studies.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Ince202641879870,
  title = {Compulsive sexual behavior disorder (CSBD) and problematic pornography use (PPU): A comprehensive, interdisciplinary, and expert-informed narrative review with suggested future directions.},
  author = {Ince, C and Antons, S and Ashton, S and Borgogna, NC and Brand, M and Briken, P and Castro-Calvo, J and Chen, L and Coleman, E and Efrati, Y and Fernández, DP and Fuss, J and Gleason, N and Gola, M and Jennings, TL and Kowalewska, E and Kraus, SW and Lewczuk, K and Grubbs, JB and Lew-Starowicz, M and Love, T and Mestre-Bach, G and Potenza, MN and Rahm-Knigge, RL and De Tubino Scanavino, M and Stark, R and Demetrovics, Z and Bőthe, B},
  journal = {Journal of behavioral addictions},
  year = {2026},
  doi = {10.1556/2006.2025.00337},
  pmid = {41879870},
  url = {https://pubmed.ncbi.nlm.nih.gov/41879870/},
  abstract = {The nature and classification of dysregulated sexual behaviors remain widely debated. Compulsive Sexual Behavior Disorder (CSBD) and Problematic Pornography Use (PPU) are the two most commonly studied constructs in this area, each carrying significant implications for mental health, interpersonal functioning, and broader well-being. Although scientific output on these topics has expanded rapidly in the past decade, recent reviews have tended to focus on specific subthemes, single constructs, or narrow disciplinary perspectives. Accordingly, this review provides an updated and interdisciplinary overview of empirical and theoretical knowledge. In this narrative review, we summarize current knowledge regarding CSBD and PPU, with contributions from diverse experts across multiple disciplines (e.g., psychology, psychiatry, sexology, addiction science, neuroscience). We provide research and clinical perspectives to ensure a comprehensive and balanced discussion. We extensively summarize eleven key areas, namely historical context, conceptualization and symptomatology, assessment and measurement, epidemiology, co-occurring disorders, etiology, potential negative consequences, intervention, treatment, and policy considerations. Additionally, we consider underrepresented populations and contexts, including adolescents, LGBTQ+ (i.e., lesbian, gay, bisexual, trans, queer, and other diverse identities) individuals, women, and cultural factors. The review concludes with a critical discussion of prevailing controversies, methodological challenges, and key directions for future research. By providing a comprehensive and integrative overview, this work aims to advance scientific discourse, promote interdisciplinary collaborations, inform clinical practice, and support public health initiatives in the field of CSBD and PPU.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Yang202642315263,
  title = {Comparative effectiveness of different inhaler technique education modalities on clinical outcomes in patients with asthma and chronic obstructive pulmonary disease: a protocol for a systematic review and network meta-analysis of randomised controlled trials.},
  author = {Yang, X and Chen, X and Yang, C and Feng, M and Wu, Y},
  journal = {BMJ open},
  year = {2026},
  doi = {10.1136/bmjopen-2026-120185},
  pmid = {42315263},
  url = {https://pubmed.ncbi.nlm.nih.gov/42315263/},
  abstract = {Asthma and chronic obstructive pulmonary disease (COPD) collectively affect an estimated 475 million individuals worldwide, yet only 31% of patients achieve correct inhaler technique, a proportion that has not meaningfully improved over four decades of clinical practice. Critical technique errors are independently associated with poor disease control, increased exacerbation risk and greater healthcare utilisation. Although multiple educational modalities exist, no systematic review has applied network meta-analysis (NMA) to simultaneously compare and rank all six principal training approaches. This protocol describes a systematic review and NMA to generate comparative effectiveness evidence for inhaler technique training modality selection in adults with asthma or COPD. A Bayesian random-effects NMA will be conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses for Protocols (PRISMA-P) 2015, PRISMA-NMA and PRISMA 2020, with prospective PROSPERO registration (systematic search: June 2026; completion anticipated: February 2027). Seven databases will be searched from inception to June 2026 without language restriction: PubMed/MEDLINE, Embase, Cochrane Central Register of Controlled Trials (CENTRAL), Web of Science Core Collection, CINAHL, CNKI and Wanfang Data, supplemented by clinical trial registry searches. Eligible randomised controlled trials will enrol adults aged 18 years or older with confirmed asthma (Global Initiative for Asthma (GINA) criteria) or COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) criteria). Six intervention nodes defined a priori using the Template for Intervention Description and Replication (TIDieR) framework will be compared against usual care and each other: face-to-face physical demonstration, video and digital training, teach-to-goal training, pharmacist-led training, nurse or clinician-led training and sensor-assisted technique feedback training. Primary analyses comprise two disease-specific NMAs (asthma: Asthma Control Test; COPD: COPD Assessment Test) with a pooled exploratory NMA as secondary analysis, a prespecified sparsity contingency and Bayesian meta-regression for transitivity (four covariates in disease-specific NMAs: device category, baseline severity, number of training sessions and participant age; disease type is added as a fifth in the pooled NMA). Risk of bias will be assessed using the Cochrane Risk of Bias 2; certainty of evidence will be evaluated using the Confidence in Network Meta-Analysis framework. Formal ethical approval is not required. Findings will be published in a peer-reviewed respiratory or evidence synthesis journal, presented at ERS and ATS annual congresses and communicated to GINA, GOLD and NICE guideline development groups. CRD420261347918.},
  note = {PubMed query source: Ying Wu}
}

@article{Xu202641775487,
  title = {Comparative effectiveness and safety of digital health delivery models for pulmonary rehabilitation in patients with chronic obstructive pulmonary disease: a protocol for systematic review and network meta-analysis of randomised controlled trials.},
  author = {Xu, L and Chen, X and Yang, C and Feng, M and Wu, Y},
  journal = {BMJ open},
  year = {2026},
  doi = {10.1136/bmjopen-2025-115607},
  pmid = {41775487},
  url = {https://pubmed.ncbi.nlm.nih.gov/41775487/},
  abstract = {Chronic obstructive pulmonary disease (COPD) affects approximately 480 million individuals globally and is projected to reach 600 million by 2050, representing a substantial burden on healthcare systems and patient quality of life. Pulmonary rehabilitation is a cornerstone intervention for COPD management, delivering clinically meaningful improvements in exercise capacity, health-related quality of life and dyspnoea. Despite strong guideline recommendations and established efficacy, only 2%-4% of eligible patients with COPD access traditional centre-based pulmonary rehabilitation due to geographical barriers, transportation difficulties, scheduling conflicts and limited healthcare resources. Digital health technologies offer promising alternatives to overcome these access barriers while potentially maintaining therapeutic benefits. Various digital delivery models have emerged, including video-based telerehabilitation, virtual reality platforms, mobile health applications and web-based programmes. However, their comparative effectiveness remains unclear, limiting evidence-based clinical decision making. This systematic review and network meta-analysis will aim to compare and rank the effectiveness and safety of different digital health delivery models for pulmonary rehabilitation in patients with COPD, providing evidence to inform optimal intervention selection in clinical practice. We will conduct a systematic review and Bayesian network meta-analysis following Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Network Meta-Analyses guidelines. Comprehensive searches will be performed across five electronic databases (PubMed, Embase, Cochrane Central Register of Controlled Trials, Web of Science, CINAHL) from inception to January 2026, without language restrictions. Eligible studies will include randomised controlled trials comparing digital health delivery models for pulmonary rehabilitation in adults with COPD. Digital health interventions will be categorised into four distinct delivery models: video-based telerehabilitation, virtual reality rehabilitation, mobile health rehabilitation and web-based platform rehabilitation. Interventions combining multiple modalities will be categorised according to the predominant component based on intervention frequency, duration and primary therapeutic mechanism. Two independent reviewers will perform study selection, data extraction and risk of bias assessment using the Cochrane Risk of Bias 2 tool. The primary outcome will be change in 6 min walk distance. Key secondary outcomes will include disease-specific quality of life measures, dyspnoea severity, hospitalisation rates, exacerbation frequency, intervention adherence and adverse events. A Bayesian random-effects network meta-analysis will be conducted, calculating mean differences or ORs with 95% credible intervals. Treatment rankings will be estimated using surface under the cumulative ranking curve probabilities. Evidence certainty will be assessed using the Confidence in Network Meta-Analysis framework. Planned subgroup analyses will explore potential effect modifiers including disease severity, intervention duration, supervision mode and technological features. As this systematic review will use data from previously published studies, formal ethical approval is not required. Findings will be disseminated through peer-reviewed publication, presentations at relevant scientific conferences and communication to healthcare providers, policymakers and patient advocacy organisations. CRD420251268701.},
  note = {PubMed query source: Ying Wu}
}

@article{Wu202641637172,
  title = {Alleviating Job-Related Burnout in Medical Professionals through Guided Imagery Hypnotherapy.},
  author = {Wu, YC and Carrillosulub, E and Lange, L and Wells, N and Jackson, P and Thudiyanplackal, T and Mills, PJ},
  journal = {Journal of evidence-based integrative medicine},
  year = {2026},
  doi = {10.1177/2515690X261418396},
  pmid = {41637172},
  url = {https://pubmed.ncbi.nlm.nih.gov/41637172/},
  abstract = {This pilot study examines the impact of guided imagery hypnotherapy (GIH) on symptoms of job-related burnout in medical professionals. Nine adults (eight female) involved in direct medical care in the region of San Diego, California participated in eight consecutive weekly GIH sessions. Subjective measures of burn-out, compassion, and self-compassion were recorded roughly one week before the start of the hypnotherapy series (baseline session zero) and after the first, fourth, and final GIH sessions. Resting state electroencephalographic data (EEG) was also recorded at each of these measurement times. Additionally, EEG was recorded for the duration of the hypnotherapy protocol during sessions one, four, and eight. Two sets of frontal alpha asymmetry (FAA) scores were computed for each participant. First, for each session, FAA was derived from the cleaned, preprocessed EEG recorded for the full duration of the GIH protocol. Additionally, FAA was computed from segments of EEG centered on eleven key events associated with hypnosis and visualization during the protocol. Linear mixed model analysis revealed a reliable increase in self-compassion and a decrease in emotional exhaustion across the four measurement times. Further, a reliable shift toward left over right hemispheric dominance, indicated by increases in FAA, was observed both across and within sessions, suggesting an evolution toward approach-related self-regulation at short and longer time scales. These outcomes indicate the promising potential of GIH for alleviating symptoms of job-related burnout and improving self-regulation in response to challenging work situations.},
  note = {PubMed query source: Ying Wu}
}

@article{Kos202538905162,
  title = {Why Do People Watch Pornography? Cross-Cultural Validation of the Pornography Use Motivations Scale (PUMS) and Its Short Form (PUMS-8).},
  author = {Koós, M and Nagy, L and Kraus, SW and Demetrovics, Z and Potenza, MN and Gaudet, É and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chang, YH and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Hsieh, YP and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Štulhofer, A and NA Sungkyunkwan University’s research team and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Journal of sex research},
  year = {2025},
  doi = {10.1080/00224499.2024.2359641},
  pmid = {38905162},
  url = {https://pubmed.ncbi.nlm.nih.gov/38905162/},
  abstract = {Motivations for pornography use may vary across gender identities, sexual orientations, and geographical regions, warranting examination to promote individual and public health. The aims of this study were to validate the Pornography Use Motivations Scale (PUMS) in a diverse, multicultural sample, and develop a short form (PUMS-8) that can assess a wide range of pornography use motivations. Using data from 42 countries ( N  = 75,117; M age  = 32.07; SD age  = 12.37), enabled us to thoroughly evaluate the dimensionality, validity, and reliability of the Pornography Use Motivations Scale (PUMS), leading to the development of the more concise PUMS-8 short scale. Additionally, language-, nationality-, gender-, and sexual-orientation-based measurement invariance tests were conducted to test the comparability across groups. Both the PUMS and the PUMS-8 assess eight pornography use motivations, and both demonstrated excellent psychometric properties. Sexual Pleasure emerged as the most frequent motivation for pornography use across countries, genders, and sexual orientations, while differences were observed concerning other motivations (e.g. self-exploration was more prevalent among gender-diverse individuals than men or women). The motivational background of pornography use showed high similarity in the examined countries. Both the PUMS and the PUMS-8 are reliable and valid measurement tools to assess different types of motivations for pornography use across countries, genders, and sexual orientations. Both scales are recommended for use in research and clinical settings.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wen202540236895,
  title = {Transforming long-term adjunctive therapy for cognitive impairment: the role of multimodal self-adaptive digital medicine.},
  author = {Wen, D and Xing, Y and Yao, Y and Liang, G and Xing, Y and Jung, TP and Yu, H and Xie, X and Wan, X and Liu, T and Duan, D and Li, D and Zhou, Y},
  journal = {Frontiers in neurology},
  year = {2025},
  doi = {10.3389/fneur.2025.1571817},
  pmid = {40236895},
  url = {https://pubmed.ncbi.nlm.nih.gov/40236895/},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu202538797965,
  title = {Traditional Chinese Medicine: Communicating Informational and Symbolic Functions in the Linguistic Landscape.},
  author = {Wu, Y and Silver, RE and Guo, L},
  journal = {Health communication},
  year = {2025},
  doi = {10.1080/10410236.2024.2346676},
  pmid = {38797965},
  url = {https://pubmed.ncbi.nlm.nih.gov/38797965/},
  abstract = {While dissemination of information is a key function of health communication, signage at medical facilities has other functions: signs can be a type of marketing (e.g., services offered), can promote credibility and inspire trust, can exacerbate or ameliorate social inequalities and can provide educational opportunities. All of these functions are influenced by cultural, contextual and social factors as evidenced by a linguistic landscape (LL) perspective. Traditional Chinese medicine (TCM) is a particularly instructive case for considering the functions of signage in healthcare LL as it has a strong cultural component from its historical Chinese roots, but its practice has been popularized around the globe in recent years. Given the role of TCM as a main or complementary medical treatment and healthcare option, this study investigates TCM LLs as sites of healthcare communication. Specifically, we analyze a set of 1,659 signs from two TCM hospitals in a multilingual, ethnic minority region of China as a case study which can be useful for healthcare providers when considering their own use of LL. We describe the way language and other sign features are used for informational, symbolic and other functions, showing how explicit communication channels as well as implicit ideological channels can impact healthcare communication. We discuss these findings in light of the need for healthcare communication which is sensitive to stakeholder needs.},
  note = {PubMed query source: Ying Wu}
}

@article{Kothe202540959706,
  title = {The lab streaming layer for synchronized multimodal recording.},
  author = {Kothe, C and Shirazi, SY and Stenner, T and Medine, D and Boulay, C and Grivich, MI and Artoni, F and Mullen, T and Delorme, A and Makeig, S},
  journal = {Imaging neuroscience (Cambridge, Mass.)},
  year = {2025},
  doi = {10.1162/IMAG.a.136},
  pmid = {40959706},
  url = {https://pubmed.ncbi.nlm.nih.gov/40959706/},
  abstract = {Accurately recording the interactions of humans or other organisms with their environment and other agents requires synchronized data access via multiple instruments, often running independently using different clocks. Active, hardware-mediated solutions are often infeasible or prohibitively costly to build and run across arbitrary collections of input systems. The Lab Streaming Layer (LSL) framework offers a software-based approach to synchronizing data streams based on per-sample time stamps and time synchronization across a common local area network (LAN). Built from the ground up for neurophysiological applications and designed for reliability, LSL offers zero-configuration functionality and accounts for network delays and jitters, making connection recovery, offset correction, and jitter compensation possible. These features can ensure continuous, millisecond-precise data recording, even in the face of interruptions. In this paper, we present an overview of LSL architecture, core features, and performance in common experimental contexts. We also highlight practical considerations and known pitfalls when using LSL, including the need to take into account input device throughput delays that LSL cannot itself measure or correct. The LSL ecosystem has grown to support over 150 data acquisition device classes and to establish interoperability between client software written in several programming languages, including C/C++, Python, MATLAB, Java, C#, JavaScript, Rust, and Julia. The resilience and versatility of LSL have made it a major data synchronization platform for multimodal human neurobehavioral recording, now supported by a wide range of software packages, including major stimulus presentation tools, real-time analysis environments, and brain-computer interface applications. Beyond basic science, research, and development, LSL has been used as a resilient and transparent back-end in deployment scenarios, including interactive art installations, stage performances, and commercial products. In neurobehavioral studies and other neuroscience applications, LSL facilitates the complex task of capturing organismal dynamics and environmental changes occurring within and across multiple data streams on a common timeline.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Kothe202538405712,
  title = {The Lab Streaming Layer for Synchronized Multimodal Recording.},
  author = {Kothe, C and Shirazi, SY and Stenner, T and Medine, D and Boulay, C and Grivich, MI and Artoni, F and Mullen, T and Delorme, A and Makeig, S},
  journal = {bioRxiv : the preprint server for biology},
  year = {2025},
  doi = {10.1101/2024.02.13.580071},
  pmid = {38405712},
  url = {https://pubmed.ncbi.nlm.nih.gov/38405712/},
  abstract = {Accurately recording the interactions of humans or other organisms with their environment and other agents requires synchronized data access via multiple instruments, often running independently using different clocks. Active, hardware-mediated solutions are often infeasible or prohibitively costly to build and run across arbitrary collections of input systems. The Lab Streaming Layer (LSL) framework offers a software-based approach to synchronizing data streams based on per-sample time stamps and time synchronization across a common local area netowrk (LAN). Built from the ground up for neurophysiological applications and designed for reliability, LSL offers zero-configuration functionality and accounts for network delays and jitters, making connection recovery, offset correction, and jitter compensation possible. These features can ensure continuous, millisecond-precise data recording, even in the face of interruptions. In this paper, we present an overview of LSL architecture, core features, and performance in common experimental contexts. We also highlight practical considerations and known pitfalls when using LSL, including the need to take into account input device throughput delays that LSL cannot itself measure or correct. The LSL ecosystem has grown to support over 150 data acquisition device classes and to establish interoperability between client software written in several programming languages including C/C++, Python, MATLAB, Java, C#, JavaScript, Rust, and Julia. The resilience and versatility of LSL have made it a major data synchronization platform for multimodal human neurobehavioral recording, now supported by a wide range of software packages including major stimulus presentation tools, real-time analysis envirnoments, and brain-computer interface applications. Beyond basic science, research, and development, LSL has been used as a resilient and transparent back-end in deployment scenarios including interactive art installations, stage performances, and commercial products. In neurobehavioral studies and other neuroscience applications, LSL facilitates the complex task of capturing organismal dynamics and environmental changes occurring within and across multiple data streams on a common timeline.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wang202541198859,
  title = {StarWhisper Telescope: an AI framework for automating end-to-end astronomical observations.},
  author = {Wang, C and Zhang, Y and Li, Y and Hu, X and Mao, Y and Chen, X and Du, P and Wang, R and Wu, Y and Yang, H and Li, Y and Wang, B and Mu, H and Chen, X and He, S and Mo, H and Zhang, L and Du, L and Zhao, Y and Tian, J and Ge, L and Mao, Y and Li, S and Wang, Z and Lu, X and Zou, J and Huang, Y and Sun, N and Zheng, J and He, M and Bai, Y and Jin, J and Wu, H and Liu, J},
  journal = {Communications engineering},
  year = {2025},
  doi = {10.1038/s44172-025-00520-4},
  pmid = {41198859},
  url = {https://pubmed.ncbi.nlm.nih.gov/41198859/},
  abstract = {The exponential growth of large-scale telescope arrays has boosted time-domain astronomy development but introduced operational bottlenecks, including labor-intensive observation planning, data processing, and real-time decision-making. Here we present the StarWhisper Telescope system, an AI agent framework automating end-to-end astronomical observations for surveys like the Nearby Galaxy Supernovae Survey. By integrating large language models with specialized function calls and modular workflows, StarWhisper Telescope autonomously generates site-specific observation lists, executes real-time image analysis via pipelines, and dynamically triggers follow-up proposals upon transient detection. The system reduces human intervention through automated observation planning, telescope controlling and data processing, while enabling seamless collaboration between amateur and professional astronomers. Deployed across Nearby Galaxy Supernovae Survey's network of 10 amateur telescopes, StarWhisper Telescope has detected transients with promising response times relative to existing surveys. Furthermore, StarWhisper Telescope's scalable agent architecture provides a blueprint for future facilities like the Global Open Transient Telescope Array, where AI-driven autonomy will be critical for managing 60 telescopes.},
  note = {PubMed query source: Ying Wu}
}

@article{Ross202540777444,
  title = {Sensory Entrained TMS (seTMS) enhances motor cortex plasticity.},
  author = {Ross, JM and Forman, L and Hassan, U and Gogulski, J and Truong, J and Cline, CC and Parmigiani, S and Chen, NF and Hartford, JW and Fujioka, T and Makeig, S and Pascual-Leone, A and Keller, CJ},
  journal = {bioRxiv : the preprint server for biology},
  year = {2025},
  doi = {10.1101/2025.07.23.666433},
  pmid = {40777444},
  url = {https://pubmed.ncbi.nlm.nih.gov/40777444/},
  abstract = {Neural excitability fluctuates with sensory events, creating windows of opportunity to enhance brain stimulation. Repetitive transcranial magnetic stimulation (TMS), including intermittent theta burst stimulation (iTBS), is a promising treatment for neurological and psychiatric disorders, but does not account for fluctuations in neural excitability, likely contributing to variable outcomes. Sensory Entrained TMS (seTMS) leverages sensorimotor oscillations to enhance corticospinal responses, but the sustained effects as a repetitive protocol are unknown. We extend seTMS to iTBS, measuring motor-evoked potentials (MEPs) as a physiological readout. In a randomized crossover study comparing standard iTBS with sensory entrained iTBS (se-iTBS;  n =20), we found that se-iTBS more than doubled the MEP effect (55% vs 26% MEP enhancement) and persisted for at least 30 minutes. Notably, at least 80% of participants showed larger responses with se-iTBS at all time points. se-iTBS may provide a robust and practical framework for optimizing TMS that bridges electrophysiological mechanisms and clinical applications.},
  note = {PubMed query source: Scott Makeig}
}

@article{Ross202540622189,
  title = {Sensory Entrained TMS (seTMS) Enhances Motor Cortex Excitability.},
  author = {Ross, JM and Forman, L and Gogulski, J and Hassan, U and Cline, CC and Parmigiani, S and Truong, J and Hartford, JW and Chen, NF and Fujioka, T and Makeig, S and Pascual-Leone, A and Keller, CJ},
  journal = {Human brain mapping},
  year = {2025},
  doi = {10.1002/hbm.70267},
  pmid = {40622189},
  url = {https://pubmed.ncbi.nlm.nih.gov/40622189/},
  abstract = {Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS-evoked electrophysiological responses show significant fluctuation, due in part to inconsistencies between TMS pulse timing and ongoing brain oscillations. Small or inconsistent responses to TMS limit mechanistic insights and clinical efficacy, necessitating the development of methods to precisely coordinate the timing of TMS pulses to the phase of relevant oscillatory activity. We introduce Sensory Entrained TMS (seTMS), a novel approach that uses musical rhythms to synchronize brain oscillations and time TMS pulses to enhance cortical excitability. Focusing on the sensorimotor alpha rhythm, a neural oscillation associated with motor cortical inhibition, we examine whether rhythm-evoked sensorimotor alpha phase alignment affects primary motor cortical (M1) excitability in healthy young adults (n = 33). We first confirmed using electroencephalography (EEG) that passive listening to musical rhythms desynchronizes inhibitory sensorimotor brain rhythms (mu oscillations) around 200 ms before auditory rhythmic events (27 participants). We then targeted this optimal time window by delivering single TMS pulses over M1 200 ms before rhythmic auditory events while recording motor-evoked potentials (MEPs; 19 participants), which resulted in significantly larger MEPs compared to standard single pulse TMS and an auditory control condition. Neither EEG measures during passive listening nor seTMS-induced MEP enhancement showed dependence on musical experience or training. These findings demonstrate that seTMS effectively enhances corticomotor excitability and establishes a practical, cost-effective method for optimizing non-invasive brain stimulation outcomes.},
  note = {PubMed query source: Scott Makeig}
}

@article{Antonucci202540588523,
  title = {Self-amplifying NRF2-EZH2 epigenetic loop converts KRAS-initiated progenitors to invasive pancreatic cancer.},
  author = {Antonucci, L and Li, N and Duran, A and Cobo, I and Nicoletti, C and Watari, K and Nandi, SP and Zhu, F and Zhao, Y and Riahi, I and Tsuda, M and Shah, VM and Morgan, T and Waugh, T and Caputo, L and Liu, Y and Rundberg Nilsson, A and Xian, H and Todoric, J and Gu, L and Sanchez-Lopez, E and Eibl, G and Vucic, EA and Krawczyk, M and Xu, Q and Lowy, AM and Hatzivassiliou, G and Roose-Girma, M and Skowronska-Krawczyk, D and Scott, DA and Bar-Sagi, D and Tamayo, P and Wu, Y and Sears, RC and Glass, CK and Alexandrov, LB and Puri, PL and Dawson, DW and Hu, Y and Diaz-Meco, MT and Moscat, J and Karin, M},
  journal = {Nature cancer},
  year = {2025},
  doi = {10.1038/s43018-025-01003-3},
  pmid = {40588523},
  url = {https://pubmed.ncbi.nlm.nih.gov/40588523/},
  abstract = {Pancreatic ductal adenocarcinoma (PDAC) emerges from mutant KRAS-harboring but dormant low-grade pancreatic intraepithelial neoplasia (PanIN). To examine the role of oxidative stress, a putative PDAC risk factor, we established an organoid-based transformation system. Although the prototypic oxidant H 2 O 2  induced organoid transformation, its effect was nonmutational and was mediated by the oxidant-responsive transcription factor NRF2, which induced the histone methyltransferase EZH2. Congruently, nonoxidizing NRF2 activators triggered organoid malignant conversion through NRF2 and EZH2, establishing a hitherto unknown epigenetic mechanism underlying PanIN-to-PDAC progression. While NRF2 induced EZH2 gene transcription in mouse and human PDAC, EZH2, a general repressor, coactivated transcription of NRF2-encoding NFE2L2 and interacted with other transcription factors to induce genes that sustain PDAC metabolic demands. The self-amplifying NRF2-EZH2 epigenetic loop also accounted for inflammation-driven PanIN-to-PDAC progression in vivo and was upregulated in established human PDAC, whose malignancy was maintained by NRF2 binding to the EZH2 promoter.},
  note = {PubMed query source: Ying Wu}
}

@article{Aviad202539911539,
  title = {Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation.},
  author = {Aviad, N and Moskovich, O and Orenstein, O and Benger, E and Delorme, A and Bernstein, A},
  journal = {Biological psychiatry global open science},
  year = {2025},
  doi = {10.1016/j.bpsgos.2024.100423},
  pmid = {39911539},
  url = {https://pubmed.ncbi.nlm.nih.gov/39911539/},
  abstract = {There has been rapid growth of neuroelectrophysiological studies that aspire to uncover the "black box" of mindfulness and meditation. Reliance on traditional data analysis methods hinders understanding of the complex, nonlinear, multidimensional, and systemic nature of the functional neuroelectrophysiology of meditation states. Thus, to reveal the complex systemic neuroelectrophysiology of meditation, we applied a machine learning extreme gradient boosting classification algorithm and 4 complementary feature importance methods to extract systemic electroencephalography features characterizing mindful states from electroencephalography recorded during a focused attention meditation and a control mind-wandering state among 26 experienced meditators. The algorithm classified meditation versus mind-wandering states with 83% accuracy, with an area under the receiver operating characteristic curve of 79% and F1 score of 74%. Feature importance techniques identified 10 electroencephalography features associated with increased power and coherence of high-frequency oscillations during focused attention meditation relative to an instructed mind-wandering state. The findings help delineate the complex systemic oscillatory activity that characterizes meditation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{ZunigaHertz202540535580,
  title = {Multidimensional Analysis of Twin Sets During an Intensive Week-Long Meditation Retreat: A Pilot Study.},
  author = {Zuniga-Hertz, JP and Simpson, S and Chitetti, R and Hsu, CF and Huang, HP and Jinich-Diamant, A and Chernov, AV and Onton, JA and Cuomo, R and Dispenza, J and Davis, D and Christov-Moore, L and Reggente, N and Gu, W and Kong, M and Bonds, JA and Maree, J and Simonson, TS and Ahn, AC and Poirier, MA and Moeller-Bertram, T and Patel, HH},
  journal = {Mindfulness},
  year = {2025},
  doi = {10.1007/s12671-025-02584-x},
  pmid = {40535580},
  url = {https://pubmed.ncbi.nlm.nih.gov/40535580/},
  abstract = {Meditation has long been known to promote health. We utilized a multidisciplinary approach to investigate the impact of mind-body interventions on the body in a twin cohort during a week-long meditation retreat. This study was designed to address individual changes controlling for intersubject trait variation and explore the role of genetic background on multi-omic factors during meditation. Transcriptomic analysis was carried out from whole blood samples, while metabolomic and biochemical studies were carried out in blood plasma. Quantitative electroencephalography studies, coupled with biometric analysis and molecular studies at multiple time points, were carried out in twins meditating together and in twins separated and simultaneously either meditating or listening to a documentary. Changes in gene expression, metabolites, and cytokines in blood plasma associated with specific meditative states showed patterns of change relative to the time point being assessed. Twin sets were similar in multiple domains before the start of the retreat, showed considerable divergence at the mid-point, and looked more similar by the end of the retreat. Twin pairs showed significant spectral power correlations in separate rooms and when only one twin meditated. These similarities were not observed in mismatched twin pairs. Heart rate dynamics assessments showed alignment among twin pairs, absent between unmatched pairs. To our knowledge, this pilot study is novel within the twin research paradigm and is a first step toward exploring the effects of meditation in twins. This study was not preregistered and was carried out under IRB protocol MED02#20211477. The online version contains supplementary material available at 10.1007/s12671-025-02584-x.},
  note = {PubMed query source: Julie Onton}
}

@article{Duan202541274285,
  title = {Multi-center benchmarking of large language models for clinical decision support in lung cancer screening.},
  author = {Duan, Z and Huang, X and Lu, R and Xu, W and Liu, H and Geng, Y and Takahashi, N and Wu, Y and Wang, Q and Song, Y and Xu, H and Tang, H and Lan, F and Eils, R and Tan, L},
  journal = {Cell reports. Medicine},
  year = {2025},
  doi = {10.1016/j.xcrm.2025.102465},
  pmid = {41274285},
  url = {https://pubmed.ncbi.nlm.nih.gov/41274285/},
  abstract = {Large language models (LLMs) are increasingly explored for clinical applications, but their ability to generate management recommendations for lung cancer screening remains uncertain. In this cross-sectional, multi-center study, 148 anonymized low-dose computed tomography (CT) reports from three healthcare institutions are used to assess the readability, accuracy, and consistency of four widely adopted models (GPT-3.5, GPT-4, Claude 3 Sonnet, and Claude 3 Opus). Among them, Claude 3 Opus produces the most readable recommendations, while GPT-4 achieves the highest clinical accuracy. Importantly, performance dose not differ significantly across institutions, underscoring the robustness of these models to variations in reporting templates and their utility in diverse healthcare settings. In an exploratory analysis, two state-of-the-art models, proprietary GPT-4o and its open-source counterpart DeepSeek-R1, show comparable performance to GPT-4, outperforming GPT-3.5. These findings highlight the potential role of LLMs to enhance clinical decision support in lung cancer screening across diverse healthcare settings.},
  note = {PubMed query source: Ying Wu}
}

@article{GewirtzMeydan202539945771,
  title = {Motives for pornography use and women's sexual wellbeing: Insights from a 42-country study.},
  author = {Gewirtz-Meydan, A and Feder, H and Nagy, L and Koós, M and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University’s research team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Journal of behavioral addictions},
  year = {2025},
  doi = {10.1556/2006.2024.00040},
  pmid = {39945771},
  url = {https://pubmed.ncbi.nlm.nih.gov/39945771/},
  abstract = {Despite a growing body of research on pornography use among women, there is a lack of understanding of the problematic versus non-problematic nature. The current study aimed to investigate the relationship between women's motivations for pornography use and sexual wellbeing using a cross-sectional, self-report survey design among participants from 42 countries. The total sample included 82,243 participants, of whom 46,874 (57.0%) identified as women and were analyzed. The participants' age averaged at M = 29.67 years, with a standard deviation of SD = 10.11. Participants were asked to complete a questionnaire assessing their motivations for pornography use, as well as measures of sexual functioning, sexual desire, and sexual satisfaction. Study results suggest that across cultures, women's motivations for pornography use are associated with their sexual wellbeing. Specifically, when women reported using pornography for their own pleasure or sexual curiosity, it was associated with fewer sexual functioning problems and higher sexual desire. Conversely, when women reported using pornography due to a lack of sexual satisfaction in their relationships, it was associated with more sexual functioning problems. These findings highlight the need to consider the multifaceted nature of pornography use among women, including the usage motives, to fully understand associations with sexual wellbeing. Additionally, the study emphasizes the importance of conducting further research utilizing longitudinal designs, to establish the directionality between pornography use motivations and sexual wellbeing among women.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Li202540683191,
  title = {MetaNIRS: A general decoding framework for fNIRS based motor execution/imagery.},
  author = {Li, Y and Sun, Y and Wan, F and Yuan, Z and Jung, TP and Wang, H},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  year = {2025},
  doi = {10.1016/j.neunet.2025.107873},
  pmid = {40683191},
  url = {https://pubmed.ncbi.nlm.nih.gov/40683191/},
  abstract = {Functional near-infrared spectroscopy (fNIRS) is a crucial brain activity monitoring tool with remarkable potential applications in brain-computer interfaces (BCI), particularly in rehabilitation therapy for disabilities. However, the performance of fNIRS-based BCI systems remains suboptimal, such as motor execution (ME) and motor imagery (MI) decoding. Inspired by the successful application of the PoolFormer framework in visual tasks, we first proposed a novel long-range dilation multilayer perceptron (LongDilMLP) to utilize the hemodynamic characteristics of fNIRS. Furthermore, the LongDilMLP was integrated with the PoolFormer framework, called as MetaNIRS in this study. The proposed framework MetaNIRS was employed for both ME and MI classification tasks, achieving rigorous validation of its effectiveness and practical applicability. To evaluate the performance of MetaNIRS, two publicly available ME datasets (A and C) and one self-collected MI dataset (B) were employed. The experimental results demonstrated that the average accuracy were 76.00 %, 57.45 %, and 84.14 %, with cross-subject accuracy of 77.24 %, 58.55 %, and 85.52 %, respectively. Moreover, sensitivity experiments of model parameters showed the robustness. Ablation experiments highlighted the significance of each MetaNIRS component and the efficacy of LongDilMLP over traditional MLP. Additionally, visualization techniques enhanced the interpretability of MetaNIRS, indicating the main contribution of the first half signals for classification. Using the first half of signals, the average accuracy only reduced 4.30 %, 1.69 %, and 1.11 %, respectively. These findings suggest that the superior performance of MetaNIRS, which provide an efficient general decoding framework for ME and MI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hou202540338356,
  title = {Medication adherence trajectories and clinical outcomes in patients with cardiovascular disease: a systematic review and meta-analysis.},
  author = {Hou, Q and Zhao, Y and Wu, Y},
  journal = {Journal of global health},
  year = {2025},
  doi = {10.7189/jogh.15.04145},
  pmid = {40338356},
  url = {https://pubmed.ncbi.nlm.nih.gov/40338356/},
  abstract = {The role of medication adherence trajectories in the clinical outcomes in patients with cardiovascular diseases (CVDs) remains unclear. We aimed to analyse the impact of different medication adherence trajectories on mortality and other key clinical outcomes in patients with CVDs. We identified longitudinal cohort studies that reported the association between medication adherence trajectories and clinical outcomes in patients with CVDs by conducting a comprehensive search of the Cochrane Library, PubMed, Embase, CINAHL, and Web of Science databases, without applying language restrictions in August 2024. We pooled the published hazard ratios and 95% confidence intervals using random effects models and assessed potential bias through Egger regression analysis. In this meta-analysis, we included nine cohorts with 226 203 patients with a mean age of 66.1 years and a maximum follow-up of five years. Eight of the nine studies used the proportion of days covered to assess medication adherence. We identified four distinct medication adherence trajectories: persistent adherence, persistent nonadherence, gradually increasing adherence, and gradually declining adherence. Compared to persistent adherence, persistent nonadherence was associated with significantly higher risks of all-cause mortality, major adverse cardiovascular events (MACE), and recurrent venous thromboembolism, with risk increases ranging from 32% to nearly three times higher. Gradually increasing adherence was associated with a 26% higher risk of mortality and a 22% increased risk of MACE. In the group with gradually declining adherence, the risk of MACE increased by 24%, while the risk of major bleeding decreased by 43%. The overall risk of bias was low. Sensitivity analyses confirmed the consistency and robustness of these findings. This study underscores the substantial benefits of maintaining persistent adherence to prescribed medication regimens for patients with CVDs. Conversely, persistent nonadherence significantly elevates the risk of adverse clinical outcomes. PROSPERO: CRD42023456395.},
  note = {PubMed query source: Ying Wu}
}

@article{Zhou202540459935,
  title = {Love at first glance: Imbalanced processing to gaming and natural rewards in internet gaming disorder.},
  author = {Zhou, X and Zeng, Y and Wen, Y and Dong, X and Gola, M and Li, Y},
  journal = {Journal of behavioral addictions},
  year = {2025},
  doi = {10.1556/2006.2025.00044},
  pmid = {40459935},
  url = {https://pubmed.ncbi.nlm.nih.gov/40459935/},
  abstract = {Individuals with Internet Gaming Disorder (IGD) exhibit a heightened reward responsiveness to gaming-related rewards, alongside a diminished response to natural rewards. However, the temporal dynamics and neural correlates underlying this imbalanced processing remain unclear. This electrophysiological study investigated the neural responses associated with reward processing and their relationship to self-reported reward responsiveness. Using an Incentive Delay Task, we compared neural responses to gaming and monetary rewards between 25 IGD participants and 32 recreational game users (RGUs). Self-reported reward responsiveness was assessed with the Behavioral Approach/Inhibition System (BAS/BIS) scales. The IGD group scored higher on the BAS-responsiveness subscale. Correlation analysis indicated that enhanced BAS-responsiveness was associated with automatic attention (N1) to gaming feedback, but not with feedback monitoring (FRN) or emotional arousal (LPP). No such correlation was found in the monetary condition. Following initial automatic attention, the IGD group demonstrated selective feedback monitoring (FRN) for gaming rewards while neglecting monetary feedback. Gaming stimuli automatically capture the attention of individuals with IGD, triggering less top-down monitoring of other potential positive feedback. These findings suggest that attentional bias toward game-related stimuli serves as a sensitive biological marker of heightened reward responsiveness in individuals with IGD.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Cripe202540698201,
  title = {Independent Component Analysis (ICA) With Covariates Strengthens Behavioral Links in Electroencephalography (EEG) Connectivity.},
  author = {Cripe, CT and Delorme, A},
  journal = {Cureus},
  year = {2025},
  doi = {10.7759/cureus.86533},
  pmid = {40698201},
  url = {https://pubmed.ncbi.nlm.nih.gov/40698201/},
  abstract = {The search for reliable biomarkers of clinical and cognitive deficits remains the holy grail of clinical neuroscience, with improved predictive methods and neural correlates paving the way for more effective treatments. Independent component analysis (ICA) has been widely applied in electroencephalography (EEG) signal processing to isolate neural activity from artifacts and noise. This study introduces a novel approach by integrating clinical covariates - behavioral assessments from the Woodcock-Johnson Cognitive Abilities Test III (WJ) Tests - into ICA, enabling the simultaneous decomposition of EEG connectivity patterns and cognitive performance metrics. Using functional connectivity measures as input, we applied two ICA methodologies to a dataset of 175 patients: (1) conventional ICA on EEG connectivity data, followed by correlation analysis with WJ scores, and (2) an augmented ICA approach incorporating both EEG connectivity and WJ measures. Our findings demonstrate that integrating behavioral data into ICA decomposition enhances the significance and robustness of correlations between EEG connectivity and cognitive performance in independent test datasets. These results underscore the potential of ICA with integrated covariates as a powerful multivariate framework for uncovering brain-behavior relationships, offering new insights for clinical and cognitive neuroscience research.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Miao202541118646,
  title = {Improving Large Language Model Applications in the Medical and Nursing Domains With Retrieval-Augmented Generation: Scoping Review.},
  author = {Miao, Y and Zhao, Y and Luo, Y and Wang, H and Wu, Y},
  journal = {Journal of medical Internet research},
  year = {2025},
  doi = {10.2196/80557},
  pmid = {41118646},
  url = {https://pubmed.ncbi.nlm.nih.gov/41118646/},
  abstract = {Retrieval-augmented generation (RAG) is increasingly used to improve large language models in the medical and nursing domains. However, a comprehensive understanding of its specific architecture and applications in medical and nursing reasoning remains limited. We aimed to summarize the current state, existing limitations, and future development directions of RAG in the medical and nursing domains. The PubMed, Web of Science, IEEE Xplore, and arXiv databases were searched for relevant articles using queries that combined terms related to RAG, medical, and nursing domains, covering the period from November 1, 2022, to May 31, 2025. This review was conducted following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews) guidelines. A total of 917 articles were retrieved, of which 67 met the inclusion criteria. Most studies focused on the medical domain (63/67, 94%), while only a few addressed nursing applications (4/67, 6%). The RAG frameworks included in this review were categorized into 5 functional types: text-based RAG (36/67, 54%), knowledge graph-enhanced RAG (17/67, 25%), agentic RAG (6/67, 9%), multimodal RAG (2/67, 3%), and plug-and-play RAG (6/67, 9%). On the basis of the Simon decision-making process theory, we divided the RAG workflow into 4 stages: intent recognition, knowledge retrieval, knowledge integration, and generation. Only 26 studies included explicit reasoning support, and few were aligned with real-world clinical workflows. Only 12 studies attempted to address ethical considerations related to RAG. We identified 4 key shifts in recent RAG development: shifting from surface-level matching toward contextualized intent recognition, from vague semantics toward logic-driven dynamic retrieval, from passive toward active knowledge retrieval, and from simple aggregation toward coherent context construction. However, most RAG systems in the medical and nursing domains have not yet introduced reasoning methods, and those that have are still predominantly reliant on data‑driven associations without causal modeling. This highlights the need to integrate causal mechanisms for more effective and domain-relevant reasoning in health care. OSF Registries 10.17605/OSF.IO/WBSV5; https://osf.io/wbsv5.},
  note = {PubMed query source: Ying Wu}
}

@article{Bthe202539945767,
  title = {Identification and comprehensive characterization of moral disapproval and behavioral dysregulation-based pornography-use profiles across 42 countries.},
  author = {Bőthe, B and Tóth-Király, I and Popova, N and Nagy, L and Koós, M and Demetrovics, Z and Potenza, MN and Kraus, SW and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Czakó, A and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's Research Team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Grubbs, JB},
  journal = {Journal of behavioral addictions},
  year = {2025},
  doi = {10.1556/2006.2024.00054},
  pmid = {39945767},
  url = {https://pubmed.ncbi.nlm.nih.gov/39945767/},
  abstract = {The Moral Incongruence Model of Pornography Use proposes that pornography-use-related problems may be present due to problematic pornography use (PPU) and/or moral disapproval (MD) of pornography use. Despite some supporting empirical evidence, no study has tested the presence of different pornography-use profiles based on individuals' behavioral dysregulation (i.e., PPU) and moral values concerning pornography use. The generalizability of previous findings to diverse populations has also been limited given the scarcity of studies conducted outside of Western countries. Using data from the International Sex Survey (42 countries, N = 66,994; Mage = 32.16 years, SD = 12.27), we conducted latent profile analysis to identify pornography-use profiles based on individuals' frequency of use, MD, and PPU. The profiles were compared along a wide range of pornography-use-related, sexuality-related, and psychological correlates. Six pornography-use profiles were identified, including two increased risk groups (i.e., Increased risk of PPU without MD and Increased risk of PPU with some MD). Several factors differentiated between the increased risk vs. no/low risk profiles (e.g., relatedness satisfaction) as well as between the two increased risk profiles (e.g., religiosity). Apart from behavioral dysregulation, moral values concerning pornography use played an important role in distinguishing pornography-use profiles and demonstrated the importance of inquiring about MD when working with individuals with pornography-use-related problems. Findings also support recent calls for better-integrated sex therapy and sexual medicine perspectives into pornography-use-related problems research and care.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Hermes202540830348,
  title = {Hierarchical Event Descriptor library schema for EEG data annotation.},
  author = {Hermes, D and Pal Attia, T and Beniczky, S and Bosch-Bayard, J and Delorme, A and Lundstrom, BN and Rogers, C and Rampp, S and Shirazi, SY and Truong, D and Valdes-Sosa, P and Worrell, G and Makeig, S and Robbins, K},
  journal = {Scientific data},
  year = {2025},
  doi = {10.1038/s41597-025-05791-2},
  pmid = {40830348},
  url = {https://pubmed.ncbi.nlm.nih.gov/40830348/},
  abstract = {Standardizing terminology to annotate electrophysiological events can improve both computational research and clinical care. Enriching data with standard terms facilitates data exploration, from case studies to mega-analyses. The machine readability of such electrophysiological event annotations is essential for performing automated analyses. The Hierarchical Event Descriptor (HED) framework provides a standard for describing events in neuroscience experiments but does not yet include terms for electrophysiological data features. The Standardized Computer-based Organized Reporting of EEG (SCORE) defines terms for EEG features but is not yet openly available in machine-readable format. This study therefore developed a HED library schema for SCORE: the HED-SCORE library schema. This library schema makes the SCORE terms machine-readable and searchable and extents the standard HED schema with a controlled hierarchical vocabulary to annotate electrophysiological events. We demonstrate that the HED-SCORE library schema can be used to annotate events in EEG data stored in the Brain Imaging Data Structure (BIDS). Clinicians and researchers worldwide can use the HED-SCORE library schema to annotate and compute on human electrophysiological data.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wang202539993330,
  title = {GraphSleepFormer: a multi-modal graph neural network for sleep staging in OSA patients.},
  author = {Wang, C and Jiang, X and Lv, C and Meng, Q and Zhao, P and Yan, D and Feng, C and Xu, F and Lu, S and Jung, TP and Leng, J},
  journal = {Journal of neural engineering},
  year = {2025},
  doi = {10.1088/1741-2552/adb996},
  pmid = {39993330},
  url = {https://pubmed.ncbi.nlm.nih.gov/39993330/},
  abstract = {Objective. Obstructive sleep apnea (OSA) is a prevalent sleep disorder. Accurate sleep staging is one of the prerequisites in the study of sleep-related disorders and the evaluation of sleep quality. We introduce a novel GraphSleepFormer (GSF) network designed to effectively capture global dependencies and node characteristics in graph-structured data. Approach. The network incorporates centrality coding and spatial coding into its architecture. It employs adaptive learning of adjacency matrices for spatial encoding between channels located on the head, thereby encoding graph structure information to enhance the model's representation and understanding of spatial relationships. Centrality encoding integrates the degree matrix into node features, assigning varying degrees of attention to different channels. Ablation experiments demonstrate the effectiveness of these encoding methods. The Shapley Additive Explanations (SHAP) method was employed to evaluate the contribution of each channel in sleep staging, highlighting the necessity of using multimodal data. Main results. We trained our model on overnight polysomnography data collected from 28 OSA patients in a clinical setting and achieved an overall accuracy of 80.10%. GSF achieved performance comparable to state-of-the-art methods on two subsets of the ISRUC database. Significance. The GSF Accurately identifies sleep periods, providing a critical basis for diagnosing and treating OSA, thereby contributing to advancements in sleep medicine.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Li202539993452,
  title = {From text to insight: A natural language processing-based analysis of burst and research trends in HER2-low breast cancer patients.},
  author = {Li, M and Zheng, A and Song, M and Jin, F and Pang, M and Zhang, Y and Wu, Y and Li, X and Zhao, M and Li, Z},
  journal = {Ageing research reviews},
  year = {2025},
  doi = {10.1016/j.arr.2025.102692},
  pmid = {39993452},
  url = {https://pubmed.ncbi.nlm.nih.gov/39993452/},
  abstract = {With the intensification of population aging, the proportion of elderly breast cancer patients is continuously increasing, among which those with low HER2 expression account for approximately 45 %-55 % of all cases within traditional HER2-negative breast cancer. Concurrently, the significant therapeutic effect of T-DXd on patients with HER2-low tumors has brought this group into the public spotlight. Since the clinical approval of T-DXd in 2019, there has been a significant vertical surge in the volume of publications within this domain. We analyzed 512 articles on HER2-low breast cancer from the Web of Science Core Collection using bibliometrics, topic modeling, and knowledge graph techniques to summarize the current state and trends of research in this domain. Research efforts are particularly concentrated in the United States and China. Our analysis revealed six main research directions: HER2 detection, omics and clinical biomarkers, basic and translational research, neoadjuvant therapy and prognosis, progress of ADC drugs and clinical trials. To enhance the therapeutic efficacy and safety of antibodydrug conjugates (ADCs), researchers are actively exploring potential drug candidates other than T-DXd, with numerous ADC drugs emerging in clinical practice and trials. By incorporating emerging treatment strategies such as immunotherapy and employing circulating tumor cell (CTC) detection techniques, progress has been made toward improving the prognosis of patients with low HER2 expression. We believe that these research efforts hold promise as compelling evidence that HER2-low breast cancer may constitute a distinct and independent subtype.},
  note = {PubMed query source: Ying Wu}
}

@article{Adamus202540063093,
  title = {Exploring the role of the amygdala in Compulsive Sexual Behavior Disorder via a parcellation pipeline based on Recurrence Quantification Analysis.},
  author = {Adamus, S and Bielski, K and Szatkowska, I and Gola, M and Draps, M},
  journal = {Journal of behavioral addictions},
  year = {2025},
  doi = {10.1556/2006.2025.00014},
  pmid = {40063093},
  url = {https://pubmed.ncbi.nlm.nih.gov/40063093/},
  abstract = {Despite the inclusion of Compulsive Sexual Behavior Disorder (CSBD) in the ICD-11, there are many open questions on its neuronal pathogenesis, especially regarding the role of the amygdala. In this study, we aimed to further unravel this issue via a parcellation method based on Recurrence Quantification Analysis (RQA). The RQA pipeline was applied to resting-state functional magnetic resonance imaging data from 45 heterosexual males with CSBD and 26 Healthy Controls. Each amygdala was divided into two subdivisions in each group. In the CSBD group, the scores of psychological questionnaires were used as covariates in a second-level seed-to-voxel connectivity analysis with the amygdala as a region of interest. Obtained parcellations revealed bilateral differences in the sizes of dorsomedial (DM) and ventrolateral (VL) amygdala between groups. Mean values of Shannon's Entropy in the left DM and right VL amygdala correlated negatively with depression level, anxiety, and impulsivity, which might represent a vulnerability to CSBD, but only the right VL was implicated in the severity of CSBD symptoms. Multiple correlations between resting-state functional connectivity of the amygdala subdivisions and CSBD severity were observed, especially between the left VL amygdala and several default mode network nodes. This is the first attempt to explore the role of the amygdala in CSBD by a parcellation method. Our results suggest the importance of the right VL amygdala in understanding the pathogenesis of the severity of CSBD symptoms, which highlights the rising need to explore the amygdala as a complex structure with diverse functions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Luo202539555676,
  title = {Exploring the Current Applications and Effectiveness of ChatGPT in Nursing: An Integrative Review.},
  author = {Luo, Y and Miao, Y and Zhao, Y and Li, J and Wu, Y},
  journal = {Journal of advanced nursing},
  year = {2025},
  doi = {10.1111/jan.16628},
  pmid = {39555676},
  url = {https://pubmed.ncbi.nlm.nih.gov/39555676/},
  abstract = {To systematically review the current application status of ChatGPT in nursing and explore its application effects. An integrative review. Following inclusion and exclusion criteria, two researchers summarised the selected literature and conducted a quality appraisal, followed by narrative synthesis. PubMed, Web of Science and Scopus were searched from January 2022 to June 2024. A total of 31 papers met the inclusion criteria. Fifteen empirical studies were rated as grade 5, while five were rated as grade 4. The references of a minireview were not recently published and lacked ChatGPT-related articles, and a systematic review was of low quality. The review focused on three main topics: (1) The subsidiary role of ChatGPT in nursing; (2) Comparison of different models' effectiveness and (3) Existing challenges. While adopting new technologies such as ChatGPT, it is important to maintain a balanced perspective on both its benefits and limitations. Nursing professionals must actively address these deficiencies and explore solutions to improve ChatGPT's utility in the field. This review synthesised evidence on ChatGPT's application and highlighted existing challenges in nursing. Nursing researchers, educators and practitioners can further validate these findings to explore its potential in various aspects of nursing practice. For researchers, ChatGPT can enhance language quality and summarise findings effectively, but adherence to research standards is crucial. For educators, ChatGPT can serve as an effective information source for students, though caution should be taken to avoid overreliance. For practitioners, ChatGPT can offer useful suggestions for clinical practice, but these should be critically evaluated and not followed blindly, as issues of inaccuracy must be addressed. This review adhered to Preferred Reporting Items for Systematic Reviews and Meta-Analyses. No patient or public contribution.},
  note = {PubMed query source: Ying Wu}
}

@article{Fournier202539054862,
  title = {Evaluating the factor structure and measurement invariance of the 20-item short version of the UPPS-P Impulsive Behavior Scale across multiple countries, languages, and gender identities.},
  author = {Fournier, L and Bőthe, B and Demetrovics, Z and Koós, M and Kraus, SW and Nagy, L and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Saiful Islam, M and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Sungkyunkwan University Research Team and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Tsai, MC and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Billieux, J},
  journal = {Assessment},
  year = {2025},
  doi = {10.1177/10731911241259560},
  pmid = {39054862},
  url = {https://pubmed.ncbi.nlm.nih.gov/39054862/},
  abstract = {The UPPS-P Impulsive Behavior Model and the various psychometric instruments developed and validated based on this model are well established in clinical and research settings. However, evidence regarding the psychometric validity, reliability, and equivalence across multiple countries of residence, languages, or gender identities, including gender-diverse individuals, is lacking to date. Using data from the International Sex Survey ( N  = 82,243), confirmatory factor analyses and measurement invariance analyses were performed on the preestablished five-factor structure of the 20-item short version of the UPPS-P Impulsive Behavior Scale to examine whether (a) psychometric validity and reliability and (b) psychometric equivalence hold across 34 country-of-residence-related, 22 language-related, and three gender-identity-related groups. The results of the present study extend the latter psychometric instrument's well-established relevance to 26 countries, 13 languages, and three gender identities. Most notably, psychometric validity and reliability were evidenced across nine novel translations included in the present study (i.e., Croatian, English, German, Hebrew, Korean, Macedonian, Polish, Portuguese-Portugal, and Spanish-Latin American) and psychometric equivalence was evidenced across all three gender identities included in the present study (i.e., women, men, and gender-diverse individuals).},
  note = {PubMed query source: Mateusz Gola}
}

@article{Pan202540294568,
  title = {Enhancing motor imagery EEG classification with a Riemannian geometry-based spatial filtering (RSF) method.},
  author = {Pan, L and Wang, K and Huang, Y and Sun, X and Meng, J and Yi, W and Xu, M and Jung, TP and Ming, D},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  year = {2025},
  doi = {10.1016/j.neunet.2025.107511},
  pmid = {40294568},
  url = {https://pubmed.ncbi.nlm.nih.gov/40294568/},
  abstract = {Motor imagery (MI) refers to the mental simulation of movements without physical execution, and it can be captured using electroencephalography (EEG). This area has garnered significant research interest due to its substantial potential in brain-computer interface (BCI) applications, especially for individuals with physical disabilities. However, accurate classification of MI EEG signals remains a major challenge due to their non-stationary nature, low signal-to-noise ratio, and sensitivity to both external and physiological noise. Traditional classification methods, such as common spatial pattern (CSP), often assume that the data is stationary and Gaussian, which limits their applicability in real-world scenarios where these assumptions do not hold. These challenges highlight the need for more robust methods to improve classification accuracy in MI-BCI systems. To address these issues, this study introduces a Riemannian geometry-based spatial filtering (RSF) method that projects EEG signals into a lower-dimensional subspace, maximizing the Riemannian distance between covariance matrices from different classes. By leveraging the inherent geometric properties of EEG data, RSF enhances the discriminative power of the features while maintaining robustness against noise. The performance of RSF was evaluated in combination with ten commonly used MI decoding algorithms, including CSP with linear discriminant analysis (CSP-LDA), Filter Bank CSP (FBCSP), Minimum Distance to Riemannian Mean (MDM), Tangent Space Mapping (TSM), EEGNet, ShallowConvNet (sCNN), DeepConvNet (dCNN), FBCNet, Graph-CSPNet, and LMDA-Net, using six publicly available MI-BCI datasets. The results demonstrate that RSF significantly improves classification accuracy and reduces computational time, particularly for deep learning models with high computational complexity. These findings underscore the potential of RSF as an effective spatial filtering approach for MI EEG classification, providing new insights and opportunities for the development of robust MI-BCI systems. The code for this research is available at https://github.com/PLC-TJU/RSF.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202539560446,
  title = {Enhancing Motor Imagery Classification with Residual Graph Convolutional Networks and Multi-Feature Fusion.},
  author = {Xu, F and Shi, W and Lv, C and Sun, Y and Guo, S and Feng, C and Zhang, Y and Jung, TP and Leng, J},
  journal = {International journal of neural systems},
  year = {2025},
  doi = {10.1142/S0129065724500692},
  pmid = {39560446},
  url = {https://pubmed.ncbi.nlm.nih.gov/39560446/},
  abstract = {Stroke, an abrupt cerebrovascular ailment resulting in brain tissue damage, has prompted the adoption of motor imagery (MI)-based brain-computer interface (BCI) systems in stroke rehabilitation. However, analyzing electroencephalogram (EEG) signals from stroke patients poses challenges. To address the issues of low accuracy and efficiency in EEG classification, particularly involving MI, the study proposes a residual graph convolutional network (M-ResGCN) framework based on the modified  S -transform (MST), and introduces the self-attention mechanism into residual graph convolutional network (ResGCN). This study uses MST to extract EEG time-frequency domain features, derives spatial EEG features by calculating the absolute Pearson correlation coefficient (aPcc) between channels, and devises a method to construct the adjacency matrix of the brain network using aPcc to measure the strength of the connection between channels. Experimental results involving 16 stroke patients and 16 healthy subjects demonstrate significant improvements in classification quality and robustness across tests and subjects. The highest classification accuracy reached 94.91% and a Kappa coefficient of 0.8918. The average accuracy and  F 1 scores from 10 times 10-fold cross-validation are 94.38% and 94.36%, respectively. By validating the feasibility and applicability of brain networks constructed using the aPcc in EEG signal analysis and feature encoding, it was established that the aPcc effectively reflects overall brain activity. The proposed method presents a novel approach to exploring channel relationships in MI-EEG and improving classification performance. It holds promise for real-time applications in MI-based BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wojciechowski202540014056,
  title = {Enhanced conditioning and disrupted extinction processes in men struggling with compulsive sexual behaviors.},
  author = {Wojciechowski, J and Draps, M and Kublik, E and Dubiejko, P and Wolak, T and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2025},
  doi = {10.1556/2006.2025.00012},
  pmid = {40014056},
  url = {https://pubmed.ncbi.nlm.nih.gov/40014056/},
  abstract = {Despite a previously reported connection between compulsive sexual behaviors (CSB), such as problematic pornography use, and heightened cue-reactivity, empirical evidence of the alteration of processes responsible for increased salience attribution to erotic cues remains sparse. Drawing on similarities with addiction models, this study explores the neuronal mechanisms of CSB through the use of appetitive conditioning and extinction with erotic and monetary rewards. Thirty-two heterosexual males struggling with CSB (age: 28.9 ± 7.1), and 31 healthy matched participants (age: 27.8 ± 5.6) underwent active appetitive conditioning and extinction tasks in fMRI. The effects of conditioning and extinction towards cues of erotic and monetary rewards were measured via self-assessment (valence and arousal rating towards cues), behavior (reaction times), and brain reactivity. In conditioning, subjective ratings increased, and reaction times were faster for both erotic and monetary cues among participants with CSB, along with altered activity in ventral striatum (vStr), dorsal anterior cingulate cortex (dACC), and anterior orbitofrontal cortex (aOFC). In extinction, self-assessment ratings remained elevated in the CSB group for both cues in a non-reward-specific fashion, accompanied by altered activity of dACC and vStr. These findings suggest enhanced incentive salience attribution to conditioned cues, highlighting a generalized motivational and value-related transfer from rewards to the cues in participants with CSB. Additionally, despite the absence of rewards, the persistence of arousal and valence towards cues underscored the maladaptive extinction process. These insights advance the understanding of CSB's neurobiological underpinnings and its relation to addiction frameworks.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Huang202541104530,
  title = {Elevated Release of Presynaptic Glutamate: The Potential Pathogenesis of Anti-NMDAR Encephalitis-Associated Seizures.},
  author = {Huang, H and Huang, Y and Li, S and Wu, Y and Yang, S and Wu, Y},
  journal = {CNS neuroscience & therapeutics},
  year = {2025},
  doi = {10.1111/cns.70585},
  pmid = {41104530},
  url = {https://pubmed.ncbi.nlm.nih.gov/41104530/},
  abstract = {The pathogenesis of anti-N-methyl-D-aspartate receptor encephalitis (anti-NMDAR encephalitis)-associated seizures remains elusive. Mice were injected with GluN1 359-378  peptide to construct a model of anti-NMDAR encephalitis. Next, the expression of NMDAR antibodies (NMDAR-Ab) was detected in serum samples. The electroencephalograms (EEGs) of mice were recorded. Afterward, neuronal action potentials (APs) and miniature excitatory postsynaptic currents (mEPSCs) were examined following exposure to serum derived from model mice. The expression levels of subunits of the NMDA receptor (GluN1, GluN2B) and glutamate vesicular transporter 1 (Vglut1) were quantified via Western blot analysis. Additionally, mice were injected with pentylenetetrazol (PTZ) to construct an in vivo model of status epilepticus (SE). Lastly, neurons exposed to mouse serum were incubated in a magnesium-free solution (Mg 2+ -free) for 1, 2, and 3 h, and APs were assessed. Following the administration of immunogenic peptide GluN1 359-378 , serum NMDAR-Ab was detected. EEG recording revealed that 68.75% (11/16) of mice receiving GluN1 359-378  exhibited epileptiform discharges. Moreover, the frequency of neuronal APs and mEPSCs following exposure to serum derived from mice receiving GluN1 359-378  was increased. The surface expression level of the GluN1 protein was significantly decreased, whereas that of the total Vglut1 protein was increased. Moreover, the seizure latency of mice receiving GluN1 359-378  was significantly shortened. Finally, after 1 to 2 h of incubation with Mg 2+ -free solution, the frequency of neuronal APs following exposure to serum derived from mice receiving GluN1 359-378  was increased. To the best of our knowledge, this is the first study to demonstrate that increased glutamate release may increase seizure susceptibility in patients with anti-NMDAR encephalitis.},
  note = {PubMed query source: Ying Wu}
}

@article{Roshanaei202539821106,
  title = {EEG-based functional and effective connectivity patterns during emotional episodes using graph theoretical analysis.},
  author = {Roshanaei, M and Norouzi, H and Onton, J and Makeig, S and Mohammadi, A},
  journal = {Scientific reports},
  year = {2025},
  doi = {10.1038/s41598-025-86040-9},
  pmid = {39821106},
  url = {https://pubmed.ncbi.nlm.nih.gov/39821106/},
  abstract = {Understanding the neural mechanisms underlying emotional processing is critical for advancing neuroscience and mental health interventions. This study examined these mechanisms by analyzing EEG connectivity patterns across different brain regions while participants evoked various emotions. After applying independent component analysis (ICA) to eliminate non-cortical activity, we assessed frequency-specific connectivity patterns using coherence, Granger causality, and graph theoretical measures to evaluate both functional and effective connectivity. Graph theoretical analysis revealed significant differences in connectivity between emotions across multiple frequency bands, particularly in the delta and beta bands. These results indicated modulations in key brain regions, such as the precentral, superior frontal, and temporal areas, suggesting that these regions play a crucial role in emotional processing. Coherence analysis demonstrated predominant alpha band activity across all emotions, with specific emotional states, such as fear, grief, and jealousy, exhibiting enhanced beta band activity. In terms of coherence strength, we observed that the gamma band was largely inactive, except for the emotion of sadness, which displayed significant activity in the right lobe, particularly in regions such as the supplementary motor area and the lingual gyrus. Additionally, Granger causality analysis highlighted that the beta and gamma bands were dominant across all emotional states, with minimal modulation observed in the theta band. Clustering coefficients from the graph analysis further revealed distinct patterns of connectivity in the delta and beta bands, with significant variations across different emotions, particularly in the temporal and frontal regions. These findings enhance our understanding of emotional processing and have practical applications in mental health, biomarker identification, and human-computer interaction.},
  note = {PubMed query source: Scott Makeig}
}

@article{Miyakoshi202541230010,
  title = {EEG power modulation in the sensorimotor regions is critical to motor tic suppression.},
  author = {Miyakoshi, M and Jurgiel, J and Dillon, A and Piacentini, J and Makeig, S and Loo, SK},
  journal = {Frontiers in psychiatry},
  year = {2025},
  doi = {10.3389/fpsyt.2025.1580636},
  pmid = {41230010},
  url = {https://pubmed.ncbi.nlm.nih.gov/41230010/},
  abstract = {The neural mechanisms underlying tic suppression in chronic tic disorder (CTD) have been investigated using various neuroimaging modalities. A limitation in studying CTD is that abrupt motor action is inherent to the nature of the disorder, but the movement makes any form of neural recording challenging. However, recent advances in hardware and software technologies have enabled EEG studies during motion, which open new avenues for studying CTD with EEG. We performed an event-related EEG power spectral analysis in children with chronic tic disorder (CTD) or typically developing children (TDC) as controls in a sample of 76 children (39 CTD) contributing to the final statistics. There were three block-separated conditions: no suppression (NoSupp), suppression with verbal instruction (Supp Vrb ), and suppression with reward (Supp Rwd ); the latter two conditions were collapsed into Supp Ave . EEG data were processed using independent component analysis, and the event-related potential was decomposed in the time-frequency domain. During tic or blink suppression, both CTD and TDC showed EEG power increase centered within the theta range in frontal, cingulate, and central regions. Meanwhile, the CTD group showed the opposite pattern in broadband EEG power modulation relative to controls, particularly in the centro-temporal sensorimotor regions. The regression analysis between this broadband power and tic suppression performance resulted in a significant positive correlation. Better tic suppression was associated with increased EEG power, a similar pattern observed among controls during blink suppression. EEG power in sensorimotor regions is a neural marker of tic suppression performance in children with CTD.},
  note = {PubMed query source: Scott Makeig}
}

@article{Westner202540800958,
  title = {Cycling on the Freeway: The perilous state of open-source neuroscience software.},
  author = {Westner, BU and McCloy, DR and Larson, E and Gramfort, A and Katz, DS and Smith, AM and Delorme, A and Litvak, V and Makeig, S and Oostenveld, R and Schoffelen, JM and Tierney, TM},
  journal = {Imaging neuroscience (Cambridge, Mass.)},
  year = {2025},
  doi = {10.1162/imag_a_00554},
  pmid = {40800958},
  url = {https://pubmed.ncbi.nlm.nih.gov/40800958/},
  abstract = {Most scientists need software to perform their research (Barker et al., 2020;Carver et al., 2022;Hettrick, 2014;Hettrick et al., 2014;Switters & Osimo, 2019), and neuroscientists are no exception. Whether we work with reaction times, electrophysiological signals, or magnetic resonance imaging data, we rely on software to acquire, analyze, and statistically evaluate the raw data we obtain-or to generate such data if we work with simulations. In recent years, there has been a shift toward relying on free, open-source scientific software (FOSSS) for neuroscience data analysis (Poldrack et al., 2019), in line with the broader open science movement in academia (McKiernan et al., 2016) and wider industry trends (Eghbal, 2016). Importantly, FOSSS is typically developed by working scientists (not professional software developers), which sets up a precarious situation given the nature of the typical academic workplace wherein academics, especially in their early careers, are on short- and fixed-term contracts. In this paper, we argue that the existing ecosystem of neuroscientific open-source software is brittle, and discuss why and how the neuroscience community needs to come together to ensure a healthy software ecosystem to the benefit of all.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{GewirtzMeydan202540040591,
  title = {Cross-Cultural Validation of the Binge Eating Disorder Screener-7 (BEDS-7) Across 42 Countries.},
  author = {Gewirtz-Meydan, A and Spivak-Lavi, Z and Kraus, SW and Nagy, L and Koós, M and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's Research Team and Chang, H and Park, K and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {The International journal of eating disorders},
  year = {2025},
  doi = {10.1002/eat.24365},
  pmid = {40040591},
  url = {https://pubmed.ncbi.nlm.nih.gov/40040591/},
  abstract = {This study aimed to evaluate the reliability and validity of the Binge Eating Disorder Screener-7 (BEDS-7) across 42 countries and 26 languages, assessing its reliability and validity as a screening tool for binge-eating disorder (BED) in diverse cultural contexts. Specifically, it sought to enhance early recognition of BED symptoms in primary care settings globally, contributing to a standardized framework for assessing BED. The International Sex Survey, a cross-sectional online study, was conducted in 42 countries and 26 languages. A diverse community sample of 82,243 participants, aged 18 years or older, completed the BEDS-7 and measures of sexuality, mental health, substance use, and sociodemographic characteristics. Confirmatory factor analyses and tests of measurement invariance were employed to evaluate the reliability and validity of the BEDS-7 across languages, countries, genders, and sexual orientations. The BEDS-7 demonstrated scalar factorial invariance across languages and countries, indicating consistent factor loadings and item intercepts. In contrast, the screener showed residual invariance across gender and sexual orientation groups, supporting its robustness across these demographics. Kruskal-Wallis tests revealed significant differences in BED symptoms across languages, countries, genders, and sexual orientations, with the highest BED scores observed among queer, pansexual, and gender-diverse individuals. The BEDS-7 also demonstrated adequate reliability (Cronbach's alpha > 0.80) and moderate criterion validity. The findings provide further evidence of the reliability and validity of the BEDS-7 as a potential screening tool for identifying probable cases of BED globally, facilitating early intervention in primary care settings.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Leng202540090883,
  title = {Coherence-Based Graph Convolution Network to Assess Brain Reorganization in Spinal Cord Injury Patients.},
  author = {Leng, J and Zhao, J and Wu, Y and Lv, C and Lun, Z and Li, Y and Zhang, C and Zhang, B and Zhang, Y and Xu, F and Yi, C and Jung, TP},
  journal = {International journal of neural systems},
  year = {2025},
  doi = {10.1142/S0129065725500212},
  pmid = {40090883},
  url = {https://pubmed.ncbi.nlm.nih.gov/40090883/},
  abstract = {Motor imagery (MI) engages a broad network of brain regions to imagine a specific action. Investigating the mechanism of brain network reorganization during MI after spinal cord injury (SCI) is crucial because it reflects overall brain activity. Using electroencephalogram (EEG) data from SCI patients, we conducted EEG-based coherence analysis to examine different brain network reorganizations across different frequency bands, from resting to MI. Furthermore, we introduced a consistency calculation-based residual graph convolution (C-ResGCN) classification algorithm. The results show that the [Formula: see text]- and [Formula: see text]-band connectivity weakens, and brain activity decreases during the MI task compared to the resting state. In contrast, the [Formula: see text]-band connectivity increases in motor regions while the default mode network activity declines during MI. Our C-ResGCN algorithm showed excellent performance, achieving a maximum classification accuracy of 96.25%, highlighting its reliability and stability. These findings suggest that brain reorganization in SCI patients reallocates relevant brain resources from the resting state to MI, and effective network reorganization correlates with improved MI performance. This study offers new insights into the mechanisms of MI and potential biomarkers for evaluating rehabilitation outcomes in patients with SCI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Growska202541488587,
  title = {COVID-19, sense of control, and the rise of addictive behaviors: a study in Poland.},
  author = {Górowska, MP and Obarska, K and Szymczak, K and Gola, M and Chodkiewicz, J},
  journal = {Postepy psychiatrii neurologii},
  year = {2025},
  doi = {10.5114/ppn.2025.156769},
  pmid = {41488587},
  url = {https://pubmed.ncbi.nlm.nih.gov/41488587/},
  abstract = {As some addictive behaviors increased during the COVID-19 pandemic, we have attempted to identify their risks and protective factors against them. In this research, we have investigated the relationship between the fear of COVID-19 and addictive behaviors and the role of general and COVID-19-specific sense of control, attitude to vaccination, and earlier recovery from COVID-19. A total of 511 individuals aged 18-79 participated in the online survey. Women comprised 71.29% of the sample, men 27.93%, and 0.79% ( n  = 3) declined to provide information on their gender. Participants completed questionnaires assessing substance-related and substance-dependent behaviors, general and COVID-19-specific locus of control, fear of COVID-19, and attitudes toward vaccination. Moderation and mediation analyses were conducted. Fear of COVID-19 was associated with increased internet, social media, and marijuana use. Lower sense of control (both general and COVID-19-specific) was associated with an increased severity of various addictions. A COVID-19-specific sense of control mediated the relationship between fear and addictive behaviors, particularly for women. This study highlights the impact of fear and sense of control on addictive behaviors during the COVID-19 pandemic. Promoting a sense of control may mitigate the risk of addiction in the face of pandemic-related stress. Public health efforts should address the potential for long-term consequences of addictive behaviors exacerbated by such global health crises, as similar challenges may arise with future outbreaks.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Uppal202541336081,
  title = {Brain-Body Coupling in Listening to Metronomic Sounds and Music.},
  author = {Uppal, A and Lee, MS and Fei, T and Balaji, A and Liu, Z and Jung, TP and Rangel, LM and De Sa, VR and Parhi, R and Paul, A and Xu, Y and Cauwenberghs, G},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2025},
  doi = {10.1109/EMBC58623.2025.11251651},
  pmid = {41336081},
  url = {https://pubmed.ncbi.nlm.nih.gov/41336081/},
  abstract = {Wearables continue to expand their ability to sample more signals from the brain and body while reducing form factors and limiting on-device computing to meet real-world comfort and power constraints. Where evolving multimodal sensing platforms can combine electrophysiological (ExG), optical, chemical, and mechanical sensors for holistic brain-body state estimation, understanding of cross-modal coupling mechanisms remains limited. Here, we collect and analyze bio-signals in a brain-body coupling experiment using simultaneous electroencephalogram (EEG), electrocardiogram (ECG), and respiratory measurements. Our experimental paradigm contrasted listening to self-selected music, preceded by tempo-matched isochronous cues. The results show a clear entrainment of cardiac rhythms with the underlying beat of auditory stimuli for both metronome cues and subject-selected music. Magnitude-Squared coherence analysis showed frequency coupling across recorded modalities, with ECG, EEG, and breath, exhibiting peak coherence near heard or underlying musical beat or its harmonics. We present minimally pre-processed data to motivate future methodological explorations of multiscale brain-body entrainment to rhythmic stimuli.Clinical relevance-These findings have implications for designing music therapy and biofeedback interventions that could adapt to ongoing brain-body rhythms. Understanding brain-body entrainment mechanisms and validating simplified measurement approaches could enable more accessible and effective rhythmic interventions in clinical settings, particularly for conditions benefiting from audio-based therapies or cardiac rehabilitation.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Yue202541064747,
  title = {Augmenting Electroencephalogram Transformer for Steady-State Visually Evoked Potential-Based Brain-Computer Interfaces.},
  author = {Yue, J and Xiao, X and Wang, K and Yi, W and Jung, TP and Xu, M and Ming, D},
  journal = {Cyborg and bionic systems (Washington, D.C.)},
  year = {2025},
  doi = {10.34133/cbsystems.0379},
  pmid = {41064747},
  url = {https://pubmed.ncbi.nlm.nih.gov/41064747/},
  abstract = {Objective:  Advancing high-speed steady-state visually evoked potential (SSVEP)-based brain-computer interface (BCI) systems requires effective electroencephalogram (EEG) decoding through deep learning. However, challenges persist due to data sparsity and the unclear neural basis of most augmentation techniques. Furthermore, effective processing of dynamic EEG signals and accommodating augmented data require a more sophisticated model tailored to the unique characteristics of EEG signals.  Approach:  This study introduces background EEG mixing (BGMix), a novel data augmentation technique grounded in neural principles that enhances training samples by replacing background noise between different classes. Building on this, we propose the augment EEG Transformer (AETF), a Transformer-based model designed to capture the temporal, spatial, and frequential features of EEG signals, leveraging the advantages of Transformer architectures.  Main results:  Experimental evaluations of 2 publicly available SSVEP datasets show the efficacy of the BGMix strategy and the AETF model. The BGMix approach notably improved the average classification accuracy of 4 distinct deep learning models, with increases ranging from 11.06% to 21.39% and 4.81% to 25.17% in the respective datasets. Furthermore, the AETF model outperformed state-of-the-art baseline models, excelling with short training data lengths and achieving the highest information transfer rates (ITRs) of 205.82 ± 15.81 bits/min and 240.03 ± 14.91 bits/min on the 2 datasets.  Significance:  This study introduces a novel EEG augmentation method and a new approach to designing deep learning models informed by the neural processes of EEG. These innovations significantly improve the performance and practicality of high-speed SSVEP-based BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Shirazi202541256398,
  title = {Age-related Reorganization of Corticomuscular Connectivity During Locomotor Perturbations.},
  author = {Shirazi, SY and Tasin, SM and Huang, HJ},
  journal = {bioRxiv : the preprint server for biology},
  year = {2025},
  doi = {10.1101/2025.09.28.679054},
  pmid = {41256398},
  url = {https://pubmed.ncbi.nlm.nih.gov/41256398/},
  abstract = {Locomotor perturbations elicit cortical and muscular responses that help minimize motor errors through neural processes involving multiple brain regions. The anterior cingulate cortex monitors motor errors, the supplementary motor areas integrate sensory and executive control, and the posterior parietal cortices process sensorimotor predictions, while muscles show increased activation and co-contraction patterns. With aging, these neural control strategies shift; older adults demonstrate less flexible cortical and muscular responses, using compensatory overactivation and simpler muscle synergies to maintain performance comparable to young adults. We investigated corticomuscular connectivity patterns during perturbed recumbent stepping in seventeen young adults (age 25±4.9 years) and eleven older adults (age 68±3.6 years) using high-density EEG (128 electrodes) and EMG from six bilateral muscles. Brief mechanical perturbations (200ms of increased resistance) were applied at left or right leg extension-onset or mid-extension during continuous stepping at 60 steps per minute. We applied independent component analysis, source localization, and direct directed transfer function to quantify bidirectional information flow between cortical clusters and muscles in theta (3-8 Hz), alpha (8-13 Hz), and beta (13-35 Hz) bands. Young adults demonstrated concentrated electrocortical sources in anterior cingulate cortex, bilateral supplementary motor areas, and bilateral posterior parietal cortices, with strong theta-band synchronization following perturbations. In contrast, older adults showed fewer differentiated cortical sources, particularly lacking distinct anterior cingulate activity, and exhibited only minimal synchronization changes. Baseline corticomuscular connectivity was significantly stronger in older adults compared to young adults (p=0.012), suggesting fundamental differences in resting motor control states. During perturbations, young adults employed flexible, task-specific connectivity modulation involving error-processing networks, with the anterior cingulate showing selective bidirectional connectivity changes with specific muscles. Older adults relied on more diffuse (i.e., not focused to specific brain area) connectivity patterns dominated by motor and posterior parietal cortices, with strong connections to multiple upper and lower limb muscles simultaneously. These findings reveal an age-related strategic reorganization from dynamic, error-driven neural control to a more constrained, stability-focused approach that may reflect compensation for sensorimotor changes. The distinct connectivity signatures establish perturbed recumbent stepping as a valuable tool for assessing corticomuscular communication and provide normative benchmarks for developing targeted rehabilitation interventions to restore efficient motor control in aging and neurological populations.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Wang202540720262,
  title = {Adaptive Neurofeedback Training Using a Virtual Reality Game Enhances Motor Imagery Performance in Brain-Computer Interfaces.},
  author = {Wang, K and Liu, Y and Tian, F and Yi, W and Zhang, Y and Jung, TP and Xu, M and Ming, D},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2025},
  doi = {10.1109/TNSRE.2025.3592988},
  pmid = {40720262},
  url = {https://pubmed.ncbi.nlm.nih.gov/40720262/},
  abstract = {Neurofeedback training (NFT) has been widely used in motor rehabilitation. However, NFT combined with motor imagery-based brain-computer interface (MI-BCI) faces challenges such as mental fatigue and non-personalized training strategies. Therefore, we proposed an adaptive NFT based on a VR game that simulates real-life motor tasks to improve training efficiency. We conducted a detailed comparative analysis of the efficiency of the VR-based NFT and traditional Graz-based NFT. Forty-eight healthy subjects were randomly assigned to five groups and underwent various NFT protocols. Among them, the subjects in the four experimental groups were required to perform the NFT three times over five days, including virtual or real scenarios, as well as unilateral or bilateral hands training. We evaluated training effects by analyzing EEG features and classification performance, while online recognition duration served as the primary measure for assessing the adaptive NFT strategy. EEG analysis showed that VR-based NFT significantly enhanced the Event-related desynchronization (ERD) activations in the sensorimotor cortices over five days. The VR-based NFT group achieved a classification accuracy of 81.85%, representing a 10.14% improvement from baseline, which exceeded the 6.43% increase observed in the Graz-based NFT group. Furthermore, implementing the adaptive NFT strategy reduced the mean task duration by over 30% compared to the fixed-time training protocol. The results demonstrated that the adaptive MI-BCI-based NFT in a VR game achieves superior training outcomes while reducing training duration. These findings suggest the promising potential for applying MI-BCI NFT with VR games in motor rehabilitation following a stroke.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Ji202540584269,
  title = {A user-friendly BCI encoding by high frequency single-frequency-SDMA SSaVEF using MEG.},
  author = {Ji, D and Yu, H and Xiao, X and Huang, Y and Zhou, X and Xu, M and Jung, TP and Ming, D},
  journal = {Cognitive neurodynamics},
  year = {2025},
  doi = {10.1007/s11571-025-10279-1},
  pmid = {40584269},
  url = {https://pubmed.ncbi.nlm.nih.gov/40584269/},
  abstract = {Magnetoencephalography (MEG) delivers high spatial resolution and superior detection performance for high-frequency signals compared to Electroencephalography (EEG). Therefore, researchers can leverage MEG for high-frequency steady-state asymmetric visual evoked potential (SSaVEP). Current SSaVEP encoding typically uses low-frequency stimulation with relatively large stimulus areas, hindering the applicability of this encoding method in user-friendly brain-computer interface (BCI) systems. This study introduces an ultra critical flicker frequency (ultra-CFF) single-frequency-SDMA steady-state asymmetric visual evoked field (SSaVEF) encoding powered by MEG and presents an eight-command SSaVEF-BCI system. The BCI system features a 60 Hz SSVEF visual stimulus landmark and eight visual targets spaced 45° apart. Ten participants took part in the offline experiments, during which data from 41 channels in the occipital region were collected. This study analyzed the spatiotemporal characteristics, frequency-space characteristics, signal-to-noise ratio, and other features of the SSaVEF signals. We also evaluated the system's performance using the multi-DCPM algorithm. Using the multi-DCPM algorithm, the system achieved an impressive average classification accuracy of 81.65% with 4-s length data. With a data length of 1 s, the system achieved an average Information Transfer Rate (ITR) of 32.05 bits/min, with the highest individual ITR reached an astonishing 64.45 bits/min. This study represents the exploration of a high-frequency spatial encoding SSVEF-BCI system based on MEG. The results demonstrate MEG's feasibility and potential of applying MEG in such BCI systems, providing both theoretical and practical value for the further development and implementation of future BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Jin202540787683,
  title = {A comparative evaluation of EEG Power spectrum characteristics between two methods for alleviating preoperative anxiety in breast cancer patients.},
  author = {Jin, X and Wang, Y and Jiang, H and Wu, Y and Liu, Y},
  journal = {Frontiers in psychiatry},
  year = {2025},
  doi = {10.3389/fpsyt.2025.1611129},
  pmid = {40787683},
  url = {https://pubmed.ncbi.nlm.nih.gov/40787683/},
  abstract = {Women with breast cancer are prone to moderate to severe preoperative anxiety. Effective measures for preventing and managing preoperative anxiety include drug therapy and non-drug intervention. The main evaluation method is scale assessment, which has certain limitations and may involve human concealment or evaluation errors. In this study, resting-state electroencephalography (EEG) was used to explore changes in power spectrum during the alleviation of preoperative anxiety in breast cancer patients, which is of great significance for objectively identifying and evaluating preoperative anxiety in patients. 40 breast cancer patients were randomly divided into two groups (20 patients per group), receiving either psychological intervention (PI) or intravenous midazolam (MID) before surgery. Visual Analog Scale for Anxiety (VAS-A) and Observer's assessment alert/Sedation (OAA/S) scores, clinical monitoring indexes and EEG data were measured before and after intervention. VAS-A scores significantly decreased in both groups (p < 0.05), the power in the theta band of the frontal parietal regions decreased (p < 0.05) and was positively correlated with VAS-A scores (p < 0.001). Network analysis revealed that the three highest centrality measures in the PI group were located in the alpha band frontal parietal region, frontal central region, and gamma band parietal region, while the OAA/S scores showed the highest centrality for all three measures in the MID group. Both PI and intravenous MID can effectively alleviate preoperative anxiety in breast cancer patients, but their neuroelectrophysiological mechanisms were not entirely the same. Regarding the relationship between brain region power and monitoring indexes, the power of three specific regions in certain frequency bands was the primary factor in the PI group, while the level of sedation was the determining factor in the MID group.},
  note = {PubMed query source: Ying Wu}
}

@article{Jin202539504274,
  title = {A Growing Bubble Speller Paradigm for Brain-Computer Interface Based on Event-Related Potentials.},
  author = {Jin, J and Zhao, X and Daly, I and Li, S and Wang, X and Cichocki, A and Jung, TP},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2025},
  doi = {10.1109/TBME.2024.3492506},
  pmid = {39504274},
  url = {https://pubmed.ncbi.nlm.nih.gov/39504274/},
  abstract = {Event-related potentials (ERPs) reflect electropotential changes within specific cortical regions in response to specific events or stimuli during cognitive processes. The P300 speller is an important application of ERP-based brain-computer interfaces (BCIs), offering potential assistance to individuals with severe motor disabilities by decoding their electroencephalography (EEG) to communicate. This study introduced a novel speller paradigm using a dynamically growing bubble (GB) visualization as the stimulus, departing from the conventional flash stimulus (TF). Additionally, we proposed a "Lock a Target by Two Flashes" (LT2F) method to offer more versatile stimulus flash rules, complementing the row and column (RC) and single character (SC) modes. We applied the "Sub and Global" multi-window mode to EEGNet (mwEEGNet) to enhance classification and explored the performance of eight other representative algorithms. Twenty healthy volunteers participated in the experiments. Our analysis revealed that our proposed pattern elicited more pronounced negative peaks in the parietal and occipital brain regions between 200 ms and 230 ms post-stimulus onset compared with the TF pattern. Compared to the TF pattern, the GB pattern yielded a 2.00% increase in online character accuracy (ACC) and a 5.39 bits/min improvement in information transfer rate (ITR) when using mwEEGNet. Furthermore, results demonstrated that mwEEGNet outperformed other methods in classification performance. These results underscore the significance of our work in advancing ERP-based BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Onton202441424496,
  title = {Validation of spectral sleep scoring with polysomnography using forehead EEG device.},
  author = {Onton, JA and Simon, KC and Morehouse, AB and Shuster, AE and Zhang, J and Peña, AA and Mednick, SC},
  journal = {Frontiers in sleep},
  year = {2024},
  doi = {10.3389/frsle.2024.1349537},
  pmid = {41424496},
  url = {https://pubmed.ncbi.nlm.nih.gov/41424496/},
  abstract = {Visual scoring of sleep electroencephalography (EEG) has long been considered the gold standard for sleep staging. However, it has several drawbacks, including high cost, time-intensiveness, vulnerability to human variability, discomfort to patients, lack of visualization to validate the hypnogram, and no acknowledgment of differences between delta and slow oscillation deep sleep. This report highlights a spectral scoring approach that addresses all these shortcomings of visual scoring. Past algorithms have used spectral information to help classify traditional visual stages. The current method used the clearly visible spectral patterns to develop new spectral stages, which are similar to but not the same as visual stages. Importantly, spectral scoring delivers both a hypnogram and a whole-night spectrogram, which can be visually inspected to ensure accurate scoring. This study compared traditional visual scoring of 32-channel polysomnography with forehead-only spectral scoring from an EEG patch worn concurrently. The PSG was visually scored by trained technicians and the forehead patch was scored spectrally. Because non-rapid eye movement (NREM) stage divisions in spectral scoring are not based on visual NREM stages, the agreements are not expected to be as high as other automated sleep scoring algorithms. Rather, they are a guide to understanding spectral stages as they relate to the more widely understood visual stages and to emphasize reasons for the differences. The results showed that visual REM was highly recognized as spectral REM (89%). Visual wake was only scored as spectral Wake 47% of the time, partly because of excessive visual scoring of wake during Light and REM sleep. The majority of spectral Light (predominance of spindle power) was scored as N2 (74%), while less N2 was scored as Light (65%), mostly because of incorrect visual staging of Lo Deep sleep due to high-pass filtering. N3 was scored as both Hi Deep (13 Hz power, 42%) and Lo Deep (0-1 Hz power, 39%), constituting a total of 81% of N3. The results show that spectral scoring better identifies clinically relevant physiology at a substantially lower cost and in a more reproducible fashion than visual scoring, supporting further work exploring its use in clinical and research settings.},
  note = {PubMed query source: Julie Onton}
}

@article{Leng202438857138,
  title = {Time-Frequency-Space EEG Decoding Model Based on Dense Graph Convolutional Network for Stroke.},
  author = {Leng, J and Li, H and Shi, W and Gao, L and Lv, C and Wang, C and Xu, F and Zhang, Y and Jung, TP},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2024},
  doi = {10.1109/JBHI.2024.3411646},
  pmid = {38857138},
  url = {https://pubmed.ncbi.nlm.nih.gov/38857138/},
  abstract = {Stroke, a sudden cerebrovascular ailment resulting from brain tissue damage, has prompted the use of motor imagery (MI)-based Brain-Computer Interface (BCI) systems in stroke rehabilitation. However, analyzing EEG signals from stroke patients is challenging because of their low signal-to-noise ratio and high variability. Therefore, we propose a novel approach that combines the modified S-transform (MST) and a dense graph convolutional network (DenseGCN) algorithm to enhance the MI-BCI performance across time, frequency, and space domains. MST is a time-frequency analysis method that efficiently concentrates energy in EEG signals, while DenseGCN is a deep learning model that uses EEG feature maps from each layer as inputs for subsequent layers, facilitating feature reuse and hyper-parameters optimization. Our approach outperforms conventional networks, achieving a peak classification accuracy of 90.22% and an average information transfer rate (ITR) of 68.52 bits per minute. Moreover, we conduct an in-depth analysis of the event-related desynchronization/event-related synchronization (ERD/ERS) phenomenon in the deep-level EEG features of stroke patients. Our experimental results confirm the feasibility and efficacy of the proposed approach for MI-BCI rehabilitation systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lin202438706570,
  title = {The short version of the Sexual Distress Scale (SDS-3): Measurement invariance across countries, gender identities, and sexual orientations.},
  author = {Lin, CY and Tsai, MC and Koós, M and Nagy, L and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, M and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Milea, I and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's research team and Ponce, FP and Quintana, GR and Garzola, GCQ and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {International journal of clinical and health psychology : IJCHP},
  year = {2024},
  doi = {10.1016/j.ijchp.2024.100461},
  pmid = {38706570},
  url = {https://pubmed.ncbi.nlm.nih.gov/38706570/},
  abstract = {The three-item Sexual Distress Scale (SDS-3) has been frequently used to assess distress related to sexuality in public health surveys and research on sexual wellbeing. However, its psychometric properties and measurement invariance across cultural, gender and sexual subgroups have not yet been examined. This multinational study aimed to validate the SDS-3 and test its psychometric properties, including measurement invariance across language, country, gender identity, and sexual orientation groups. We used global survey data from 82,243 individuals (Mean  age =32.39 years; 40.3 % men, 57.0 % women, 2.8 % non-binary, and 0.6 % other genders) participating in the International Sexual Survey (ISS; https://internationalsexsurvey.org/) across 42 countries and 26 languages. Participants completed the SDS-3, as well as questions regarding sociodemographic characteristics, including gender identity and sexual orientation. Confirmatory factor analysis (CFA) supported a unidimensional factor structure for the SDS-3, and multi-group CFA (MGCFA) suggested that this factor structure was invariant across countries, languages, gender identities, and sexual orientations. Cronbach's  α  for the unidimensional score was 0.83 (range between 0.76 and 0.89), and McDonald's  ω  was 0.84 (range between 0.76 and 0.90). Participants who did not experience sexual problems had significantly lower SDS-3 total scores ( M  = 2.99;  SD =2.54) compared to those who reported sexual problems ( M  = 5.60;  SD =3.00), with a large effect size (Cohen's  d  = 1.01 [95 % CI=-1.03, -0.98];  p  < 0.001). The SDS-3 has a unidimensional factor structure and appears to be valid and reliable for measuring sexual distress among individuals from different countries, gender identities, and sexual orientations.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Luo202439084073,
  title = {The research hotspots and theme trends of artificial intelligence in nurse education: A bibliometric analysis from 1994 to 2023.},
  author = {Luo, C and Mao, B and Wu, Y and He, Y},
  journal = {Nurse education today},
  year = {2024},
  doi = {10.1016/j.nedt.2024.106321},
  pmid = {39084073},
  url = {https://pubmed.ncbi.nlm.nih.gov/39084073/},
  abstract = {To explore research hotspots and theme trends in artificial intelligence in nurse education using bibliometric analysis. Bibliometric analysis. Literature from the Web of Science Core Collection from the time of construction to October 31, 2023 was searched. Analyses of countries, authors, institutions, journals, and keywords were conducted using Bibliometrix (based on R language), CiteSpace, the online analysis platform (bibliometric), Vosviewer, and Pajek. A total of 135 articles with a straight upward trend over the last three years were retrieved. By fitting the curve R 2  = 0.6022 (R 2  > 0.4), we predicted that the number of annual articles is projected to grow in the coming years. The United States (n = 38), the National University of Singapore (n = 16), Professor Jun Ota (n = 8), and Nurse Education Today (n = 14) are the countries, institutions, authors, and journals that contributed to the most publications, respectively. Collaborative network analysis revealed that 32 institutional and 64 author collaborative teams were established. We identified ten high-frequency keywords and nine clusters. We categorized the research hotspots of artificial intelligence in nurse education into three areas: (1) Artificial intelligence-enhanced simulation robots, (2) machine learning and data mining, and (3) large language models based on natural language processing and deep learning. By analyzing the temporal and spatial evolution of keywords and burst detection, we found that future research trends may include (1) expanding and deepening the application of AI technology, (2) assessment of behavioral intent and educational outcomes, and (3) moral and ethical considerations. Future research should be conducted on technology applications, behavioral intent, ethical policy, international cooperation, interdisciplinary cooperation, and sustainability to promote the continued development and innovation of AI in nurse education.},
  note = {PubMed query source: Ying Wu}
}

@article{Poldrack202439308505,
  title = {The past, present, and future of the brain imaging data structure (BIDS).},
  author = {Poldrack, RA and Markiewicz, CJ and Appelhoff, S and Ashar, YK and Auer, T and Baillet, S and Bansal, S and Beltrachini, L and Benar, CG and Bertazzoli, G and Bhogawar, S and Blair, RW and Bortoletto, M and Boudreau, M and Brooks, TL and Calhoun, VD and Castelli, FM and Clement, P and Cohen, AL and Cohen-Adad, J and D'Ambrosio, S and de Hollander, G and de la Iglesia-Vayá, M and de la Vega, A and Delorme, A and Devinsky, O and Draschkow, D and Duff, EP and DuPre, E and Earl, E and Esteban, O and Feingold, FW and Flandin, G and Galassi, A and Gallitto, G and Ganz, M and Gau, R and Gholam, J and Ghosh, SS and Giacomel, A and Gillman, AG and Gleeson, P and Gramfort, A and Guay, S and Guidali, G and Halchenko, YO and Handwerker, DA and Hardcastle, N and Herholz, P and Hermes, D and Honey, CJ and Innis, RB and Ioanas, HI and Jahn, A and Karakuzu, A and Keator, DB and Kiar, G and Kincses, B and Laird, AR and Lau, JC and Lazari, A and Legarreta, JH and Li, A and Li, X and Love, BC and Lu, H and Marcantoni, E and Maumet, C and Mazzamuto, G and Meisler, SL and Mikkelsen, M and Mutsaerts, H and Nichols, TE and Nikolaidis, A and Nilsonne, G and Niso, G and Norgaard, M and Okell, TW and Oostenveld, R and Ort, E and Park, PJ and Pawlik, M and Pernet, CR and Pestilli, F and Petr, J and Phillips, C and Poline, JB and Pollonini, L and Raamana, PR and Ritter, P and Rizzo, G and Robbins, KA and Rockhill, AP and Rogers, C and Rokem, A and Rorden, C and Routier, A and Saborit-Torres, JM and Salo, T and Schirner, M and Smith, RE and Spisak, T and Sprenger, J and Swann, NC and Szinte, M and Takerkart, S and Thirion, B and Thomas, AG and Torabian, S and Varoquaux, G and Voytek, B and Welzel, J and Wilson, M and Yarkoni, T and Gorgolewski, KJ},
  journal = {Imaging neuroscience (Cambridge, Mass.)},
  year = {2024},
  doi = {10.1162/imag_a_00103},
  pmid = {39308505},
  url = {https://pubmed.ncbi.nlm.nih.gov/39308505/},
  abstract = {The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Usman202439169432,
  title = {The effect of Zentangle on cognitive focus, emotional well-being, and stress levels: A neural perspective.},
  author = {Usman, M and Jung, TP and Hsin, DY and Lin, CL},
  journal = {Brain and behavior},
  year = {2024},
  doi = {10.1002/brb3.3628},
  pmid = {39169432},
  url = {https://pubmed.ncbi.nlm.nih.gov/39169432/},
  abstract = {This study aimed to assess how a Zentangle intervention influences cognitive focus, emotional well-being, stress levels, and neural activity patterns across brain regions and frequency bands. A cohort of 30 healthy adults, all without prior Zentangle experience, participated in this study. Electroencephalography (EEG) was used to measure their brain activity, and self-reported data were collected through questionnaires to assess subjects' concentration levels, emotional calm, and stress and anxiety. Participants reported enhanced cognitive focus and emotional well-being, evidenced by increased self-reported concentration and emotional calmness, and reduced stress and anxiety levels during the intervention. EEG analyses revealed notable changes in neural activity patterns, including decreased delta power and increased theta, alpha, beta, and gamma bands. Functional connectivity analysis also highlighted alterations in the brain's functional connectivity, suggesting potential effects on neural communication and information processing. This study provides compelling evidence of Zentangle's impact on EEG data, aligning it with equanimity and tranquility consistent with previous mindfulness research. These findings underscore Zentangle as an effective mindfulness practice, potentially enhancing cognitive focus and emotional well-being, and emerging as a valuable intervention for improving mental health and overall well-being.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Poldrack202437744469,
  title = {The Past, Present, and Future of the Brain Imaging Data Structure (BIDS).},
  author = {Poldrack, RA and Markiewicz, CJ and Appelhoff, S and Ashar, YK and Auer, T and Baillet, S and Bansal, S and Beltrachini, L and Benar, CG and Bertazzoli, G and Bhogawar, S and Blair, RW and Bortoletto, M and Boudreau, M and Brooks, TL and Calhoun, VD and Castelli, FM and Clement, P and Cohen, AL and Cohen-Adad, J and D'Ambrosio, S and de Hollander, G and de la Iglesia-Vayá, M and de la Vega, A and Delorme, A and Devinsky, O and Draschkow, D and Duff, EP and DuPre, E and Earl, E and Esteban, O and Feingold, FW and Flandin, G and Galassi, A and Gallitto, G and Ganz, M and Gau, R and Gholam, J and Ghosh, SS and Giacomel, A and Gillman, AG and Gleeson, P and Gramfort, A and Guay, S and Guidali, G and Halchenko, YO and Handwerker, DA and Hardcastle, N and Herholz, P and Hermes, D and Honey, CJ and Innis, RB and Ioanas, HI and Jahn, A and Karakuzu, A and Keator, DB and Kiar, G and Kincses, B and Laird, AR and Lau, JC and Lazari, A and Legarreta, JH and Li, A and Li, X and Love, BC and Lu, H and Marcantoni, E and Maumet, C and Mazzamuto, G and Meisler, SL and Mikkelsen, M and Mutsaerts, H and Nichols, TE and Nikolaidis, A and Nilsonne, G and Niso, G and Norgaard, M and Okell, TW and Oostenveld, R and Ort, E and Park, PJ and Pawlik, M and Pernet, CR and Pestilli, F and Petr, J and Phillips, C and Poline, JB and Pollonini, L and Raamana, PR and Ritter, P and Rizzo, G and Robbins, KA and Rockhill, AP and Rogers, C and Rokem, A and Rorden, C and Routier, A and Saborit-Torres, JM and Salo, T and Schirner, M and Smith, RE and Spisak, T and Sprenger, J and Swann, NC and Szinte, M and Takerkart, S and Thirion, B and Thomas, AG and Torabian, S and Varoquaux, G and Voytek, B and Welzel, J and Wilson, M and Yarkoni, T and Gorgolewski, KJ},
  journal = {ArXiv},
  year = {2024},
  pmid = {37744469},
  url = {https://pubmed.ncbi.nlm.nih.gov/37744469/},
  abstract = {The Brain Imaging Data Structure (BIDS) is a community-driven standard for the organization of data and metadata from a growing range of neuroscience modalities. This paper is meant as a history of how the standard has developed and grown over time. We outline the principles behind the project, the mechanisms by which it has been extended, and some of the challenges being addressed as it evolves. We also discuss the lessons learned through the project, with the aim of enabling researchers in other domains to learn from the success of BIDS.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Ross202439651225,
  title = {Sensory Entrained TMS (seTMS) enhances motor cortex excitability.},
  author = {Ross, JM and Forman, L and Gogulski, J and Hassan, U and Cline, CC and Parmigiani, S and Truong, J and Hartford, JW and Chen, NF and Fujioka, T and Makeig, S and Pascual-Leone, A and Keller, CJ},
  journal = {bioRxiv : the preprint server for biology},
  year = {2024},
  doi = {10.1101/2024.11.26.625537},
  pmid = {39651225},
  url = {https://pubmed.ncbi.nlm.nih.gov/39651225/},
  abstract = {Transcranial magnetic stimulation (TMS) applied to the motor cortex has revolutionized the study of motor physiology in humans. Despite this, TMS-evoked electrophysiological responses show significant variability, due in part to inconsistencies between TMS pulse timing and ongoing brain oscillations. Variable responses to TMS limit mechanistic insights and clinical efficacy, necessitating the development of methods to precisely coordinate the timing of TMS pulses to the phase of relevant oscillatory activity. We introduce Sensory Entrained TMS (seTMS), a novel approach that uses musical rhythms to synchronize brain oscillations and time TMS pulses to enhance cortical excitability. Focusing on the sensorimotor alpha rhythm, a neural oscillation associated with motor cortical inhibition, we examine whether rhythm-evoked sensorimotor alpha phase alignment affects primary motor cortical (M1) excitability in healthy young adults ( n =33). We first confirmed using electroencephalography (EEG) that passive listening to musical rhythms desynchronizes inhibitory sensorimotor brain rhythms ( mu oscillations ) around 200 ms before auditory rhythmic events (27 participants). We then targeted this optimal time window by delivering single TMS pulses over M1 200 ms before rhythmic auditory events while recording motor-evoked potentials (MEPs; 19 participants), which resulted in significantly larger MEPs compared to standard single pulse TMS and an auditory control condition. Neither EEG measures during passive listening nor seTMS-induced MEP enhancement showed dependence on musical experience or training. These findings demonstrate that seTMS effectively enhances corticomotor excitability and establishes a practical, cost-effective method for optimizing non-invasive brain stimulation outcomes.},
  note = {PubMed query source: Scott Makeig}
}

@article{Miao202438981035,
  title = {Performance of GPT-4 on Chinese Nursing Examination: Potentials for AI-Assisted Nursing Education Using Large Language Models.},
  author = {Miao, Y and Luo, Y and Zhao, Y and Li, J and Liu, M and Wang, H and Chen, Y and Wu, Y},
  journal = {Nurse educator},
  year = {2024},
  doi = {10.1097/NNE.0000000000001679},
  pmid = {38981035},
  url = {https://pubmed.ncbi.nlm.nih.gov/38981035/},
  abstract = {The performance of GPT-4 in nursing examinations within the Chinese context has not yet been thoroughly evaluated. To assess the performance of GPT-4 on multiple-choice and open-ended questions derived from nursing examinations in the Chinese context. The data sets of the Chinese National Nursing Licensure Examination spanning 2021 to 2023 were used to evaluate the accuracy of GPT-4 in multiple-choice questions. The performance of GPT-4 on open-ended questions was examined using 18 case-based questions. For multiple-choice questions, GPT-4 achieved an accuracy of 71.0% (511/720). For open-ended questions, the responses were evaluated for cosine similarity, logical consistency, and information quality, all of which were found to be at a moderate level. GPT-4 performed well at addressing queries on basic knowledge. However, it has notable limitations in answering open-ended questions. Nursing educators should weigh the benefits and challenges of GPT-4 for integration into nursing education.},
  note = {PubMed query source: Ying Wu}
}

@article{Mushtaq202439174725,
  title = {One hundred years of EEG for brain and behaviour research.},
  author = {Mushtaq, F and Welke, D and Gallagher, A and Pavlov, YG and Kouara, L and Bosch-Bayard, J and van den Bosch, JJF and Arvaneh, M and Bland, AR and Chaumon, M and Borck, C and He, X and Luck, SJ and Machizawa, MG and Pernet, C and Puce, A and Segalowitz, SJ and Rogers, C and Awais, M and Babiloni, C and Bailey, NW and Baillet, S and Bendall, RCA and Brady, D and Bringas-Vega, ML and Busch, NA and Calzada-Reyes, A and Chatard, A and Clayson, PE and Cohen, MX and Cole, J and Constant, M and Corneyllie, A and Coyle, D and Cruse, D and Delis, I and Delorme, A and Fair, D and Falk, TH and Gamer, M and Ganis, G and Gloy, K and Gregory, S and Hassall, CD and Hiley, KE and Ivry, RB and Jerbi, K and Jenkins, M and Kaiser, J and Keil, A and Knight, RT and Kochen, S and Kotchoubey, B and Krigolson, OE and Langer, N and Liesefeld, HR and Lippé, S and London, RE and MacNamara, A and Makeig, S and Marinovic, W and Martínez-Montes, E and Marzuki, AA and Mathew, RK and Michel, C and Millán, JDR and Mon-Williams, M and Morales-Chacón, L and Naar, R and Nilsonne, G and Niso, G and Nyhus, E and Oostenveld, R and Paul, K and Paulus, W and Pfabigan, DM and Pourtois, G and Rampp, S and Rausch, M and Robbins, K and Rossini, PM and Ruzzoli, M and Schmidt, B and Senderecka, M and Srinivasan, N and Stegmann, Y and Thompson, PM and Valdes-Sosa, M and van der Molen, MJW and Veniero, D and Verona, E and Voytek, B and Yao, D and Evans, AC and Valdes-Sosa, P},
  journal = {Nature human behaviour},
  year = {2024},
  doi = {10.1038/s41562-024-01941-5},
  pmid = {39174725},
  url = {https://pubmed.ncbi.nlm.nih.gov/39174725/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Shirazi202438717333,
  title = {Older adults use fewer muscles to overcome perturbations during a seated locomotor task.},
  author = {Shirazi, SY and Huang, HJ},
  journal = {Journal of neurophysiology},
  year = {2024},
  doi = {10.1152/jn.00263.2023},
  pmid = {38717333},
  url = {https://pubmed.ncbi.nlm.nih.gov/38717333/},
  abstract = {Locomotor perturbations provide insights into humans' response to motor errors. We investigated the differences in motor adaptation and muscle cocontraction between young and older adults during perturbed-arm and -leg recumbent stepping. We hypothesized that besides prolonged adaptation due to use-dependent learning, older adults would exhibit greater muscle cocontraction than young adults in response to the perturbations. Perturbations were brief increases in resistance applied during each stride at the extension onset or midextension of the left or right leg. Seventeen young adults and eleven older adults completed four 10-min perturbed stepping tasks. Subjects were instructed to follow a visual pacing cue, step smoothly, and use all their limbs to drive the stepper. Results showed that young and older adults did not decrease their errors with more perturbation experience, and errors did not wash out after perturbations were removed. Interestingly, older adults consistently had smaller motor errors than young adults in response to the perturbations. Older adults used fewer muscles to drive the stepper and had greater cocontraction than young adults. The results suggest that, despite similar motor error responses, young and older adults use distinctive muscle recruitment patterns to perform the motor task. Age-related motor strategies help track motor changes across the human life span and are a baseline for rehabilitation and performance assessment. NEW & NOTEWORTHY  Older adults often demonstrate greater cocontraction and motor errors than young adults in response to motor perturbations. We demonstrated that older adults reduced their motor errors more than young adults with brief perturbations during recumbent stepping while maintaining greater muscle cocontraction. In doing so, older adults largely used one muscle pair to drive the stepper, tibialis anterior and soleus, whereas young adults used all muscles. These two muscles are crucial for maintaining upright balance.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Ng202439642375,
  title = {Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers.},
  author = {Ng, HH and Wu, CW and Hsu, HC and Huang, CM and Hsu, AL and Chao, YP and Jung, TP and Chuang, CH},
  journal = {JMIR formative research},
  year = {2024},
  doi = {10.2196/55478},
  pmid = {39642375},
  url = {https://pubmed.ncbi.nlm.nih.gov/39642375/},
  abstract = {Recent advancements in virtual reality (VR) and biofeedback (BF) technologies have opened new avenues for breathing training. Breathing training has been suggested as an effective means for mental disorders, but it is difficult to master the technique at the beginning. VR-BF technologies address the problem of breathing, and visualizing breathing may facilitate the learning of breathing training. This study explores the integration of VR and BF to enhance user engagement in self-help breathing training, which is a multifaceted approach encompassing mindful breathing, guided breathing, and breath counting techniques. We identified 3 common breathing training techniques in previous studies, namely mindful breathing, guided breathing, and breath counting. Despite the availability of diverse breathing training methods, their varying effectiveness and underlying neurological mechanisms remain insufficiently understood. We investigated using electroencephalography (EEG) indices across multiple breathing training modalities to address this gap. Our automated VR-based breathing training environment incorporated real-time EEG, heart rate, and breath signal BF. We examined 4 distinct breathing training conditions (resting, mindful breathing, guided breathing, and breath counting) in a cross-sectional experiment involving 51 healthy young adults, who were recruited through online forum advertisements and billboard posters. In an experimental session, participants practiced resting state and each breathing training technique for 6 minutes. We then compared the neurological differences across the 4 conditions in terms of EEG band power and EEG effective connectivity outflow and inflow with repeated measures ANOVA and paired t tests. The analyses included the data of 51 participants. Notably, EEG band power across the theta, alpha, low-beta, high-beta, and gamma bands varied significantly over the entire scalp (t ≥1.96, P values <.05). Outflow analysis identified condition-specific variations in the delta, alpha, and gamma bands (P values <.05), while inflow analysis revealed significant differences across all frequency bands (P values <.05). Connectivity flow analysis highlighted the predominant influence of the right frontal, central, and parietal brain regions in the neurological mechanisms underlying the breathing training techniques. This study provides neurological evidence supporting the effectiveness of self-help breathing training through the combined use of VR and BF technologies. Our findings suggest the involvement of internal-external attention focus and the dorsal attention network in different breathing training conditions. There is a huge potential for the use of breathing training with VR-BF techniques in terms of clinical settings, the new living style since COVID-19, and the commercial value of introducing VR-BF breathing training into consumer-level digital products. Furthermore, we propose avenues for future research with an emphasis on the exploration of applications and the gamification potential in combined VR and BF breathing training. ClinicalTrials.gov NCT06656741; https://clinicaltrials.gov/study/NCT06656741.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Yang202439034596,
  title = {Muscle activity and hypoalgesia in blood flow restricted versus unrestricted effort-matched resistance exercise in healthy adults.},
  author = {Yang, J and O'Keeffe, R and Shirazi, SY and Mehrdad, S and Atashzar, SF and Rao, S},
  journal = {Physiological reports},
  year = {2024},
  doi = {10.14814/phy2.16037},
  pmid = {39034596},
  url = {https://pubmed.ncbi.nlm.nih.gov/39034596/},
  abstract = {This study assessed muscle activity (root mean square, RMS, and median frequency, MDF) to evaluate the acute response to blood flow restriction (BFR) resistance exercise (RE) and conventional moderate intensity (MI) RE. We also performed exploratory analyses of differences based on sex and exercise-induced hypoalgesia (EIH). Fourteen asymptomatic individuals performed four sets of unilateral leg press with their dominant leg to volitional fatigue under two exercise conditions: BFR RE and MI RE. Dominant side rectus femoris (RF) and vastus lateralis (VL) muscle activity were measured using surface electromyography (sEMG) through exercise. RMS and MDF were calculated and compared between conditions and timepoints using a linear mixed model. Pressure pain thresholds (PPT) were tested before and immediately after exercise and used to quantify EIH. Participants were then divided into EIH responders and nonresponders, and the differences on RMS and MDF were compared between the two groups using Hedges' g. RMS significantly increased over time (RF: p = 0.0039; VL: p = 0.001) but not between conditions (RF: p = 0.4; VL: p = 0.67). MDF decreased over time (RF: p = 0.042; VL: p < 0.001) but not between conditions (RF: p = 0.74; VL: p = 0.77). Consistently lower muscle activation was found in females compared with males (BRF, RF: g = 0.63; VL, g = 0.5. MI, RF: g = 0.72; VL: g = 1.56), with more heterogeneous findings in MDF changes. For BFR, EIH responders showed greater RMS changes (Δ RMS) (RF: g = 0.90; VL: g = 1.21) but similar MDF changes (Δ MDF) (RF: g = 0.45; VL: g = 0.28) compared to nonresponders. For MI, EIH responders demonstrated greater increase on Δ RMS (g = 0.61) and decrease on Δ MDF (g = 0.68) in RF but similar changes in VL (Δ RMS: g = 0.40; Δ MDF: g = 0.39). These results indicate that when exercising to fatigue, no statistically significant difference was observed between BFR RE and conventional MI RE in Δ RMS and Δ MDF. Lower muscle activity was noticed in females. While exercising to volitional fatigue, muscle activity may contribute to EIH.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Tran202438851836,
  title = {Multimodal fusion for anticipating human decision performance.},
  author = {Tran, XT and Do, T and Pal, NR and Jung, TP and Lin, CT},
  journal = {Scientific reports},
  year = {2024},
  doi = {10.1038/s41598-024-63651-2},
  pmid = {38851836},
  url = {https://pubmed.ncbi.nlm.nih.gov/38851836/},
  abstract = {Anticipating human decisions while performing complex tasks remains a formidable challenge. This study proposes a multimodal machine-learning approach that leverages image features and electroencephalography (EEG) data to predict human response correctness in a demanding visual searching task. Notably, we extract a novel set of image features pertaining to object relationships using the Segment Anything Model (SAM), which enhances prediction accuracy compared to traditional features. Additionally, our approach effectively utilizes a combination of EEG signals and image features to streamline the feature set required for the Random Forest Classifier (RFC) while maintaining high accuracy. The findings of this research hold substantial potential for developing advanced fault alert systems, particularly in critical decision-making environments such as the medical and defence sectors.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{OKeeffe202439008387,
  title = {Low-Frequency Motor Cortex EEG Predicts Four Rates of Force Development.},
  author = {O'Keeffe, R and Shirazi, SY and Vecchio, AD and Ibaaez, J and Mrachacz-Kersting, N and Bighamian, R and Rizzo, JR and Farina, D and Atashzar, SF},
  journal = {IEEE transactions on haptics},
  year = {2024},
  doi = {10.1109/TOH.2024.3428308},
  pmid = {39008387},
  url = {https://pubmed.ncbi.nlm.nih.gov/39008387/},
  abstract = {The movement-related cortical potential (MRCP) is a low-frequency component of the electroencephalography (EEG) signal that originates from the motor cortex and surrounding cortical regions. As the MRCP reflects both the intention and execution of motor control, it has the potential to serve as a communication interface between patients and neurorehabilitation robots. In this study, we investigated the EEG signal recorded centered at the Cz electrode with the aim of decoding four rates of force development (RFD) during isometric contractions of the tibialis anterior muscle. The four levels of RFD were defined with respect to the maximum voluntary contraction (MVC) of the muscle as follows: Slow (20% MVC/s), Medium (30% MVC/s), Fast (60% MVC/s), and Ballistic (120% MVC/s). Three feature sets were assessed for describing the EEG traces in the classification process. These included: (i) MRCP Morphological Characteristics in the -band, such as timing and amplitude; (ii) MRCP Statistical Characteristics in the -band, such as standard deviation, mean, and kurtosis; and (iii) Wideband Time-frequency Features in the 0.1-90 Hz range. The four levels of RFD were accurately classified using a support vector machine. When utilizing the Wideband Time-frequency Features, the accuracy was 83% 9% (mean SD). Meanwhile, when using the MRCP Statistical Characteristics, the accuracy was 78% 12% (mean SD). The analysis of the MRCP waveform revealed that it contains highly informative data on the planning, execution, completion, and duration of the isometric dorsiflexion task. The temporal analysis emphasized the importance of the -band in translating to motor command, and this has promising implications for the field of neural engineering systems.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Zhang202439141467,
  title = {Integrating Large Language Model, EEG, and Eye-Tracking for Word-Level Neural State Classification in Reading Comprehension.},
  author = {Zhang, Y and Li, Q and Nahata, S and Jamal, T and Cheng, SK and Cauwenberghs, G and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2024},
  doi = {10.1109/TNSRE.2024.3435460},
  pmid = {39141467},
  url = {https://pubmed.ncbi.nlm.nih.gov/39141467/},
  abstract = {With the recent proliferation of large language models (LLMs), such as Generative Pre-trained Transformers (GPT), there has been a significant shift in exploring human and machine comprehension of semantic language meaning. This shift calls for interdisciplinary research that bridges cognitive science and natural language processing (NLP). This pilot study aims to provide insights into individuals' neural states during a semantic inference reading-comprehension task. We propose jointly analyzing LLMs, eye-gaze, and electroencephalographic (EEG) data to study how the brain processes words with varying degrees of relevance to a keyword during reading. We also use feature engineering to improve the fixation-related EEG data classification while participants read words with high versus low relevance to the keyword. The best validation accuracy in this word-level classification is over 60% across 12 subjects. Words highly relevant to the inference keyword received significantly more eye fixations per word: 1.0584 compared to 0.6576, including words with no fixations. This study represents the first attempt to classify brain states at a word level using LLM-generated labels. It provides valuable insights into human cognitive abilities and Artificial General Intelligence (AGI), and offers guidance for developing potential reading-assisted technologies.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cannard202439097360,
  title = {HRV and EEG correlates of well-being using ultra-short, portable, and low-cost measurements.},
  author = {Cannard, C and Delorme, A and Wahbeh, H},
  journal = {Progress in brain research},
  year = {2024},
  doi = {10.1016/bs.pbr.2024.04.004},
  pmid = {39097360},
  url = {https://pubmed.ncbi.nlm.nih.gov/39097360/},
  abstract = {Wearable electroencephalography (EEG) and electrocardiography (ECG) devices may offer a non-invasive, user-friendly, and cost-effective approach for assessing well-being (WB) in real-world settings. However, challenges remain in dealing with signal artifacts (such as environmental noise and movements) and identifying robust biomarkers. We evaluated the feasibility of using portable hardware to identify potential EEG and heart-rate variability (HRV) correlates of WB. We collected simultaneous ultrashort (2-min) EEG and ECG data from 60 individuals in real-world settings using a wrist ECG electrode connected to a 4-channel wearable EEG headset. These data were processed, assessed for signal quality, and analyzed using the open-source EEGLAB BrainBeats plugin to extract several theory-driven metrics as potential correlates of WB. Namely, the individual alpha frequency (IAF), frontal and posterior alpha asymmetry, and signal entropy for EEG. SDNN, the low/high frequency (LF/HF) ratio, the Poincaré SD1/SD2 ratio, and signal entropy for HRV. We assessed potential associations between these features and the main WB dimensions (hedonic, eudaimonic, global, physical, and social) implementing a pairwise correlation approach, robust Spearman's correlations, and corrections for multiple comparisons. Only eight files showed poor signal quality and were excluded from the analysis. Eudaimonic (psychological) WB was positively correlated with SDNN and the LF/HF ratio. EEG posterior alpha asymmetry was positively correlated with Physical WB (i.e., sleep and pain levels). No relationships were found with the other metrics, or between EEG and HRV metrics. These physiological metrics enable a quick, objective assessment of well-being in real-world settings using scalable, user-friendly tools.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Denissen202439715746,
  title = {HED LANG - A Hierarchical Event Descriptors library extension for annotation of language cognition experiments.},
  author = {Denissen, M and Pöll, B and Robbins, K and Makeig, S and Hutzler, F},
  journal = {Scientific data},
  year = {2024},
  doi = {10.1038/s41597-024-04282-0},
  pmid = {39715746},
  url = {https://pubmed.ncbi.nlm.nih.gov/39715746/},
  abstract = {Experimental design in language cognition research often involves presenting language material while measuring associated behavior and/or neural activity. To make the collected data easily and fully analyzable by both the original data authors and others, it is important to have detailed information about the stimulus presentation events, including the nature and properties of the presented stimuli, using a common vocabulary and syntax. We present HED LANG, a library extension of the Hierarchical Event Descriptors (HED) event annotation schema for time series behavioral and neuroimaging data. HED LANG provides an open source, standardized vocabulary for building detailed, human- and machine-actionable annotations for language cognition datasets. It builds on existing annotation systems in linguistics and is supported by a suite of HED tools for annotating, validating, searching, and characterizing HED-tagged datasets. HED LANG is specific enough to allow event data annotation at the range of levels needed to support many current research paradigms and analyses. Both HED and HED LANG are open to community input and participation, enabling them to evolve with continuing developments in language cognition research.},
  note = {PubMed query source: Scott Makeig}
}

@article{GewirtzMeydan202438382177,
  title = {Global cross-cultural validation of a brief measure for identifying potential suicide risk in 42 countries.},
  author = {Gewirtz-Meydan, A and Koós, M and Nagy, L and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, R and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's research team NA and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strong, C and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Public health},
  year = {2024},
  doi = {10.1016/j.puhe.2023.12.031},
  pmid = {38382177},
  url = {https://pubmed.ncbi.nlm.nih.gov/38382177/},
  abstract = {This study aimed to examine the psychometric properties of the P4 suicide screener in a multinational sample. The primary goal was to evaluate the reliability and validity of the scale and investigate its convergent validity by analyzing its correlation with depression, anxiety, and substance use. The study design is a cross-sectional self-report study conducted across 42 countries. A cross-sectional, self-report study was conducted in 42 countries, with a total of 82,243 participants included in the final data set. The study provides an overview of suicide ideation rates across 42 countries and confirms the structural validity of the P4 screener. The findings indicated that sexual and gender minority individuals exhibited higher rates of suicidal ideation. The P4 screener showed adequate reliability, convergence, and discriminant validity, and a cutoff score of 1 is recommended to identify individuals at risk of suicidal behavior. The study supports the reliability and validity of the P4 suicide screener across 42 diverse countries, highlighting the importance of using a cross-cultural suicide risk assessment to standardize the identification of high-risk individuals and tailoring culturally sensitive suicide prevention strategies.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Liu202440039052,
  title = {Gaze intersection points reveal the onset of visual processing during eye and head movement.},
  author = {Liu, W and Stevenson, C and Chang, CY and Thurman, S and Cohen-Hoffing, R and Jung, TP and Wu, YC},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2024},
  doi = {10.1109/EMBC53108.2024.10781581},
  pmid = {40039052},
  url = {https://pubmed.ncbi.nlm.nih.gov/40039052/},
  abstract = {This study explored the dynamics of steady-state visual evoked potentials (SSVEPs) amid unrestricted head and eye movements using immersive virtual reality (VR) to concurrently record eye and head movement data with a 64-channel electroencephalogram (EEG) during a visual fixation task. Employing a dual-condition approach-eye-shifting and head-turning-the trials were time-locked to stimulus onset, Gaze Intersection Point (GIP) onset, and fixation onset. Eye and head velocity, Canonical Correlation Analysis (CCA) correlation, and Inter-Trial Coherence (ITC) were computed across the trial duration. SSVEP signal detection (reflected in CCA scores) was most closely aligned with the GIP onset. The CCA score increase before fixation suggests that visual processing is not fully suppressed during simultaneous head and eye movements. These findings support the potential of SSVEP for tracking the time course of visual processing in naturalistic settings where research participants are free to move their heads and eyes as they explore their three-dimensional environment.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Zhang202440031482,
  title = {From Word Embedding to Reading Embedding Using Large Language Model, EEG and Eye-tracking.},
  author = {Zhang, Y and Yang, S and Cauwenberghs, G and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2024},
  doi = {10.1109/EMBC53108.2024.10781627},
  pmid = {40031482},
  url = {https://pubmed.ncbi.nlm.nih.gov/40031482/},
  abstract = {Reading comprehension, a fundamental cognitive ability essential for knowledge acquisition, is a complex skill, with a notable number of learners lacking proficiency in this domain. This study introduces innovative tasks for Brain-Computer Interface (BCI), predicting the relevance of words or tokens read by individuals to the target inference words. We use state-of-the-art Large Language Models (LLMs) to guide a new reading embedding representation in training. This representation, integrating EEG and eye-tracking biomarkers through an attention-based transformer encoder, achieved a mean 5-fold cross-validation accuracy of 68.7% across nine subjects using a balanced sample, with the highest single-subject accuracy reaching 71.2%. This study pioneers the integration of LLMs, EEG, and eye-tracking for predicting human reading comprehension at the word level. We fine-tune the pre-trained Bidirectional Encoder Representations from Transformers (BERT) model for word embedding, devoid of information about the reading tasks. Despite this absence of task-specific details, the model effortlessly attains an accuracy of 92.7%, thereby validating our findings from LLMs. This work represents a preliminary step toward developing tools to assist reading. The code and data are available in github.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wisniewski202438339905,
  title = {Finding tau rhythms in EEG: An independent component analysis approach.},
  author = {Wisniewski, MG and Joyner, CN and Zakrzewski, AC and Makeig, S},
  journal = {Human brain mapping},
  year = {2024},
  doi = {10.1002/hbm.26572},
  pmid = {38339905},
  url = {https://pubmed.ncbi.nlm.nih.gov/38339905/},
  abstract = {Tau rhythms are largely defined by sound responsive alpha band (~8-13 Hz) oscillations generated largely within auditory areas of the superior temporal gyri. Studies of tau have mostly employed magnetoencephalography or intracranial recording because of tau's elusiveness in the electroencephalogram. Here, we demonstrate that independent component analysis (ICA) decomposition can be an effective way to identify tau sources and study tau source activities in EEG recordings. Subjects (N = 18) were passively exposed to complex acoustic stimuli while the EEG was recorded from 68 electrodes across the scalp. Subjects' data were split into 60 parallel processing pipelines entailing use of five levels of high-pass filtering (passbands of 0.1, 0.5, 1, 2, and 4 Hz), three levels of low-pass filtering (25, 50, and 100 Hz), and four different ICA algorithms (fastICA, infomax, adaptive mixture ICA [AMICA], and multi-model AMICA [mAMICA]). Tau-related independent component (IC) processes were identified from this data as being localized near the superior temporal gyri with a spectral peak in the 8-13 Hz alpha band. These "tau ICs" showed alpha suppression during sound presentations that was not seen for other commonly observed IC clusters with spectral peaks in the alpha range (e.g., those associated with somatomotor mu, and parietal or occipital alpha). The choice of analysis parameters impacted the likelihood of obtaining tau ICs from an ICA decomposition. Lower cutoff frequencies for high-pass filtering resulted in significantly fewer subjects showing a tau IC than more aggressive high-pass filtering. Decomposition using the fastICA algorithm performed the poorest in this regard, while mAMICA performed best. The best combination of filters and ICA model choice was able to identify at least one tau IC in the data of ~94% of the sample. Altogether, the data reveal close similarities between tau EEG IC dynamics and tau dynamics observed in MEG and intracranial data. Use of relatively aggressive high-pass filters and mAMICA decomposition should allow researchers to identify and characterize tau rhythms in a majority of their subjects. We believe adopting the ICA decomposition approach to EEG analysis can increase the rate and range of discoveries related to auditory responsive tau rhythms.},
  note = {PubMed query source: Scott Makeig}
}

@article{Su202438683718,
  title = {Extracting Stress-Related EEG Patterns From Pre-Sleep EEG for Forecasting Slow-Wave Sleep Deficiency.},
  author = {Su, CH and Ko, LW and Jung, TP and Onton, J and Tzou, SC and Juang, JC and Hsu, CY},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2024},
  doi = {10.1109/TNSRE.2024.3394471},
  pmid = {38683718},
  url = {https://pubmed.ncbi.nlm.nih.gov/38683718/},
  abstract = {Sleep is vital to our daily activity. Lack of proper sleep can impair functionality and overall health. While stress is known for its detrimental impact on sleep quality, the precise effect of pre-sleep stress on subsequent sleep structure remains unknown. This study introduced a novel approach to study the pre-sleep stress effect on sleep structure, specifically slow-wave sleep (SWS) deficiency. To achieve this, we selected forehead resting EEG immediately before and upon sleep onset to extract stress-related neurological markers through power spectra and entropy analysis. These markers include beta/delta correlation, alpha asymmetry, fuzzy entropy (FuzzEn) and spectral entropy (SpEn). Fifteen subjects were included in this study. Our results showed that subjects lacking SWS often exhibited signs of stress in EEG, such as an increased beta/delta correlation, higher alpha asymmetry, and increased FuzzEn in frontal EEG. Conversely, individuals with ample SWS displayed a weak beta/delta correlation and reduced FuzzEn. Finally, we employed several supervised learning models and found that the selected neurological markers can predict subsequent SWS deficiency. Our investigation demonstrated that the classifiers could effectively predict varying levels of slow-wave sleep (SWS) from pre-sleep EEG segments, achieving a mean balanced accuracy surpassing 0.75. The SMOTE-Tomek resampling method could improve the performance to 0.77. This study suggests that stress-related neurological markers derived from pre-sleep EEG can effectively predict SWS deficiency. Such information can be integrated with existing sleep-improving techniques to provide a personalized sleep forecasting and improvement solution.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{He202439133582,
  title = {Exploring Embodied Cognition and Brain Dynamics Under Multi-Tasks Target Detection in Immerse Projector-Based Augmented Reality (IPAR) Scenarios.},
  author = {He, C and Chen, YY and Phang, CR and Chen, IP and Tzou, SC and Jung, TP and Ko, LW},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2024},
  doi = {10.1109/TNSRE.2024.3442241},
  pmid = {39133582},
  url = {https://pubmed.ncbi.nlm.nih.gov/39133582/},
  abstract = {Embodied cognition explores the intricate interaction between the brain, body, and the surrounding environment. The advancement of mobile devices, such as immersive interactive computing and wireless electroencephalogram (EEG) devices, has presented new challenges and opportunities for studying embodied cognition. To address how mobile technology within immersive hybrid settings affects embodied cognition, we propose a target detection multitask incorporating mixed body movement interference and an environmental distraction light signal. We aim to investigate human embodied cognition in immersive projector-based augmented reality (IPAR) scenarios using wireless EEG technology. We recruited and engaged fifteen participants in four multitasking conditions: standing without distraction (SND), walking without distraction (WND), standing with distraction (SD), and walking with distraction (WD). We pre-processed the EEG data using Independent Component Analysis (ICA) to isolate brain sources and K-means clustering to categorize Independent Components (ICs). Following that, we conducted time-frequency and correlation analyses to identify neural dynamics changes associated with multitasking. Our findings reveal a decline in behavioral performance during multitasking activities. We also observed decreases in alpha and beta power in the frontal and motor cortex during standing target search tasks, decreases in theta power, and increases in alpha power in the occipital lobe during multitasking. We also noted perturbations in theta band power during distraction tasks. Notably, physical movement induced more significant fluctuations in the frontal and motor cortex than distractions from social environment light signals. Particularly in scenarios involving walking and multitasking, there was a noticeable reduction in beta suppression. Our study underscores the importance of brain-body collaboration in multitasking scenarios, where the simultaneous engagement of the body and brain in complex tasks highlights the dynamic nature of cognitive processes within the framework of embodied cognition. Furthermore, integrating immersive augmented reality technology into embodied cognition research enhances our understanding of the interplay between the body, environment, and cognitive functions, with profound implications for advancing human-computer interaction and elucidating cognitive dynamics in multitasking.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Huang202438430577,
  title = {Exogenous titanium dioxide nanoparticles alleviate cadmium toxicity by enhancing the antioxidative capacity of Tetrastigma hemsleyanum.},
  author = {Huang, Y and Cai, S and Ying, W and Niu, T and Yan, J and Hu, H and Ruan, S},
  journal = {Ecotoxicology and environmental safety},
  year = {2024},
  doi = {10.1016/j.ecoenv.2024.116166},
  pmid = {38430577},
  url = {https://pubmed.ncbi.nlm.nih.gov/38430577/},
  abstract = {Nanotechnology is one of the most recent approaches employed to defend plants against both biotic and abiotic stress including heavy metals such as Cadmium (Cd). In this study, we evaluated the effects of titanium dioxide (TiO 2 ) nanoparticles (TiO 2  NPs) in alleviating Cd stress in Tetrastigma hemsleyanum Diels et Gilg. Compared with Cd treatment, TiO 2  NPs decreased leaf Cd concentration, restored Cd exposure-related reduction in the biomass to about 69% of control and decreased activities of antioxidative enzymes. Integrative analysis of transcriptome and metabolome revealed 325 differentially expressed genes associated with TiO 2  NP treatment, most of which were enriched in biosynthesis of secondary metabolites. Among them, the flavonoid and phenylpropanoid biosynthetic pathways were significantly regulated to improve the growth of T. hemsleyanum when treated with Cd. In the KEGG Markup Language (KGML) network analysis, we found some commonly regulated pathways between Cd and Cd+TiO 2  NP treatment, including phenylpropanoid biosynthesis, ABC transporters, and isoflavonoid biosynthesis, indicating their potential core network positions in controlling T. hemsleyanum response to Cd stress. Overall, our findings revealed a complex response system for tolerating Cd, encompassing the transportation, reactive oxygen species scavenging, regulation of gene expression, and metabolite accumulation in T. hemsleyanum. Our results indicate that TiO 2  NP can be used to reduce Cd toxicity in T. hemsleyanum.},
  note = {PubMed query source: Ying Wu}
}

@article{Cohen202439622875,
  title = {Examining the effects of biofield therapy through simultaneous assessment of electrophysiological and cellular outcomes.},
  author = {Cohen, L and Delorme, A and Cusimano, A and Chakraborty, S and Nguyen, P and Deng, D and Iqbal, S and Nelson, M and Wei, D and Fields, C and Yang, P},
  journal = {Scientific reports},
  year = {2024},
  doi = {10.1038/s41598-024-79617-3},
  pmid = {39622875},
  url = {https://pubmed.ncbi.nlm.nih.gov/39622875/},
  abstract = {In this case study, a self-described biofield therapy (BT) practitioner (participant) took part in multiple (n = 60) treatment and control (non-treatment) sessions under double-blind conditions. During the treatment phases, the participant provided BT treatment at a distance of about 12 inches from the cells, alternating with rest phases where no such efforts were made. Human pancreatic cancer cell activity was assessed using three markers - cytoskeleton changes (tubulin and β-actin) and Ca 2+  uptake. The study examined changes in the participant's physiological parameters including electroencephalogram (EEG) and heart rate measures during the treatment of: (1) live cells and (2) either dead cells or medium only with no cells (control group). Changes in cellular outcomes and if there was an association between the participant's physiological parameters and cellular outcomes were examined. The experimental setup was a 2 × 2 design, contrasting cell type (live vs. control) against session type (treatment vs. non-treatment). Parallel sham-treated control cells were examined for changes in the cell parameters over time while controlling for the presence of a person in front of the cells mimicking the distance and movements of the participant. The participant's physiological data, including 64-channel EEG and heart rate, were continuously monitored throughout these sessions. We observed significant (p < 0.01) spectral changes in the participant's EEG during BT treatment in all frequency bands of interest, as well as in heart rate variability (HRV) (RMSSD measure; p < 0.01). We also observed significant differences in beta and gamma EEG and HRV (pNN50 measure) when the participant treated live but not control cells (p = 0.02). However, no interaction between treatment and cell type (live vs. dead cells/medium-no cells) was observed. We observed Ca 2+  uptake increased over time during both BT and sham treatment, but the increase was significantly less for the BT group relative to the sham-treatment controls (p = 0.03). When using Granger causality to assess causal directional associations between cell markers and participant's physiological parameters, EEG measurements showed significant bidirectional causal effects with cell metrics, especially β-actin and intracellular Ca 2+  levels (p < 0.000001). These outcomes suggest a complex relationship between physiological responses and cellular effects during BT treatment sessions. Given the study's limitations, follow-up investigations are warranted.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Makeig202438846339,
  title = {Events in context-The HED framework for the study of brain, experience and behavior.},
  author = {Makeig, S and Robbins, K},
  journal = {Frontiers in neuroinformatics},
  year = {2024},
  doi = {10.3389/fninf.2024.1292667},
  pmid = {38846339},
  url = {https://pubmed.ncbi.nlm.nih.gov/38846339/},
  abstract = {The brain is a complex dynamic system whose current state is inextricably coupled to awareness of past, current, and anticipated future threats and opportunities that continually affect awareness and behavioral goals and decisions. Brain activity is driven on multiple time scales by an ever-evolving flow of sensory, proprioceptive, and idiothetic experience. Neuroimaging experiments seek to isolate and focus on some aspect of these complex dynamics to better understand how human experience, cognition, behavior, and health are supported by brain activity. Here we consider an event-related data modeling approach that seeks to parse experience and behavior into a set of time-delimited events. We distinguish between  event processes  themselves, that unfold through time, and  event markers  that record the experiment timeline latencies of event onset, offset, and any other event phase transitions. Precise descriptions of experiment events (sensory, motor, or other) allow participant experience and behavior to be interpreted in the context either of the event itself or of all or any experiment events. We discuss how events in neuroimaging experiments have been, are currently, and should best be identified and represented with emphasis on the importance of modeling both events and event context for meaningful interpretation of relationships between brain dynamics, experience, and behavior. We show how text annotation of time series neuroimaging data using the system of Hierarchical Event Descriptors (HED; https://www.hedtags.org) can more adequately model the roles of both events and their ever-evolving context than current data annotation practice and can thereby facilitate data analysis, meta-analysis, and mega-analysis. Finally, we discuss ways in which the HED system must continue to expand to serve the evolving needs of neuroimaging research.},
  note = {PubMed query source: Scott Makeig}
}

@article{Rede202438784165,
  title = {Evaluating the effectiveness of a mobile app-based self-guided psychological interventions to reduce relapse in substance use disorder: protocol for a randomized controlled trial.},
  author = {Redeł, A and Binkowska, AA and Obarska, K and Marcowski, P and Szymczak, K and Lewczuk, K and Solich, K and Banaszak, M and Woronowicz, B and Nowicka, M and Skorko, M and Gola, M and Bielecki, M},
  journal = {Frontiers in psychiatry},
  year = {2024},
  doi = {10.3389/fpsyt.2024.1335105},
  pmid = {38784165},
  url = {https://pubmed.ncbi.nlm.nih.gov/38784165/},
  abstract = {Substance Use Disorder (SUD) persists as a significant public health challenge worldwide, with an estimated prevalence of approximately 10-15% across the global populace. This condition is characterized by a notably high risk of lapses and relapses, even subsequent to treatment interventions. Mobile health interventions, owing to their widespread accessibility, emerge as a promising approach to diminish the risk of relapse post-treatment and to broaden the scope of care, especially in regions with a scarcity of trained medical professionals. This study is designed to assess the effectiveness of mobile interventions in mitigating cravings and preventing lapses among individuals diagnosed with SUD. Employing a two-armed, randomized controlled trial framework, the study will evaluate a self-administered psychological intervention delivered through a mobile application, Nałogometr 2.0. Over a period of three months, participants will engage with intervention modules that primarily incorporate mindfulness techniques and Cognitive Behavioral Therapy (CBT) principles. Ecological Momentary Assessment (EMA) will be utilized to gather longitudinal data on a range of variables that are indicative of craving intensity and the risk of lapse. In addition to this, a monthly-administered battery of questionnaires will be employed to gauge the severity of substance dependence, as well as to measure levels of anxiety, depression, and overall life satisfaction. Results will be submitted for publication in peer-reviewed journals. https://clinicaltrials.gov/, identifier [NCT05730504].},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wang202439453939,
  title = {Empowering legal justice with AI: A reinforcement learning SAC-VAE framework for advanced legal text summarization.},
  author = {Wang, X and Wu, YC},
  journal = {PloS one},
  year = {2024},
  doi = {10.1371/journal.pone.0312623},
  pmid = {39453939},
  url = {https://pubmed.ncbi.nlm.nih.gov/39453939/},
  abstract = {Automated summarization of legal texts poses a significant challenge due to the complex and specialized nature of legal documentation. Despite the recent progress in reinforcement learning for natural language text summarization, its application in the legal domain has been less effective. This paper introduces SAC-VAE, a novel reinforcement learning framework specifically designed for legal text summarization. We leverage a Variational Autoencoder (VAE) to condense the high-dimensional state space into a more manageable lower-dimensional feature space. These compressed features are subsequently utilized by the Soft Actor-Critic (SAC) algorithm for policy learning, facilitating the automated generation of summaries from legal texts. Through comprehensive experimentation, we have empirically demonstrated the effectiveness and superior performance of the SAC-VAE framework in legal text summarization.},
  note = {PubMed query source: Ying Wu}
}

@article{Draps202438967992,
  title = {Emotional interference and attentional bias in compulsive sexual behaviors disorder - An fMRI study on heterosexual males.},
  author = {Draps, M and Kulesza, M and Glica, A and Szymanowska, J and Lewińska, K and Żukrowska, W and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2024},
  doi = {10.1556/2006.2024.00033},
  pmid = {38967992},
  url = {https://pubmed.ncbi.nlm.nih.gov/38967992/},
  abstract = {Despite the inclusion of the Compulsive Sexual Behavior Disorder (CSBD) in the 11th edition of the International Classification of Diseases, emotional and cognitive impairments related to CSBD remains unclear. This study aimed to investigate the behavioral and neuronal effects of emotional interference on cognition among CSBD patients. Thirty heterosexual males with CSBD and matched healthy controls (HC) were studied with the Emotional Stroop Task using 5 categories of emotionally arousing words (sex-related, positive, fear-related, negative, neutral) during functional magnetic imaging. At the behavioral level, we found the main effect of the condition: sex-related words evoked a stronger Stroop effect than other conditions. At the neural level, we found a significant group effect. Among CSBD patients processing of sex-related words was related to increased activity in the right putamen, right thalamus, hippocampi, and left pulvinar, when compared to HC. We also found a negative correlation between neuronal activation and time spent on sexual activity during the week preceding study and numerous group differences in brain regions connected to the emotional and motivational processing of sexually explicit material, correlating with CSBD symptoms. Behavioral results indicate a specific attentional bias toward sex-related stimuli in both groups, while neural data uncovered stronger reactivity to sex-related words in CSBD compared to HC. This reactivity is related to CSBD symptoms and provides evidence for the interference of sex-related stimuli with cognition. Such results are firmly in line with the Incentive Salience Theory and conceptualizing CSBD as a behavioral addiction.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Yitao202439104701,
  title = {Dynamic brain functional states associated with inhibition control under different altitudes.},
  author = {Yitao, L and Lv, Z and Xin, W and Yongchen, F and Ying, W},
  journal = {Cognitive neurodynamics},
  year = {2024},
  doi = {10.1007/s11571-023-10054-0},
  pmid = {39104701},
  url = {https://pubmed.ncbi.nlm.nih.gov/39104701/},
  abstract = {Chronic exposure to the hypobaric hypoxia environment of plateau could influence human cognitive behaviours which are supported by dynamic brain connectivity states. Until now, how functional connectivity (FC) of the brain network changes with altitudes is still unclear. In this article, we used EEG data of the Go/NoGo paradigm from Weinan (347 m) and Nyingchi (2950 m). A combination of dynamic FC (dFC) and the K-means cluster was employed to extract dynamic FC states which were later distinguished by graph metrics. Besides, temporal properties of networks such as fractional windows (FW), transition numbers (TN) and mean dwell time (MDT) were calculated. Finally, we successfully extracted two different states from dFC matrices where State 1 was verified to have higher functional integration and segregation. The dFC states dynamically switched during the Go/NoGo tasks and the FW of State 1 showed a rise in the high-altitude participants. Also, in the regional analysis, we found higher state deviation in the fronto-parietal cortices and enhanced FC strength in the occipital lobe. These results demonstrated that long-term exposure to the high-altitude environment could lead brain networks to reorganize as networks with higher inter- and intra-networks information transfer efficiency, which could be attributed to a compensatory mechanism to the compromised brain function due to the plateau environment. This study provides a new perspective in considering how the plateau impacted cognitive impairment.},
  note = {PubMed query source: Ying Wu}
}

@article{Quintana202438244805,
  title = {Cross-cultural validation and measurement invariance of anxiety and depression symptoms: A study of the Brief Symptom Inventory (BSI) in 42 countries.},
  author = {Quintana, GR and Ponce, FP and Escudero-Pastén, JI and Santibáñez-Palma, JF and Nagy, L and Koós, M and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's research team NA and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Journal of affective disorders},
  year = {2024},
  doi = {10.1016/j.jad.2024.01.127},
  pmid = {38244805},
  url = {https://pubmed.ncbi.nlm.nih.gov/38244805/},
  abstract = {Depression and anxiety are among the most prevalent mental health issues experienced worldwide. However, whereas cross-cultural studies utilize psychometrically valid and reliable scales, fewer can meaningfully compare these conditions across different groups. To address this gap, the current study aimed to psychometrically assess the Brief Symptomatology Index (BSI) in 42 countries. Using data from the International Sex Survey (N = 82,243; M age  = 32.39; SD age  = 12.52; women: n = 46,874; 57 %), we examined the reliability of depression and anxiety symptom scores of the BSI-18, as well as evaluated evidence of construct, invariance, and criterion-related validity in predicting clinically relevant variables across countries, languages, genders, and sexual orientations. Results corroborated an invariant, two-factor structure across all groups tested, exhibiting excellent reliability estimates for both subscales. The 'caseness' criterion effectively discriminated among those at low and high risk of depression and anxiety, yielding differential effects on the clinical criteria examined. The predictive validation was not made against a clinical diagnosis, and the full BSI-18 scale was not examined (excluding the somatization sub-dimension), limiting the validation scope of the BSI-18. Finally, the study was conducted online, mainly by advertisements through social media, ultimately skewing our sample towards women, younger, and highly educated populations. The results support that the BSI-12 is a valid and reliable assessment tool for assessing depression and anxiety symptoms across countries, languages, genders, and sexual orientations. Further, its caseness criterion can discriminate well between participants at high and low risk of depression and anxiety.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Lewczuk202438180045,
  title = {Cross-Cultural Adult ADHD Assessment in 42 Countries Using the Adult ADHD Self-Report Scale Screener.},
  author = {Lewczuk, K and Marcowski, P and Wizła, M and Gola, M and Nagy, L and Koós, M and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lin, CY and Lin, YC and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University’s research team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Ünsal, BC and Vaillancourt-Morel, MP and Claire Van Hout, M and Bőthe, B},
  journal = {Journal of attention disorders},
  year = {2024},
  doi = {10.1177/10870547231215518},
  pmid = {38180045},
  url = {https://pubmed.ncbi.nlm.nih.gov/38180045/},
  abstract = {We analyzed adult ADHD symptoms in a cross-cultural context, including investigating the occurrence and potential correlates of adult ADHD and psychometric examination of the Adult ADHD Self-Report Scale (ASRS) Screener. Our analysis is based on a large-scale research project involving 42 countries  (International Sex Survey, N =72,627, 57%  women, Mage =32.84;  SDage =12.57). The ASRS Screener demonstrated good reliability and validity, along with partial invariance across different languages, countries, and genders. The occurrence of being at risk for adult ADHD was relatively high (21.4% for women, 18.1% for men). The highest scores were obtained in the US, Canada, and other English-speaking Western countries, with significantly lower scores among East Asian and non-English-speaking European countries. Moreover, ADHD symptom severity and occurrence were especially high among gender-diverse individuals. Significant associations between adult ADHD symptoms and age, mental and sexual health, and socioeconomic status were observed. Present results show significant cross-cultural variability in adult ADHD occurrence as well as highlight important factors related to adult ADHD. Moreover, the importance of further research on adult ADHD in previously understudied populations (non-Western countries) and minority groups (gender-diverse individuals) is stressed. Lastly, the present analysis is consistent with previous evidence showing low specificity of adult ADHD screening instruments and contributes to the current discussion on accurate adult ADHD screening and diagnosis.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Laskowski202438929566,
  title = {Comparison of Navigated and Frame-Based Stereotactic Biopsy-A Single-Center Cohort Study.},
  author = {Laskowski, M and Paździora, P and Błaszczyk, B and Gola, M and Ciekalski, M and Koperczak, A and Marcin, S and Zimny, M and Zioła-Paździora, A and Wojtacha, M and Rudnik, A},
  journal = {Medicina (Kaunas, Lithuania)},
  year = {2024},
  doi = {10.3390/medicina60060949},
  pmid = {38929566},
  url = {https://pubmed.ncbi.nlm.nih.gov/38929566/},
  abstract = {Background and Objectives : As brain lesions present complex diagnostic challenges, accurate tissue sampling via biopsy is critical for effective treatment planning. Traditional frame-based stereotactic biopsy has been complemented by navigated biopsy techniques, leveraging advancements in imaging and navigation technology. This study aims to compare the navigated and frame-based stereotactic biopsy methods in a clinical setting, evaluating their efficacy, safety, and diagnostic outcomes to determine the optimal approach for precise brain lesion targeting.  Materials and Methods : retrospective analysis was conducted on patients who underwent brain biopsies between January 2017 and August 2023 at an academic medical center. Data on patient demographics, clinical characteristics, biopsy technique (navigated vs. frame-based), and outcomes including accuracy, complications, and hospital stay duration were analyzed.  Results : The cohort comprised 112 patients, with no significant age or gender differences between groups. Symptoms leading to biopsy were predominantly diminished muscle strength (42.0%), cognitive issues (28.6%), and aphasia (24.1%). Tumors were most common in the deep hemisphere (24.1%). The median hospital stay was 5 days, with a rehospitalization rate of 27.7%. Complications occurred in 4.47% of patients, showing no significant difference between biopsy methods. However, navigated biopsies resulted in fewer samples ( p  < 0.001) but with comparable diagnostic accuracy as frame-based biopsies.  Conclusions : Navigated and frame-based stereotactic biopsies are both effective and safe, with comparable accuracy and complication rates. The choice of technique should consider lesion specifics, surgeon preference, and technological availability. The findings highlight the importance of advanced neurosurgical techniques in enhancing patient care and outcomes.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Luo202439622076,
  title = {Comparing the Accuracy of Two Generated Large Language Models in Identifying Health-Related Rumors or Misconceptions and the Applicability in Health Science Popularization: Proof-of-Concept Study.},
  author = {Luo, Y and Miao, Y and Zhao, Y and Li, J and Chen, Y and Yue, Y and Wu, Y},
  journal = {JMIR formative research},
  year = {2024},
  doi = {10.2196/63188},
  pmid = {39622076},
  url = {https://pubmed.ncbi.nlm.nih.gov/39622076/},
  abstract = {Health-related rumors and misconceptions are spreading at an alarming rate, fueled by the rapid development of the internet and the exponential growth of social media platforms. This phenomenon has become a pressing global concern, as the dissemination of false information can have severe consequences, including widespread panic, social instability, and even public health crises. The aim of the study is to compare the accuracy of rumor identification and the effectiveness of health science popularization between 2 generated large language models in Chinese (GPT-4 by OpenAI and Enhanced Representation through Knowledge Integration Bot [ERNIE Bot] 4.0 by Baidu). In total, 20 health rumors and misconceptions, along with 10 health truths, were randomly inputted into GPT-4 and ERNIE Bot 4.0. We prompted them to determine whether the statements were rumors or misconceptions and provide explanations for their judgment. Further, we asked them to generate a health science popularization essay. We evaluated the outcomes in terms of accuracy, effectiveness, readability, and applicability. Accuracy was assessed by the rate of correctly identifying health-related rumors, misconceptions, and truths. Effectiveness was determined by the accuracy of the generated explanation, which was assessed collaboratively by 2 research team members with a PhD in nursing. Readability was calculated by the readability formula of Chinese health education materials. Applicability was evaluated by the Chinese Suitability Assessment of Materials. GPT-4 and ERNIE Bot 4.0 correctly identified all health rumors and misconceptions (100% accuracy rate). For truths, the accuracy rate was 70% (7/10) and 100% (10/10), respectively. Both mostly provided widely recognized viewpoints without obvious errors. The average readability score for the health essays was 2.92 (SD 0.85) for GPT-4 and 3.02 (SD 0.84) for ERNIE Bot 4.0 (P=.65). For applicability, except for the content and cultural appropriateness category, significant differences were observed in the total score and scores in other dimensions between them (P<.05). ERNIE Bot 4.0 demonstrated similar accuracy to GPT-4 in identifying Chinese rumors. Both provided widely accepted views, despite some inaccuracies. These insights enhance understanding and correct misunderstandings. For health essays, educators can learn from readable language styles of GLLMs. Finally, ERNIE Bot 4.0 aligns with Chinese expression habits, making it a good choice for a better Chinese reading experience.},
  note = {PubMed query source: Ying Wu}
}

@article{Cannard202438738870,
  title = {BrainBeats as an Open-Source EEGLAB Plugin to Jointly Analyze EEG and Cardiovascular Signals.},
  author = {Cannard, C and Wahbeh, H and Delorme, A},
  journal = {Journal of visualized experiments : JoVE},
  year = {2024},
  doi = {10.3791/65829},
  pmid = {38738870},
  url = {https://pubmed.ncbi.nlm.nih.gov/38738870/},
  abstract = {The interplay between the brain and the cardiovascular systems is garnering increased attention for its potential to advance our understanding of human physiology and improve health outcomes. However, the multimodal analysis of these signals is challenging due to the lack of guidelines, standardized signal processing and statistical tools, graphical user interfaces (GUIs), and automation for processing large datasets or increasing reproducibility. A further void exists in standardized EEG and heart-rate variability (HRV) feature extraction methods, undermining clinical diagnostics or the robustness of machine learning (ML) models. In response to these limitations, we introduce the BrainBeats toolbox. Implemented as an open-source EEGLAB plugin, BrainBeats integrates three main protocols: 1) Heartbeat-evoked potentials (HEP) and oscillations (HEO) for assessing time-locked brain-heart interplay at the millisecond accuracy; 2) EEG and HRV feature extraction for examining associations/differences between various brain and heart metrics or for building robust feature-based ML models; 3) Automated extraction of heart artifacts from EEG signals to remove any potential cardiovascular contamination while conducting EEG analysis. We provide a step-by-step tutorial for applying these three methods to an open-source dataset containing simultaneous 64-channel EEG, ECG, and PPG signals. Users can easily fine-tune parameters to tailor their unique research needs using the graphical user interface (GUI) or the command line. BrainBeats should make brain-heart interplay research more accessible and reproducible.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Liu202438007187,
  title = {Activation network improves spatiotemporal modelling of human brain communication processes.},
  author = {Liu, X and Wang, Z and Liu, S and Gong, L and Sosa, PAV and Becker, B and Jung, TP and Dai, XJ and Wan, F},
  journal = {NeuroImage},
  year = {2024},
  doi = {10.1016/j.neuroimage.2023.120472},
  pmid = {38007187},
  url = {https://pubmed.ncbi.nlm.nih.gov/38007187/},
  abstract = {Dynamic functional networks (DFN) have considerably advanced modelling of the brain communication processes. The prevailing implementation capitalizes on the system and network-level correlations between time series. However, this approach does not account for the continuous impact of non-dynamic dependencies within the statistical correlation, resulting in relatively stable connectivity patterns of DFN over time with limited sensitivity for communication dynamic between brain regions. Here, we propose an activation network framework based on the activity of functional connectivity (AFC) to extract new types of connectivity patterns during brain communication process. The AFC captures potential time-specific fluctuations associated with the brain communication processes by eliminating the non-dynamic dependency of the statistical correlation. In a simulation study, the positive correlation (r=0.966,p<0.001) between the extracted dynamic dependencies and the simulated "ground truth" validates the method's dynamic detection capability. Applying to autism spectrum disorders (ASD) and COVID-19 datasets, the proposed activation network extracts richer topological reorganization information, which is largely invisible to the DFN. Detailed, the activation network exhibits significant inter-regional connections between function-specific subnetworks and reconfigures more efficiently in the temporal dimension. Furthermore, the DFN fails to distinguish between patients and healthy controls. However, the proposed method reveals a significant decrease (p<0.05) in brain information processing abilities in patients. Finally, combining two types of networks successfully classifies ASD (83.636 % ± 11.969 %,mean±std) and COVID-19 (67.333 % ± 5.398 %). These findings suggest the proposed method could be a potential analytic framework for elucidating the neural mechanism of brain dynamics.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Tseng202439167520,
  title = {Accurate Mental Stress Detection Using Sequential Backward Selection and Adaptive Synthetic Methods.},
  author = {Tseng, HC and Tai, KY and Ma, YZ and Van, LD and Ko, LW and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2024},
  doi = {10.1109/TNSRE.2024.3447274},
  pmid = {39167520},
  url = {https://pubmed.ncbi.nlm.nih.gov/39167520/},
  abstract = {The daily experience of mental stress profoundly influences our health and work performance while concurrently triggering alterations in brain electrical activity. Electroencephalogram (EEG) is a widely adopted method for assessing cognitive and affective states. This study delves into the EEG correlates of stress and the potential use of resting EEG in evaluating stress levels. Over 13 weeks, our longitudinal study focuses on the real-life experiences of college students, collecting data from each of the 18 participants across multiple days in classroom settings. To tackle the complexity arising from the multitude of EEG features and the imbalance in data samples across stress levels, we use the sequential backward selection (SBS) method for feature selection and the adaptive synthetic (ADASYN) sampling algorithm for imbalanced data. Our findings unveil that delta and theta features account for approximately 50% of the selected features through the SBS process. In leave-one-out (LOO) cross-validation, the combination of band power and pair-wise coherence (COH) achieves a maximum balanced accuracy of 94.8% in stress-level detection for the above daily stress dataset. Notably, using ADASYN and borderline synthesized minority over-sampling technique (borderline-SMOTE) methods enhances model accuracy compared to the traditional SMOTE approach. These results provide valuable insights into using EEG signals for assessing stress levels in real-life scenarios, shedding light on potential strategies for managing stress more effectively.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Ji202438812288,
  title = {A user-friendly visual brain-computer interface based on high-frequency steady-state visual evoked fields recorded by OPM-MEG.},
  author = {Ji, D and Xiao, X and Wu, J and He, X and Zhang, G and Guo, R and Liu, M and Xu, M and Lin, Q and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2024},
  doi = {10.1088/1741-2552/ad44d8},
  pmid = {38812288},
  url = {https://pubmed.ncbi.nlm.nih.gov/38812288/},
  abstract = {Objective . Magnetoencephalography (MEG) shares a comparable time resolution with electroencephalography. However, MEG excels in spatial resolution, enabling it to capture even the subtlest and weakest brain signals for brain-computer interfaces (BCIs). Leveraging MEG's capabilities, specifically with optically pumped magnetometers (OPM-MEG), proves to be a promising avenue for advancing MEG-BCIs, owing to its exceptional sensitivity and portability. This study harnesses the power of high-frequency steady-state visual evoked fields (SSVEFs) to build an MEG-BCI system that is flickering-imperceptible, user-friendly, and highly accurate. Approach. We have constructed a nine-command BCI that operates on high-frequency SSVEF (58-62 Hz with a 0.5 Hz interval) stimulation. We achieved this by placing the light source inside and outside the magnetic shielding room, ensuring compliance with non-magnetic and visual stimulus presentation requirements. Five participants took part in offline experiments, during which we collected six-channel multi-dimensional MEG signals along both the vertical ( Z -axis) and tangential ( Y -axis) components. Our approach leveraged the ensemble task-related component analysis algorithm for SSVEF identification and system performance evaluation. Main Results. The offline average accuracy of our proposed system reached an impressive 92.98% when considering multi-dimensional conjoint analysis using data from both the Z and Y axes. Our method achieved a theoretical average information transfer rate (ITR) of 58.36 bits min -1 with a data length of 0.7 s, and the highest individual ITR reached an impressive 63.75 bits min -1 . Significance. This study marks the first exploration of high-frequency SSVEF-BCI based on OPM-MEG. These results underscore the potential and feasibility of MEG in detecting subtle brain signals, offering both theoretical insights and practical value in advancing the development and application of MEG in BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Leng202439556943,
  title = {A multi-feature fusion graph attention network for decoding motor imagery intention in spinal cord injury patients.},
  author = {Leng, J and Gao, L and Jiang, X and Lou, Y and Sun, Y and Wang, C and Li, J and Zhao, H and Feng, C and Xu, F and Zhang, Y and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2024},
  doi = {10.1088/1741-2552/ad9403},
  pmid = {39556943},
  url = {https://pubmed.ncbi.nlm.nih.gov/39556943/},
  abstract = {Objective. Electroencephalogram (EEG) signals exhibit temporal-frequency-spatial multi-domain feature, and due to the nonplanar nature of the brain surface, the electrode distributions follow non-Euclidean topology. To fully resolve the EEG signals, this study proposes a temporal-frequency-spatial multi-domain feature fusion graph attention network (GAT) for motor imagery (MI) intention recognition in spinal cord injury (SCI) patients. Approach. The proposed model uses phase-locked value (PLV) to extract spatial phase connectivity information between EEG channels and continuous wavelet transform to extract valid EEG information in the time-frequency domain. It then models as a graph data structure containing multi-domain information. The gated recurrent unit and GAT learn EEG's dynamic temporal-spatial information. Finally, the fully connected layer outputs the MI intention recognition results. Main results. After 10 times 10-fold cross-validation, the proposed model can achieve an average accuracy of 95.82%. Furthermore, this study analyses the event-related desynchronization/event-related synchronization and PLV brain network to explore the brain activity of SCI patients during MI. Significance. This study confirms the potential of the proposed model in terms of EEG decoding performance and provides a reference for the mechanism of neural activity in SCI patients.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chiang202337040738,
  title = {Using EEG signals to assess workload during memory retrieval in a real-world scenario.},
  author = {Chiang, KJ and Dong, S and Cheng, CK and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/accbed},
  pmid = {37040738},
  url = {https://pubmed.ncbi.nlm.nih.gov/37040738/},
  abstract = {Objective . The electroencephalogram (EEG) is gaining popularity as a physiological measure for neuroergonomics in human factor studies because it is objective, less prone to bias, and capable of assessing the dynamics of cognitive states. This study investigated the associations between memory workload and EEG during participants' typical office tasks on a single-monitor and dual-monitor arrangement. We expect a higher memory workload for the single-monitor arrangement. Approach . We designed an experiment that mimics the scenario of a subject performing some office work and examined whether the subjects experienced various levels of memory workload in two different office setups: (1) a single-monitor setup and (2) a dual-monitor setup. We used EEG band power, mutual information, and coherence as features to train machine learning models to classify high versus low memory workload states. Main results . The study results showed that these characteristics exhibited significant differences that were consistent across all participants. We also verified the robustness and consistency of these EEG signatures in a different data set collected during a Sternberg task in a prior study. Significance . The study found the EEG correlates of memory workload across individuals, demonstrating the effectiveness of using EEG analysis in conducting real-world neuroergonomic studies.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Delorme202338179199,
  title = {This is no "ICA bug": response to the article, "ICA's bug: how ghost ICs emerge from effective rank deficiency caused by EEG electrode interpolation and incorrect re-referencing".},
  author = {Delorme, A and Makeig, S},
  journal = {Frontiers in neuroimaging},
  year = {2023},
  doi = {10.3389/fnimg.2023.1331404},
  pmid = {38179199},
  url = {https://pubmed.ncbi.nlm.nih.gov/38179199/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lee202337453212,
  title = {The eleven-item Alcohol, Smoking and Substance Involvement Screening Test (ASSIST-11): Cross-cultural psychometric evaluation across 42 countries.},
  author = {Lee, CT and Lin, CY and Koós, M and Nagy, L and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, RI and Fernandez, DP and Fernandez, EF and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, M and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Milea, I and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's Research Team(,) and Ponce, FP and Quintana, GR and Garzola, GCQ and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Journal of psychiatric research},
  year = {2023},
  doi = {10.1016/j.jpsychires.2023.06.033},
  pmid = {37453212},
  url = {https://pubmed.ncbi.nlm.nih.gov/37453212/},
  abstract = {The Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) is an instrument to screen substance-use-related health risks. However, little is known whether the ASSIST could be further shortened while remaining psychometrically sound across different countries, languages, gender identities, and sexual-orientation-based groups. The study aimed to validate a shortened 11-item ASSIST (ASSIST-11). Using the International Sex Survey data, 82,243 participants (M  age  = 32.39 years) across 42 countries and 26 languages completed questions from the ASSIST-11 regarding gender identity, sexual orientation, and other information. Confirmatory factor analysis (CFA) and multigroup CFA (MGCFA) evaluated the ASSIST-11's structure and tested measurement invariance across groups. Cronbach's α and McDonald's ω were used to examine the internal consistency. Cohen's d and independent t-tests were used to examine known-group validity. The ASSIST-11 was unidimensional across countries, languages, age groups, gender identities (i.e., men, women, and gender-diverse individuals), and sexual orientations (i.e., heterosexual and sexual minority individuals). Cronbach's α was 0.63 and McDonald's ω was 0.68 for the ASSIST-11. Known-group validity was supported by Cohen's d (range between 0.23 and 0.40) with significant differences (p-values<0.001). The ASSIST-11 is a modified instrument with a unidimensional factor structure across different languages, age groups, countries, gender identities, and sexual orientations. The low internal consistency of the ASSIST-11 might be acceptable as it assesses a broad concept (i.e., use of several different substances). Healthcare providers and researchers may use the ASSIST-11 to quickly assess substance-use information from general populations and evaluate the need to follow up with more detailed questions about substance use.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Lewczuk202335896936,
  title = {The Relation of Sexual Attitudes to Hypersexuality and Problematic Pornography Use.},
  author = {Lewczuk, K and Wizła, M and Gola, M},
  journal = {Archives of sexual behavior},
  year = {2023},
  doi = {10.1007/s10508-022-02358-9},
  pmid = {35896936},
  url = {https://pubmed.ncbi.nlm.nih.gov/35896936/},
  abstract = {Previous studies have shown that specific attitudes related to moral convictions can have an important role in the development and maintenance of problematic sexual behavior symptoms. However, although other types of attitudes, like sexual attitudes, are potentially highly relevant, they have not yet been studied in this role. We investigated how four dimensions of sexual attitudes: Permissiveness, Birth Control, Communion and Instrumentality, contribute to problematic pornography use (PPU) and hypersexual disorder (HD) symptoms, controlling for religiosity, sex, age and relationship status. The study was administered through an online questionnaire and based on a representative sample of n = 1036 (M age  = 43.28, SD = 14.21; 50.3% women) Polish adult citizens. When adjusting for other variables, higher sexual Permissiveness positively predicted HD and PPU among both men (HD: β = .26, p < .001; PPU: β = .22, p < .001) and women (HD: β = .44, p < .001; PPU: β = .26; p < .001). Sexual Instrumentality positively, although weakly, contributed to HD severity among men (β = .11, p < .05). Attitudes reflecting higher support for responsible sexuality (Birth Control subscale) negatively and weakly predicted HD among women (β = - .11, p < .05). Permissiveness was also the only sexual attitude dimension that consistently predicted a higher frequency of sexual activity among men and women. Based on the cutoff criteria proposed by the authors of the used screening instruments (≥ 53 points for the Hypersexual Behavior Inventory and ≥ 4 points for the Brief Pornography Screen), the prevalence of being at risk for HD was 10.0% (men: 11.4%, women: 8.7%) and for PPU was 17.8% (men: 26.8%, women: 9.1%). Our results point to a significant contribution of sexual attitudes to problematic sexual behavior symptoms, which was not encapsulated by the previously studied influence of religious beliefs, although most of the obtained relationships were relatively weak. Particularly, a consistent link between permissive attitudes and both HD and PPU among men and women may indicate that permissive attitudes can potentially contribute to the development and maintenance of problematic sexual behavior. The prevalence of being at risk for PPU (and to some degree HD) in the current representative sample was high. Such results raise questions about the appropriateness of the proposed cutoff criteria and the risk of overpathologizing normative sexual activity, if the cutoff thresholds are not tailored adequately. The results have implications for the assessment, diagnosis and theory of problematic sexual behavior.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Maymon202337584835,
  title = {The Promises and Pitfalls of Virtual Reality.},
  author = {Maymon, C and Wu, YC and Grimshaw, G},
  journal = {Current topics in behavioral neurosciences},
  year = {2023},
  doi = {10.1007/7854_2023_440},
  pmid = {37584835},
  url = {https://pubmed.ncbi.nlm.nih.gov/37584835/},
  abstract = {Increasingly, Virtual Reality technologies are finding a place in psychology and behavioral neuroscience labs. Immersing participants in virtual worlds enables researchers to investigate empirical questions in realistic or imaginary environments while measuring a wide range of behavioral responses, without sacrificing experimental control. In this chapter, we aim to provide a balanced appraisal of VR research methods. We describe how VR can help advance psychological science by opening pathways for addressing many pernicious challenges currently facing science (e.g., direct replication, prioritizing ecological validity). We also outline a range of unique and perhaps unanticipated obstacles and provide practical recommendations to overcome them.},
  note = {PubMed query source: Ying Wu}
}

@article{Wang202335969565,
  title = {Stimulus-Stimulus Transfer Based on Time-Frequency-Joint Representation in SSVEP-Based BCIs.},
  author = {Wang, Z and Wong, CM and Rosa, A and Qian, T and Jung, TP and Wan, F},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2023},
  doi = {10.1109/TBME.2022.3198639},
  pmid = {35969565},
  url = {https://pubmed.ncbi.nlm.nih.gov/35969565/},
  abstract = {Brain-computer interfaces (BCIs) based on steady-state visual evoked potential (SSVEP) require extensive and costly calibration to achieve high performance. Using transfer learning to re-use existing calibration data from old stimuli is a promising strategy, but finding commonalities in the SSVEP signals across different stimuli remains a challenge. This study presents a new perspective, namely time-frequency-joint representation, in which SSVEP signals corresponding to different stimuli can be synchronized, and thus can emphasize common components. According to this time-frequency-joint representation, an adaptive decomposition technique based on the multi-channel adaptive Fourier decomposition (MAFD) is proposed to adaptively decompose SSVEP signals of different stimuli simultaneously. Then, common components can be identified and transferred across stimuli. A simulation study on public SSVEP datasets demonstrates that the proposed stimulus-stimulus transfer method has the ability to extract and transfer these common components across stimuli. By using calibration data from eight source stimuli, the proposed stimulus-stimulus transfer method can generate SSVEP templates of other 32 target stimuli. It boosts the ITR of the stimulus-stimulus transfer based recognition method from 95.966 bits/min to 123.684 bits/min. By extracting and transfer common components across stimuli in the proposed time-frequency-joint representation, the proposed stimulus-stimulus transfer method produces good classification performance without requiring calibration data of target stimuli. This study provides a synchronization standpoint to analyze and model SSVEP signals. In addition, the proposed stimulus-stimulus method shortens the calibration time and thus improve comfort, which could facilitate real-world applications of SSVEP-based BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202337262122,
  title = {Stimulus Design for Visual Evoked Potential Based Brain-Computer Interfaces.},
  author = {Xu, H and Hsu, SH and Nakanishi, M and Lin, Y and Jung, TP and Cauwenberghs, G},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2023},
  doi = {10.1109/TNSRE.2023.3280081},
  pmid = {37262122},
  url = {https://pubmed.ncbi.nlm.nih.gov/37262122/},
  abstract = {Visual stimuli design plays an important role in brain-computer interfaces (BCIs) based on visual evoked potentials (VEPs). Variations in stimulus parameters have been shown to affect both decoding accuracy and subjective perception experience, implying the need for a trade-off in design. In this study, we comprehensively and systematically compared various combinations of amplitude contrast and spectral content parameters in the stimulus design to quantify their impact on decoding performance and subject comfort. Specifically, three parameters were investigated: 1) contrast level, 2) temporal pattern (periodic steady-state or pseudo-random code-modulated), and 3) frequency range. We collected electroencephalogram (EEG) data and subjective perception ratings from ten subjects and evaluated the decoding accuracy and subject comfort rating for different combinations of the stimulus parameters. Our results indicate that while high-frequency steady-state VEP (SSVEP) stimuli were rated the most comfortable, they also had the lowest decoding accuracy. Conversely, low-frequency SSVEP stimuli were rated the least comfortable but had the highest decoding accuracy. Standard and high-frequency M-sequence code-modulated VEPs (c-VEPs) produced intermediates between the two. We observed a consistent trade-off relationship between decoding accuracy and subjective comfort level across all parameters. Based on our findings, we offer c-VEP as a preferable stimulus for achieving reliable decoding accuracy while maintaining a reasonable level of comfortability.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Horvth202337782987,
  title = {Psychometric properties of the Alcohol Use Disorders Identification Test (AUDIT) across cross-cultural subgroups, genders, and sexual orientations: Findings from the International Sex Survey (ISS).},
  author = {Horváth, Z and Nagy, L and Koós, M and Kraus, SW and Demetrovics, Z and Potenza, MN and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, R and Fernandez, DP and Fujiwara, H and Fernandez, EF and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, SK and Lewczuk, K and Lin, CY and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University’s research team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and Scanavino, MT and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre-Leirós, V and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Tsai, MC and Ünsal, BC and Vaillancourt-Morel, MP and Van Hout, MC and Bőthe, B},
  journal = {Comprehensive psychiatry},
  year = {2023},
  doi = {10.1016/j.comppsych.2023.152427},
  pmid = {37782987},
  url = {https://pubmed.ncbi.nlm.nih.gov/37782987/},
  abstract = {Despite being a widely used screening questionnaire, there is no consensus on the most appropriate measurement model for the Alcohol Use Disorders Identification Test (AUDIT). Furthermore, there have been limited studies on its measurement invariance across cross-cultural subgroups, genders, and sexual orientations. The present study aimed to examine the fit of different measurement models for the AUDIT and its measurement invariance across a wide range of subgroups by country, language, gender, and sexual orientation. Responses concerning past-year alcohol use from the participants of the cross-sectional International Sex Survey were considered (N = 62,943; M age : 32.73; SD = 12.59). Confirmatory factor analysis, as well as measurement invariance tests were performed for 21 countries, 14 languages, three genders, and four sexual-orientation subgroups that met the minimum sample size requirement for inclusion in these analyses. A two-factor model with factors describing 'alcohol use' (items 1-3) and 'alcohol problems' (items 4-10) showed the best model fit across countries, languages, genders, and sexual orientations. For the former two, scalar and latent mean levels of invariance were reached considering different criteria. For gender and sexual orientation, a latent mean level of invariance was reached. In line with the two-factor model, the calculation of separate alcohol-use and alcohol-problem scores is recommended when using the AUDIT. The high levels of measurement invariance achieved for the AUDIT support its use in cross-cultural research, capable also of meaningful comparisons among genders and sexual orientations.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Nakanishi202337022841,
  title = {Novel Moving Steady-State Visual Evoked Potential Stimulus to Assess Afferent and Efferent Dysfunction in Multiple Sclerosis.},
  author = {Nakanishi, M and Miner, A and Jung, TP and Graves, J},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2023},
  doi = {10.1109/TNSRE.2023.3243554},
  pmid = {37022841},
  url = {https://pubmed.ncbi.nlm.nih.gov/37022841/},
  abstract = {Afferent and efferent visual dysfunction are prominent features of multiple sclerosis (MS). Visual outcomes have been shown to be robust biomarkers of the overall disease state. Unfortunately, precise measurement of afferent and efferent function is typically limited to tertiary care facilities, which have the equipment and analytical capacity to make these measurements, and even then, only a few centers can accurately quantify both afferent and efferent dysfunction. These measurements are currently unavailable in acute care facilities (ER, hospital floors). We aimed to develop a moving multifocal steady-state visual evoked potential (mfSSVEP) stimulus to simultaneously assess afferent and efferent dysfunction in MS for application on a mobile platform. The brain-computer interface (BCI) platform consists of a head-mounted virtual-reality headset with electroencephalogram (EEG) and electrooculogram (EOG) sensors. To evaluate the platform, we recruited consecutive patients who met the 2017 MS McDonald diagnostic criteria and healthy controls for a pilot cross-sectional study. Nine MS patients (mean age 32.7 years, SD 4.33) and ten healthy controls (24.9 years, SD 7.2) completed the research protocol. The afferent measures based on mfSSVEPs showed a significant difference between the groups (signal-to-noise ratio of mfSSVEPs for controls: 2.50 ± 0.72 vs. MS: 2.04 ± 0.47) after controlling for age (p = 0.049). In addition, the moving stimulus successfully induced smooth pursuit movement that can be measured by the EOG signals. There was a trend for worse smooth pursuit tracking in cases vs. controls, but this did not reach nominal statistical significance in this small pilot sample. This study introduces a novel moving mfSSVEP stimulus for a BCI platform to evaluate neurologic visual function. The moving stimulus showed a reliable capability to assess both afferent and efferent visual functions simultaneously.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{OKeeffe202337022022,
  title = {Non-Parametric Functional Muscle Network as a Robust Biomarker of Fatigue.},
  author = {O'Keeffe, R and Shirazi, SY and Yang, J and Mehrdad, S and Rao, S and Atashzar, SF},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2023},
  doi = {10.1109/JBHI.2023.3234960},
  pmid = {37022022},
  url = {https://pubmed.ncbi.nlm.nih.gov/37022022/},
  abstract = {Characterization of fatigue using surface electromyography (sEMG) data has been motivated for rehabilitation and injury-preventative technologies. Current sEMG-based models of fatigue are limited due to (a) linear and parametric assumptions, (b) lack of a holistic neurophysiological view, and (c) complex and heterogeneous responses. This paper proposes and validates a data-driven non-parametric functional muscle network analysis to reliably characterize fatigue-related changes in synergistic muscle coordination and distribution of neural drive at the peripheral level. The proposed approach was tested on data collected in this study from the lower extremities of 26 asymptomatic volunteers (13 subjects were assigned to the fatigue intervention group, and 13 age/gender-matched subjects were assigned to the control group). Volitional fatigue was induced in the intervention group by moderate-intensity unilateral leg press exercises. The proposed non-parametric functional muscle network demonstrated a consistent decrease in connectivity after the fatigue intervention, as indicated by network degree, weighted clustering coefficient (WCC), and global efficiency. The graph metrics displayed consistent and significant decreases at the group level, individual subject level, and individual muscle level. For the first time, this paper proposed a non-parametric functional muscle network and highlighted the corresponding potential as a sensitive biomarker of fatigue with superior performance to conventional spectrotemporal measures.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Li202337250403,
  title = {Modulation of rhythmic visual stimulation on left-right attentional asymmetry.},
  author = {Li, R and Xu, M and You, J and Zhou, X and Meng, J and Xiao, X and Jung, TP and Ming, D},
  journal = {Frontiers in neuroscience},
  year = {2023},
  doi = {10.3389/fnins.2023.1156890},
  pmid = {37250403},
  url = {https://pubmed.ncbi.nlm.nih.gov/37250403/},
  abstract = {The rhythmic visual stimulation (RVS)-induced oscillatory brain responses, namely steady-state visual evoked potentials (SSVEPs), have been widely used as a biomarker in studies of neural processing based on the assumption that they would not affect cognition. However, recent studies have suggested that the generation of SSVEPs might be attributed to neural entrainment and thus could impact brain functions. But their neural and behavioral effects are yet to be explored. No study has reported the SSVEP influence on functional cerebral asymmetry (FCA). We propose a novel lateralized visual discrimination paradigm to test the SSVEP effects on visuospatial selective attention by FCA analyses. Thirty-eight participants covertly shifted their attention to a target triangle appearing in either the lower-left or -right visual field (LVF or RVF), and judged its orientation. Meanwhile, participants were exposed to a series of task-independent RVSs at different frequencies, including 0 (no RVS), 10, 15, and 40-Hz. As a result, it showed that target discrimination accuracy and reaction time (RT) varied significantly across RVS frequency. Furthermore, attentional asymmetries differed for the 40-Hz condition relative to the 10-Hz condition as indexed by enhanced RT bias to the right visual field, and larger Pd EEG component for attentional suppression. Our results demonstrated that RVSs had frequency-specific effects on left-right attentional asymmetries in both behavior and neural activities. These findings provided new insights into the functional role of SSVEP on FCAs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{OKeeffe202336711641,
  title = {Linear versus Nonlinear Muscle Networks: A Case Study to Decode Hidden Synergistic Patterns During Dynamic Lower-limb Tasks.},
  author = {O'Keeffe, R and Rathod, V and Shirazi, SY and Mehrdad, S and Edwards, A and Rao, S and Atashzar, SF},
  journal = {bioRxiv : the preprint server for biology},
  year = {2023},
  doi = {10.1101/2023.01.15.524160},
  pmid = {36711641},
  url = {https://pubmed.ncbi.nlm.nih.gov/36711641/},
  abstract = {This paper, for the first time, compares the behaviors of nonlinear versus linear muscle networks in decoding hidden peripheral synergistic neural patterns during dynamic functional tasks. In this paper, we report a case study during which one healthy subject conducts a series of four lower limb repetitive tasks. Specifically, the paper focuses on tasks that involve the right knee joint, including walking, sit-tostand, stepping, and drop-jump. Twelve muscles were recorded using the Delsys Trigno system. The linear muscle network was generated using coherence analysis, and the nonlinear network was generated using Spearman's correlation. The results show that the degree, clustering coefficient, and global efficiency of the muscle network have the highest value among tasks in the linear domain for the walking task, while a low linear synergistic network behavior for the sit-to-stand is observed. On the other hand, the results show that the nonlinear functional muscle network decodes high connectivity (degree) and clustering coefficient and efficiency for the sit-tostand when compared with other tasks. We have also developed a two-dimensional functional connectivity plane composed of linear and nonlinear features and shown that it can span the lower-limb dynamic task space. The results of this paper for the first time highlight the importance of observing both linear and nonlinear connectivity patterns, especially for complex dynamic tasks. It should also be noted that through a simultaneous EEG recording (using BrainVision System), we have shown that, indeed, cortical activity may indirectly explain highly-connected nonlinear muscle network for the sit-to-stand task, highlighting the importance of nonlinear muscle network as a neurophysiological window of observation beyond the periphery.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Wu202337306851,
  title = {Launching Your VR Neuroscience Laboratory.},
  author = {Wu, YC and Maymon, C and Paden, J and Liu, W},
  journal = {Current topics in behavioral neurosciences},
  year = {2023},
  doi = {10.1007/7854_2023_420},
  pmid = {37306851},
  url = {https://pubmed.ncbi.nlm.nih.gov/37306851/},
  abstract = {The proliferation and refinement of affordable virtual reality (VR) technologies and wearable sensors have opened new frontiers in cognitive and behavioral neuroscience. This chapter offers a broad overview of VR for anyone interested in leveraging it as a research tool. In the first section, it examines the fundamental functionalities of VR and outlines important considerations that inform the development of immersive content that stimulates the senses. In the second section, the focus of the discussion shifts to the implementation of VR in the context of the neuroscience lab. Practical advice is offered on adapting commercial, off-the-shelf devices to a researcher's specific purposes. Further, methods are explored for recording, synchronizing, and fusing heterogeneous forms of data obtained through the VR system or add-on sensors, as well as for labeling events and capturing game play. The reader should come away with an understanding of fundamental considerations that need to be addressed in order to launch a successful VR neuroscience research program.},
  note = {PubMed query source: Ying Wu}
}

@article{Wang202337611567,
  title = {Investigating EEG-based cross-session and cross-task vigilance estimation in BCI systems.},
  author = {Wang, K and Qiu, S and Wei, W and Yi, W and He, H and Xu, M and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/acf345},
  pmid = {37611567},
  url = {https://pubmed.ncbi.nlm.nih.gov/37611567/},
  abstract = {Objective . The state of vigilance is crucial for effective performance in brain-computer interface (BCI) tasks, and therefore, it is essential to investigate vigilance levels in BCI tasks. Despite this, most studies have focused on vigilance levels in driving tasks rather than on BCI tasks, and the electroencephalogram (EEG) patterns of vigilance states in different BCI tasks remain unclear. This study aimed to identify similarities and differences in EEG patterns and performances of vigilance estimation in different BCI tasks and sessions. Approach. To achieve this, we built a steady-state visual evoked potential-based BCI system and a rapid serial visual presentation-based BCI system and recruited 18 participants to carry out four BCI experimental sessions over four days. Main results . Our findings demonstrate that specific neural patterns for high and low vigilance levels are relatively stable across sessions. Differential entropy features significantly differ between different vigilance levels in all frequency bands and between BCI tasks in the delta and theta frequency bands, with the theta frequency band features playing a critical role in vigilance estimation. Additionally, prefrontal, temporal, and occipital regions are more relevant to the vigilance state in BCI tasks. Our results suggest that cross-session vigilance estimation is more accurate than cross-task estimation. Significance. Our study clarifies the underlying mechanisms of vigilance state in two BCI tasks and provides a foundation for further research in vigilance estimation in BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Pellegrini202337307866,
  title = {Identifying good practices for detecting inter-regional linear functional connectivity from EEG.},
  author = {Pellegrini, F and Delorme, A and Nikulin, V and Haufe, S},
  journal = {NeuroImage},
  year = {2023},
  doi = {10.1016/j.neuroimage.2023.120218},
  pmid = {37307866},
  url = {https://pubmed.ncbi.nlm.nih.gov/37307866/},
  abstract = {Aggregating voxel-level statistical dependencies between multivariate time series is an important intermediate step when characterising functional connectivity (FC) between larger brain regions. However, there are numerous ways in which voxel-level data can be aggregated into inter-regional FC, and the advantages of each of these approaches are currently unclear. In this study we generate ground-truth data and compare the performances of various pipelines that estimate directed and undirected linear phase-to-phase FC between regions. We test the ability of several existing and novel FC analysis pipelines to identify the true regions within which connectivity was simulated. We test various inverse modelling algorithms, strategies to aggregate time series within regions, and connectivity metrics. Furthermore, we investigate the influence of the number of interactions, the signal-to-noise ratio, the noise mix, the interaction time delay, and the number of active sources per region on the ability of detecting phase-to-phase FC. Throughout all simulated scenarios, lowest performance is obtained with pipelines involving the absolute value of coherency. Further, the combination of dynamic imaging of coherent sources (DICS) beamforming with directed FC metrics that aggregate information across multiple frequencies leads to unsatisfactory results. Pipelines that show promising results with our simulated pseudo-EEG data involve the following steps: (1) Source projection using the linearly-constrained minimum variance (LCMV) beamformer. (2) Principal component analysis (PCA) using the same fixed number of components within every region. (3) Calculation of the multivariate interaction measure (MIM) for every region pair to assess undirected phase-to-phase FC, or calculation of time-reversed Granger Causality (TRGC) to assess directed phase-to-phase FC. We formulate recommendations based on these results that may increase the validity of future experimental connectivity studies. We further introduce the free ROIconnect plugin for the EEGLAB toolbox that includes the recommended methods and pipelines that are presented here. We show an exemplary application of the best performing pipeline to the analysis of EEG data recorded during motor imagery.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Glica202336763943,
  title = {Hypo- or hyperfunction? Differential relationships between compulsive sexual behavior disorder facets and sexual health.},
  author = {Glica, A and Wizła, M and Gola, M and Lewczuk, K},
  journal = {The journal of sexual medicine},
  year = {2023},
  doi = {10.1093/jsxmed/qdac035},
  pmid = {36763943},
  url = {https://pubmed.ncbi.nlm.nih.gov/36763943/},
  abstract = {Previous studies linking compulsive sexual behavior disorder (CSBD) and sexual health have shown mixed results, which could be due to the fact that different CSBD facets may have differential relationships with sexual functioning. As CSBD is a multidimensional disorder, we wanted to investigate whether distinct CSBD domains are differentially related to sexual health. Two online studies were conducted-the first on a convenience sample (812 Polish participants; mean [SD] age, 22.07 [5.91] years) and a replication study on a representative sample of Polish adults (n = 1526; 43.02 [14.37]). Hierarchical regression was employed with sexual functioning as a predicted variable and CSBD symptoms as predictors. The Compulsive Sexual Behavior Disorder Scale was used to assess CSBD symptoms, and the Arizona Sexual Experience Scale was used to measure sexual dysfunction. In study 1, CSBD salience (β = -.20, P < .001) predicted hyperfunction (ie, stronger sex drive, easier sexual arousal, easier vaginal lubrication/penile erection, easier ability to reach an orgasm, and more satisfying orgasms). Yet, CSBD negative consequences (β = .15, P = .001) and dissatisfaction (β = .22, P < .001) predicted hypofunction (ie, weaker sex drive, more difficulties in sexual arousal, greater difficulties in vaginal lubrication/penile erection, less ability to reach an orgasm, and less satisfying orgasms). Similar results were found in study 2: salience (β = -.26, P < .001) and relapse (β = -.11, P = .004) predicted hyperfunction, while negative consequences (β = .12, P < .001) and dissatisfaction (β = .12, P < .001) predicted hypofunction. Our results stress the importance of assessing the severity of each group of symptoms in patients with CSBD to better understand possible difficulties in their sexual functioning. Our studies are the first to evaluate the effects of each CSBD domain on sexual health. We also replicated results obtained from a convenience sample on a representative sample. The cross-sectional design of the current studies does not allow causal relations to be tested, so future longitudinal research should be carried out. We also gathered data from a general population-thus, it is important to replicate these results on patients diagnosed with CSBD. Our research points out the differential impact of CSBD domains on sexual health: salience and relapse are related to sexual hyperfunction, while negative consequences and dissatisfaction to hypofunction.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Chou202336842997,
  title = {Human Brain Dynamics and Coordination Reflect the Task Difficulty of Optical Image Relational Reasoning.},
  author = {Chou, WC and She, HC and Jung, TP},
  journal = {International journal of neural systems},
  year = {2023},
  doi = {10.1142/S0129065723500181},
  pmid = {36842997},
  url = {https://pubmed.ncbi.nlm.nih.gov/36842997/},
  abstract = {Despite advances in neuroscience, the mechanisms by which human brain resolve optical image formation through relational reasoning remain unclear, particularly its relationships with task difficulty. Therefore, this study explores the underlying brain dynamics involved in optical image formation tasks at various difficulty levels, including those with a single convex lens and a single mirror. Compared to single convex lens relational reasoning with high task difficulty, the single mirror relational reasoning exhibited significantly higher response accuracy and shorter latency. As compared to single mirror tasks, single convex tasks exhibited greater frontal midline theta augmentation and right parietal alpha suppression during phase I and earlier phase II, and augmentation of frontal midline theta, right parietal-occipital alpha, and left mu alpha suppression during late phase II. Moreover, the frontal midline theta power in late phase II predicts the likelihood of solving single convex tasks the best, while the parietal alpha power in phase I is most predictive. In addition, frontal midline theta power exhibited stronger synchronization with right parietal alpha, right occipital alpha, and mu alpha power when solving single convex tasks than single mirror tasks. In summary, having stronger brain dynamics and coordination is vital for achieving optical image formation with greater difficulty.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Binkowska202337720591,
  title = {Evaluating the effectiveness of mobile app-based self-guided psychological intervention to reduce craving and lapse risk in problematic substance use and behaviors: Protocol for a randomized control trial in the general population.},
  author = {Binkowska, AA and Obarska, K and Marcowski, P and Szymczak, K and Lewczuk, K and Sollich, K and Banaszak, M and Woronowicz, B and Nowicka, M and Skorko, M and Gola, M},
  journal = {Contemporary clinical trials communications},
  year = {2023},
  doi = {10.1016/j.conctc.2023.101180},
  pmid = {37720591},
  url = {https://pubmed.ncbi.nlm.nih.gov/37720591/},
  abstract = {The prevalence of substance and behavioral addiction is estimated between 10 and 15% of the global population and remains a severe public health concern. Moreover, addiction treatment has several barriers, such as a lack of access to professional treatment or stigmatization. Mobile health interventions emerge as a promising solution. This two-armed randomized controlled trial (RCT) aims to assess the efficacy of a mobile app-based self-guided psychological intervention delivered via a smartphone app (Nałogometr) in reducing craving and lapse risk in problematic behaviors and substance use compared to a control condition. Participant recruitment and data collection will start in June 2022 and end in September 2022. Due to the nature of the study, i.e., a nationwide study of problematic substance use and behaviors, we will aim to recruit all individuals willing to participate. The four-week intervention condition includes short-term and long-term modules based mainly on mindfulness and cognitive behavioral therapy. Longitudinal data on several variables related to craving and lapse risk are collected daily using ecological momentary assessment (EMA). The primary outcomes of interest will be the self-reported number of lapses and craving level in daily EMA. Moreover, a questionnaire battery assessment is administered at baseline in the first week following onboarding, after five weeks, and after six months. The secondary outcome measures will include the severity of problematic substance use or behaviors, anxiety and depression, and life satisfaction. Results will be submitted for publication in peer-reviewed journals. [ https://clinicaltrials.gov/], identifier [NCT054 34,429].},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wahbeh202337301570,
  title = {Evaluating brain spectral and connectivity differences between silent mind-wandering and trance states.},
  author = {Wahbeh, H and Cannard, C and Kriegsman, M and Delorme, A},
  journal = {Progress in brain research},
  year = {2023},
  doi = {10.1016/bs.pbr.2022.12.011},
  pmid = {37301570},
  url = {https://pubmed.ncbi.nlm.nih.gov/37301570/},
  abstract = {Trance is an altered state of consciousness characterized by alterations in cognition. In general, trance states induce mental silence (i.e., cognitive thought reduction), and mental silence can induce trance states. Conversely, mind-wandering is the mind's propensity to stray its attention away from the task at hand and toward content irrelevant to the current moment, and its main component is inner speech. Building on the previous literature on mental silence and trance states and incorporating inverse source reconstruction advances, the study's objectives were to evaluate differences between trance and mind-wandering states using: (1) electroencephalography (EEG) power spectra at the electrode level, (2) power spectra at the area level (source reconstructed signal), and (3) EEG functional connectivity between these areas (i.e., how they interact). The relationship between subjective trance depths ratings and whole-brain connectivity during trance was also evaluated. Spectral analyses revealed increased delta and theta power in the frontal region and increased gamma in the centro-parietal region during mind-wandering, whereas trance showed increased beta and gamma power in the frontal region. Power spectra at the area level and pairwise comparisons of the connectivity between these areas demonstrated no significant difference between the two states. However, subjective trance depth ratings were inversely correlated with whole-brain connectivity in all frequency bands (i.e., deeper trance is associated with less large-scale connectivity). Trance allows one to enter mentally silent states and explore their neurophenomenological processes. Limitations and future directions are discussed.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wong202337022824,
  title = {Enhancing Detection of Multi-Frequency-Modulated SSVEP Using Phase Difference Constrained Canonical Correlation Analysis.},
  author = {Wong, CM and Wang, Z and Wang, B and Rosa, A and Jung, TP and Wan, F},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2023},
  doi = {10.1109/TNSRE.2023.3243290},
  pmid = {37022824},
  url = {https://pubmed.ncbi.nlm.nih.gov/37022824/},
  abstract = {Multi-frequency-modulated visual stimulation scheme has been shown effective for the steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) recently, especially in increasing the visual target number with less stimulus frequencies and mitigating the visual fatigue. However, the existing calibration-free recognition algorithms based on the traditional canonical correlation analysis (CCA) cannot provide the merited performance. To improve the recognition performance, this study proposes a phase difference constrained CCA (pdCCA), which assumes that the multi-frequency-modulated SSVEPs share a common spatial filter over different frequencies and have a specified phase difference. Specifically, during the CCA computation, the phase differences of the spatially filtered SSVEPs are constrained using the temporal concatenation of the sine-cosine reference signals with the pre-defined initial phases. We evaluate the performance of the proposed pdCCA-based method on three representative multi-frequency-modulated visual stimulation paradigms (i.e., based on the multi-frequency sequential coding, the dual-frequency, and the amplitude modulation). The evaluation results on four SSVEP datasets (Dataset Ia, Ib, II, and III) show that the pdCCA-based method can significantly outperform the current CCA method in terms of recognition accuracy. It improves the accuracy by 22.09% in Dataset Ia, 20.86% in Dataset Ib, 8.61% in Dataset II, and 25.85% in Dataset III. The pdCCA-based method, which actively controls the phase difference of the multi-frequency-modulated SSVEPs after spatial filtering, is a new calibration-free method for multi-frequency-modulated SSVEP-based BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Ng202336717762,
  title = {Enhanced electroencephalography effective connectivity in frontal low-gamma band correlates of emotional regulation after mindfulness training.},
  author = {Ng, HH and Wu, CW and Huang, FY and Huang, CM and Hsu, CF and Chao, YP and Jung, TP and Chuang, CH},
  journal = {Journal of neuroscience research},
  year = {2023},
  doi = {10.1002/jnr.25168},
  pmid = {36717762},
  url = {https://pubmed.ncbi.nlm.nih.gov/36717762/},
  abstract = {Practicing mindfulness, focusing attention on the internal and external experiences occurring in the present moment with open and nonjudgement stance, can lead to the development of emotional regulation skills. Yet, the effective connectivity of brain regions during mindfulness has been largely unexplored. Studies have shown that mindfulness practice promotes functional connectivity in practitioners, potentially due to improved emotional regulation abilities and increased connectivity in the lateral prefrontal areas. To examine the changes in effective connectivity due to mindfulness training, we analyzed electroencephalogram (EEG) signals taken before and after mindfulness training, focusing on training-related effective connectivity changes in the frontal area. The mindfulness training group participated in an 8-week mindfulness-based stress reduction (MBSR) program. The control group did not take part. Regardless of the specific mindfulness practice used, low-gamma band effective connectivity increased globally after the mindfulness training. High-beta band effective connectivity increased globally only during Breathing. Moreover, relatively higher outgoing effective connectivity strength was seen during Resting and Breathing and Body-scan. By analyzing the changes in outgoing and incoming connectivity edges, both F7 and F8 exhibited strong parietal connectivity during Resting and Breathing. Multiple regression analysis revealed that the changes in effective connectivity of the right lateral prefrontal area predicted mindfulness and emotional regulation abilities. These results partially support the theory that the lateral prefrontal areas have top-down modulatory control, as these areas have high outflow effective connectivity, implying that mindfulness training cultivates better emotional regulation.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202337965214,
  title = {Editorial: The application of artificial intelligence in brain-computer interface and neural system rehabilitation.},
  author = {Xu, F and Ming, D and Jung, TP and Xu, P and Xu, M},
  journal = {Frontiers in neuroscience},
  year = {2023},
  doi = {10.3389/fnins.2023.1290961},
  pmid = {37965214},
  url = {https://pubmed.ncbi.nlm.nih.gov/37965214/},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hunt202338495476,
  title = {Editorial: Electromagnetic field theories of consciousness: opportunities and obstacles.},
  author = {Hunt, T and Jones, M and McFadden, J and Delorme, A and Hales, CG and Ericson, M and Schooler, J},
  journal = {Frontiers in human neuroscience},
  year = {2023},
  doi = {10.3389/fnhum.2023.1342634},
  pmid = {38495476},
  url = {https://pubmed.ncbi.nlm.nih.gov/38495476/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Papo202337779613,
  title = {Editorial: Advances in brain dynamics in the healthy and psychiatric disorders.},
  author = {Papo, D and Bucolo, M and Dimitriadis, SI and Onton, JA and Philippu, A and Shannahoff-Khalsa, D},
  journal = {Frontiers in psychiatry},
  year = {2023},
  doi = {10.3389/fpsyt.2023.1284670},
  pmid = {37779613},
  url = {https://pubmed.ncbi.nlm.nih.gov/37779613/},
  note = {PubMed query source: Julie Onton}
}

@article{Meng202337145943,
  title = {EEG-Based Brain-Computer Interfaces are Vulnerable to Backdoor Attacks.},
  author = {Meng, L and Jiang, X and Huang, J and Zeng, Z and Yu, S and Jung, TP and Lin, CT and Chavarriaga, R and Wu, D},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2023},
  doi = {10.1109/TNSRE.2023.3273214},
  pmid = {37145943},
  url = {https://pubmed.ncbi.nlm.nih.gov/37145943/},
  abstract = {Research and development of electroencephalogram (EEG) based brain-computer interfaces (BCIs) have advanced rapidly, partly due to deeper understanding of the brain and wide adoption of sophisticated machine learning approaches for decoding the EEG signals. However, recent studies have shown that machine learning algorithms are vulnerable to adversarial attacks. This paper proposes to use narrow period pulse for poisoning attack of EEG-based BCIs, which makes adversarial attacks much easier to implement. One can create dangerous backdoors in the machine learning model by injecting poisoning samples into the training set. Test samples with the backdoor key will then be classified into the target class specified by the attacker. What most distinguishes our approach from previous ones is that the backdoor key does not need to be synchronized with the EEG trials, making it very easy to implement. The effectiveness and robustness of the backdoor attack approach is demonstrated, highlighting a critical security concern for EEG-based BCIs and calling for urgent attention to address it.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Delorme202336759667,
  title = {EEG is better left alone.},
  author = {Delorme, A},
  journal = {Scientific reports},
  year = {2023},
  doi = {10.1038/s41598-023-27528-0},
  pmid = {36759667},
  url = {https://pubmed.ncbi.nlm.nih.gov/36759667/},
  abstract = {Automated preprocessing methods are critically needed to process the large publicly-available EEG databases, but the optimal approach remains unknown because we lack data quality metrics to compare them. Here, we designed a simple yet robust EEG data quality metric assessing the percentage of significant channels between two experimental conditions within a 100 ms post-stimulus time range. Because of volume conduction in EEG, given no noise, most brain-evoked related potentials (ERP) should be visible on every single channel. Using three publicly available collections of EEG data, we showed that, with the exceptions of high-pass filtering and bad channel interpolation, automated data corrections had no effect on or significantly decreased the percentage of significant channels. Referencing and advanced baseline removal methods were significantly detrimental to performance. Rejecting bad data segments or trials could not compensate for the loss in statistical power. Automated Independent Component Analysis rejection of eyes and muscles failed to increase performance reliably. We compared optimized pipelines for preprocessing EEG data maximizing ERP significance using the leading open-source EEG software: EEGLAB, FieldTrip, MNE, and Brainstorm. Only one pipeline performed significantly better than high-pass filtering the data.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{He202337022001,
  title = {Diversity and Suitability of the State-of-the-Art Wearable and Wireless EEG Systems Review.},
  author = {He, C and Chen, YY and Phang, CR and Stevenson, C and Chen, IP and Jung, TP and Ko, LW},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2023},
  doi = {10.1109/JBHI.2023.3239053},
  pmid = {37022001},
  url = {https://pubmed.ncbi.nlm.nih.gov/37022001/},
  abstract = {Wireless electroencephalography (EEG) systems have been attracting increasing attention in recent times. Both the number of articles discussing wireless EEG and their proportion relative to general EEG publications have increased over years. These trends indicate that wireless EEG systems could be more accessible to researchers and the research community has recognized the potential of wireless EEG systems. To explore the development and diverse applications of wireless EEG systems, this review highlights the trends in wearable and wireless EEG systems over the past decade and compares the specifications and research applications of the major wireless systems marketed by 16 companies. For each product, five parameters (number of channels, sampling rate, cost, battery life, and resolution) were assessed for comparison. Currently, these wearable and portable wireless EEG systems have three main application areas: consumer, clinical, and research. To address this multitude of options, the article also discussed the thought process to find a suitable device that meets personalization and use cases specificities. These investigations suggest that low-price and convenience are key factors for consumer applications, wireless EEG systems with FDA or CE-certification may be more suitable for clinical settings, and devices that provide raw EEG data with high-density channels are important for laboratory research. This article presents an overview of the current state of the wireless EEG systems specifications and possible applications and serves as a guide point as it is expected that more influential and novel research will cyclically promote the development of such EEG systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wen202337279134,
  title = {Design and Test of Spatial Cognitive Training and Evaluation System Based on Virtual Reality Head-Mounted Display With EEG Recording.},
  author = {Wen, D and Yuan, J and Li, J and Sun, Y and Wang, X and Shi, R and Wan, X and Zhou, Y and Song, H and Dong, X and Xu, F and Lan, X and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2023},
  doi = {10.1109/TNSRE.2023.3283328},
  pmid = {37279134},
  url = {https://pubmed.ncbi.nlm.nih.gov/37279134/},
  abstract = {The field of spatial cognitive training and evaluation has rapidly evolved. However, the low learning motivation and engagement of the subjects hinder the widespread use of spatial cognitive training. This study designed a home-based spatial cognitive training and evaluation system (SCTES), which aimed to train subjects on spatial cognitive tasks for 20 days, and compared the brain activities before and after the training. This study also evaluated the feasibility of using a portable all-in-one prototype for cognitive training that combined a virtual reality (VR) head-mounted display with high-quality electroencephalogram (EEG) recording. During the course of training, the length of the navigation path and the distance between the starting position and the platform position revealed significant behavioral differences. In the testing sessions, the subjects showed significant behavioral differences in the time it took to complete the test task before and after training. After only four days of training, the subjects demonstrated significant differences in the Granger causality analysis (GCA) characteristics of brain regions in the δ , θ , α 1  , β 2  , and γ frequency bands of the EEG, as well as significant differences in the GCA of the EEG in the β 1  , β 2  , and γ frequency bands between the two test sessions. The proposed SCTES used a compact and all-in-one form factor to train and evaluate spatial cognition and collect EEG signals and behavioral data simultaneously. The recorded EEG data can be used to quantitatively assess the efficacy of spatial training in patients with spatial cognitive impairments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Luo202337015587,
  title = {Data Augmentation of SSVEPs Using Source Aliasing Matrix Estimation for Brain-Computer Interfaces.},
  author = {Luo, R and Xu, M and Zhou, X and Xiao, X and Jung, TP and Ming, D},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2023},
  doi = {10.1109/TBME.2022.3227036},
  pmid = {37015587},
  url = {https://pubmed.ncbi.nlm.nih.gov/37015587/},
  abstract = {Currently, ensemble task-related component analysis (eTRCA) and task discriminative component analysis (TDCA) are the state-of-the-art algorithms for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs). However, training the BCIs requires multiple calibration trials. With insufficient calibration data, the accuracy of the BCI will degrade, or even become invalid with only one calibration trial. However, collecting a large amount of electroencephalography (EEG) data for calibration is a time-consuming and laborious process, which hinders the practical use of eTRCA and TDCA. This study proposed a novel method, namely Source Aliasing Matrix Estimation (SAME), to augment the calibration data for SSVEP-BCIs. SAME could generate artificial EEG trials with the featured SSVEPs. Its effectiveness was evaluated using two public datasets (i.e., Benchmark, BETA). When combined with SAME, both eTRCA and TDCA had significantly improved performance with a limited number of calibration data. Specifically, SAME increased the average accuracy of eTRCA and TDCA by about 12% and 3%, respectively, with as few as two calibration trials. Notably, SAME enabled eTRCA and TDCA to work well with a single calibration trial, achieving an average accuracy >90% for the Benchmark dataset and >70% for the BETA dataset with 1-second EEG. SAME is an effective method for SSVEP-BCIs to augment the calibration data, thereby significantly enhancing the performance of eTRCA and TDCA. We propose a new data-augmentation method that is compatible with the state-of-the-art algorithms of SSVEP-based BCIs. It can significantly reduce the efforts required to calibrate SSVEP-BCIs, which is promising for the development of practical BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xie202337774694,
  title = {Cross-dataset transfer learning for motor imagery signal classification via multi-task learning and pre-training.},
  author = {Xie, Y and Wang, K and Meng, J and Yue, J and Meng, L and Yi, W and Jung, TP and Xu, M and Ming, D},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/acfe9c},
  pmid = {37774694},
  url = {https://pubmed.ncbi.nlm.nih.gov/37774694/},
  abstract = {Objective. Deep learning (DL) models have been proven to be effective in decoding motor imagery (MI) signals in Electroencephalogram (EEG) data. However, DL models' success relies heavily on large amounts of training data, whereas EEG data collection is laborious and time-consuming. Recently, cross-dataset transfer learning has emerged as a promising approach to meet the data requirements of DL models. Nevertheless, transferring knowledge across datasets involving different MI tasks remains a significant challenge in cross-dataset transfer learning, limiting the full utilization of valuable data resources. This study proposes a pre-training-based cross-dataset transfer learning method inspired by Hard Parameter Sharing in multi-task learning. Different datasets with distinct MI paradigms are considered as different tasks, classified with shared feature extraction layers and individual task-specific layers to allow cross-dataset classification with one unified model. Then, Pre-training and fine-tuning are employed to transfer knowledge across datasets. We also designed four fine-tuning schemes and conducted extensive experiments on them. The results showed that compared to models without pre-training, models with pre-training achieved a maximum increase in accuracy of 7.76%. Moreover, when limited training data were available, the pre-training method significantly improved DL model's accuracy by 27.34% at most. The experiments also revealed that pre-trained models exhibit faster convergence and remarkable robustness. The training time per subject could be reduced by up to 102.83 s, and the variance of classification accuracy decreased by 75.22% at best. This study represents the first comprehensive investigation of the cross-dataset transfer learning method between two datasets with different MI tasks. The proposed pre-training method requires only minimal fine-tuning data when applying DL models to new MI paradigms, making MI-Brain-computer interface more practical and user-friendly.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Obarska202336816420,
  title = {Corrigendum: Reducing craving and lapse risk in alcohol and stimulants dependence using mobile app involving ecological momentary assessment and self-guided psychological interventions: Protocol for a randomized controlled trial.},
  author = {Obarska, K and Binkowska, AA and Marcowski, P and Szymczak, K and Lewczuk, K and Sollich, K and Banaszak, M and Woronowicz, B and Nowicka, M and Skorko, M and Gola, M},
  journal = {Frontiers in psychiatry},
  year = {2023},
  doi = {10.3389/fpsyt.2023.1146451},
  pmid = {36816420},
  url = {https://pubmed.ncbi.nlm.nih.gov/36816420/},
  abstract = {[This corrects the article DOI: 10.3389/fpsyt.2022.1011585.].},
  note = {PubMed query source: Mateusz Gola}
}

@article{Robbins202337037959,
  title = {Correction to: Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED).},
  author = {Robbins, K and Truong, D and Jones, A and Callanan, I and Makeig, S},
  journal = {Neuroinformatics},
  year = {2023},
  doi = {10.1007/s12021-023-09628-4},
  pmid = {37037959},
  url = {https://pubmed.ncbi.nlm.nih.gov/37037959/},
  note = {PubMed query source: Scott Makeig}
}

@article{Bthe202337352095,
  title = {Compulsive sexual behavior disorder in 42 countries: Insights from the International Sex Survey and introduction of standardized assessment tools.},
  author = {Bőthe, B and Koós, M and Nagy, L and Kraus, SW and Demetrovics, Z and Potenza, MN and Michaud, A and Ballester-Arnal, R and Batthyány, D and Bergeron, S and Billieux, J and Briken, P and Burkauskas, J and Cárdenas-López, G and Carvalho, J and Castro-Calvo, J and Chen, L and Ciocca, G and Corazza, O and Csako, R and Fernandez, DP and Fernandez, EF and Fournier, L and Fujiwara, H and Fuss, J and Gabrhelík, R and Gewirtz-Meydan, A and Gjoneska, B and Gola, M and Grubbs, JB and Hashim, HT and Islam, MS and Ismail, M and Jiménez-Martínez, MC and Jurin, T and Kalina, O and Klein, V and Költő, A and Lee, CT and Lee, SK and Lewczuk, K and Lin, CY and Liverpool John Moores University's research team and Lochner, C and López-Alvarado, S and Lukavská, K and Mayta-Tristán, P and Milea, I and Miller, DJ and Orosová, O and Orosz, G and Sungkyunkwan University's research team and Ponce, FP and Quintana, GR and Quintero Garzola, GC and Ramos-Diaz, J and Rigaud, K and Rousseau, A and De Tubino Scanavino, M and Schulmeyer, MK and Sharan, P and Shibata, M and Shoib, S and Sigre Leirós, VL and Sniewski, L and Spasovski, O and Steibliene, V and Stein, DJ and Strizek, J and Štulhofer, A and Ünsal, BC and Vaillancourt-Morel, MP},
  journal = {Journal of behavioral addictions},
  year = {2023},
  doi = {10.1556/2006.2023.00028},
  pmid = {37352095},
  url = {https://pubmed.ncbi.nlm.nih.gov/37352095/},
  abstract = {Despite its inclusion in the 11th revision of the International Classification of Diseases, there is a virtual paucity of high-quality scientific evidence about compulsive sexual behavior disorder (CSBD), especially in underrepresented and underserved populations. Therefore, we comprehensively examined CSBD across 42 countries, genders, and sexual orientations, and validated the original (CSBD-19) and short (CSBD-7) versions of the Compulsive Sexual Behavior Disorder Scale to provide standardized, state-of-the-art screening tools for research and clinical practice. Using data from the International Sex Survey (N = 82,243; Mage = 32.39 years, SD = 12.52), we evaluated the psychometric properties of the CSBD-19 and CSBD-7 and compared CSBD across 42 countries, three genders, eight sexual orientations, and individuals with low vs. high risk of experiencing CSBD. A total of 4.8% of the participants were at high risk of experiencing CSBD. Country- and gender-based differences were observed, while no sexual-orientation-based differences were present in CSBD levels. Only 14% of individuals with CSBD have ever sought treatment for this disorder, with an additional 33% not having sought treatment because of various reasons. Both versions of the scale demonstrated excellent validity and reliability. This study contributes to a better understanding of CSBD in underrepresented and underserved populations and facilitates its identification in diverse populations by providing freely accessible ICD-11-based screening tools in 26 languages. The findings may also serve as a crucial building block to stimulate research into evidence-based, culturally sensitive prevention and intervention strategies for CSBD that are currently missing from the literature.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Somon202336106765,
  title = {Brain mechanisms of automated conflict avoidance simulator supervision.},
  author = {Somon, B and Campagne, A and Delorme, A and Berberian, B},
  journal = {Psychophysiology},
  year = {2023},
  doi = {10.1111/psyp.14171},
  pmid = {36106765},
  url = {https://pubmed.ncbi.nlm.nih.gov/36106765/},
  abstract = {Supervision of automated systems is an ubiquitous aspect of most of our everyday life activities which is even more necessary in high risk industries (aeronautics, power plants, etc.). Performance monitoring related to our own error making has been widely studied. Here we propose to assess the neurofunctional correlates of system error detection. We used an aviation-based conflict avoidance simulator with a 40% error-rate and recorded the electroencephalographic activity of participants while they were supervising it. Neural dynamics related to the supervision of system's correct and erroneous responses were assessed in the time and time-frequency domains to address the dynamics of the error detection process in this environment. Two levels of perceptual difficulty were introduced to assess their effect on system's error detection-related evoked activity. Using a robust cluster-based permutation test, we observed a lower widespread evoked activity in the time domain for errors compared to correct responses detection, as well as a higher theta-band activity in the time-frequency domain dissociating the detection of erroneous from that of correct system responses. We also showed a significant effect of difficulty on time-domain evoked activity, and of the phase of the experiment on spectral activity: a decrease in early theta and alpha at the end of the experiment, as well as interaction effects in theta and alpha frequency bands. These results improve our understanding of the brain dynamics of performance monitoring activity in closer-to-real-life settings and are a promising avenue for the detection of error-related components in ecological and dynamic tasks.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Grubbs202336913189,
  title = {Assessing compulsive sexual behavior disorder: The development and international validation of the compulsive sexual behavior disorder-diagnostic inventory (CSBD-DI).},
  author = {Grubbs, JB and Reid, RC and Bőthe, B and Demetrovics, Z and Coleman, E and Gleason, N and Miner, MH and Fuss, J and Klein, V and Lewczuk, K and Gola, M and Fernandez, DP and Fernandez, EF and Carnes, S and Lew-Starowicz, M and Kingston, D and Kraus, SW},
  journal = {Journal of behavioral addictions},
  year = {2023},
  doi = {10.1556/2006.2023.00005},
  pmid = {36913189},
  url = {https://pubmed.ncbi.nlm.nih.gov/36913189/},
  abstract = {The World Health Organization's International Classification of Diseases (ICD-11) includes Compulsive Sexual Behavior Disorder (CSBD), a new diagnosis that is both controversial and groundbreaking, as it is the first diagnosis to codify a disorder related to excessive, compulsive, and out-of-control sexual behavior. The inclusion of this novel diagnosis demonstrates a clear need for valid assessments of this disorder that may be quickly administered in both clinical and research settings. The present work details the development of the Compulsive Sexual Behavior Disorder Diagnostic Inventory (CSBD-DI) across seven samples, four languages, and five countries. In the first study, data were collected in community samples drawn from Malaysia (N = 375), the U.S. (N = 877), Hungary (N = 7,279), and Germany (N = 449). In the second study, data were collected from nationally representative samples in the U.S. (N = 1,601), Poland (N = 1,036), and Hungary (N = 473). Across both studies and all samples, results revealed strong psychometric qualities for the 7-item CSBD-DI, demonstrating evidence of validity via correlations with key behavioral indicators and longer measures of compulsive sexual behavior. Analyses from nationally representative samples revealed residual metric invariance across languages, scalar invariance across gender, strong evidence of validity, and utility in classifying individuals who self-identified as having problematic and excessive sexual behavior, as evidenced by ROC analyses revealing suitable cutoffs for a screening instrument. Collectively, these findings demonstrate the cross-cultural utility of the CSBD-DI as a novel measure for CSBD and provide a brief, easily administrable instrument for screening for this novel disorder.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Luo202337948768,
  title = {Almost free of calibration for SSVEP-based brain-computer interfaces.},
  author = {Luo, R and Xiao, X and Chen, E and Meng, L and Jung, TP and Xu, M and Ming, D},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/ad0b8f},
  pmid = {37948768},
  url = {https://pubmed.ncbi.nlm.nih.gov/37948768/},
  abstract = {Objective . Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) is a promising technology that can achieve high information transfer rate (ITR) with supervised algorithms such as ensemble task-related component analysis (eTRCA) and task-discriminant component analysis (TDCA). However, training individual models requires a tedious and time-consuming calibration process, which hinders the real-life use of SSVEP-BCIs. A recent data augmentation method, called source aliasing matrix estimation (SAME), can generate new EEG samples from a few calibration trials. But SAME does not exploit the information across stimuli as well as only reduces the number of calibration trials per command, so it still has some limitations. Approach . This study proposes an extended version of SAME, called multi-stimulus SAME (msSAME), which exploits the similarity of the aliasing matrix across frequencies to enhance the performance of SSVEP-BCI with insufficient calibration trials. We also propose a semi-supervised approach based on msSAME that can further reduce the number of SSVEP frequencies needed for calibration. We evaluate our method on two public datasets, Benchmark and BETA, and an online experiment. Main results . The results show that msSAME outperforms SAME for both eTRCA and TDCA on the public datasets. Moreover, the semi-supervised msSAME-based method achieves comparable performance to the fully calibrated methods and outperforms the conventional free-calibrated methods. Remarkably, our method only needs 24 s to calibrate 40 targets in the online experiment and achieves an average ITR of 213.8 bits min -1 with a peak of 242.6 bits min -1 . Significance . This study significantly reduces the calibration effort for individual SSVEP-BCIs, which is beneficial for developing practical plug-and-play SSVEP-BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hoxha202337072460,
  title = {Accounting for endogenous effects in decision-making with a non-linear diffusion decision model.},
  author = {Hoxha, I and Chevallier, S and Ciarchi, M and Glasauer, S and Delorme, A and Amorim, MA},
  journal = {Scientific reports},
  year = {2023},
  doi = {10.1038/s41598-023-32841-9},
  pmid = {37072460},
  url = {https://pubmed.ncbi.nlm.nih.gov/37072460/},
  abstract = {The Drift-Diffusion Model (DDM) is widely accepted for two-alternative forced-choice decision paradigms thanks to its simple formalism and close fit to behavioral and neurophysiological data. However, this formalism presents strong limitations in capturing inter-trial dynamics at the single-trial level and endogenous influences. We propose a novel model, the non-linear Drift-Diffusion Model (nl-DDM), that addresses these issues by allowing the existence of several trajectories to the decision boundary. We show that the non-linear model performs better than the drift-diffusion model for an equivalent complexity. To give better intuition on the meaning of nl-DDM parameters, we compare the DDM and the nl-DDM through correlation analysis. This paper provides evidence of the functioning of our model as an extension of the DDM. Moreover, we show that the nl-DDM captures time effects better than the DDM. Our model paves the way toward more accurately analyzing across-trial variability for perceptual decisions and accounts for peri-stimulus influences.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Han202336608342,
  title = {A high-speed hybrid brain-computer interface with more than 200 targets.},
  author = {Han, J and Xu, M and Xiao, X and Yi, W and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/acb105},
  pmid = {36608342},
  url = {https://pubmed.ncbi.nlm.nih.gov/36608342/},
  abstract = {Objective . Brain-computer interfaces (BCIs) have recently made significant strides in expanding their instruction set, which has attracted wide attention from researchers. The number of targets and commands is a key indicator of how well BCIs can decode the brain's intentions. No studies have reported a BCI system with over 200 targets. Approach . This study developed the first high-speed BCI system with up to 216 targets that were encoded by a combination of electroencephalography features, including P300, motion visual evoked potential (mVEP), and steady-state visual evoked potential (SSVEP). Specifically, the hybrid BCI paradigm used the time-frequency division multiple access strategy to elaborately tag targets with P300 and mVEP of different time windows, along with SSVEP of different frequencies. The hybrid features were then decoded by task-discriminant component analysis and linear discriminant analysis. Ten subjects participated in the offline and online cued-guided spelling experiments. Other ten subjects took part in online free-spelling experiments. Main results. The offline results showed that the mVEP and P300 components were prominent in the central, parietal, and occipital regions, while the most distinct SSVEP feature was in the occipital region. The online cued-guided spelling and free-spelling results showed that the proposed BCI system achieved an average accuracy of 85.37% ± 7.49% and 86.00% ± 5.98% for the 216-target classification, resulting in an average information transfer rate (ITR) of 302.83 ± 39.20 bits min -1 and 204.47 ± 37.56 bits min -1 , respectively. Notably, the peak ITR could reach up to 367.83 bits min -1 . Significance. This study developed the first high-speed BCI system with more than 200 targets, which holds promise for extending BCI's application scenarios.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xiao202337683663,
  title = {A data expansion technique based on training and testing sample to boost the detection of SSVEPs for brain-computer interfaces.},
  author = {Xiao, X and Wang, L and Xu, M and Wang, K and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2023},
  doi = {10.1088/1741-2552/acf7f6},
  pmid = {37683663},
  url = {https://pubmed.ncbi.nlm.nih.gov/37683663/},
  abstract = {Objective. Currently, steady-state visual evoked potentials (SSVEPs)-based brain-computer interfaces (BCIs) have achieved the highest interaction accuracy and speed among all BCI paradigms. However, its decoding efficacy depends deeply on the number of training samples, and the system performance would have a dramatic drop when the training dataset decreased to a small size. To date, no study has been reported to incorporate the unsupervised learning information from testing trails into the construction of supervised classification model, which is a potential way to mitigate the overfitting effect of limited samples. Approach. This study proposed a novel method for SSVEPs detection, i.e. cyclic shift trials (CSTs), which could combine unsupervised learning information from test trials and supervised learning information from train trials. Furthermore, since SSVEPs are time-locked and phase-locked to the onset of specific flashes, CST could also expand training samples on the basis of its regularity and periodicity. In order to verify the effectiveness of CST, we designed an online SSVEP-BCI system, and tested this system combined CST with two common classification algorithms, i.e. extended canonical correlation analysis and ensemble task-related component analysis. Main results. CST could significantly enhance the signal to noise ratios of SSVEPs and improve the performance of systems especially for the condition of few training samples and short stimulus time. The online information transfer rate could reach up to 236.19 bits min -1 using 36 s calibration time of only one training sample for each category. Significance. The proposed CST method can take full advantages of supervised learning information from training samples and unsupervised learning information of testing samples. Furthermore, it is a data expansion technique, which can enhance the SSVEP characteristics and reduce dependence on sample size. Above all, CST is a promising method to improve the performance of SSVEP-based BCI without any additional experimental burden.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Subash202337857685,
  title = {A comparison of neuroelectrophysiology databases.},
  author = {Subash, P and Gray, A and Boswell, M and Cohen, SL and Garner, R and Salehi, S and Fisher, C and Hobel, S and Ghosh, S and Halchenko, Y and Dichter, B and Poldrack, RA and Markiewicz, C and Hermes, D and Delorme, A and Makeig, S and Behan, B and Sparks, A and Arnott, SR and Wang, Z and Magnotti, J and Beauchamp, MS and Pouratian, N and Toga, AW and Duncan, D},
  journal = {Scientific data},
  year = {2023},
  doi = {10.1038/s41597-023-02614-0},
  pmid = {37857685},
  url = {https://pubmed.ncbi.nlm.nih.gov/37857685/},
  abstract = {As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Subash202337426452,
  title = {A Comparison of Neuroelectrophysiology Databases.},
  author = {Subash, P and Gray, A and Boswell, M and Cohen, SL and Garner, R and Salehi, S and Fisher, C and Hobel, S and Ghosh, S and Halchenko, Y and Dichter, B and Poldrack, RA and Markiewicz, C and Hermes, D and Delorme, A and Makeig, S and Behan, B and Sparks, A and Arnott, SR and Wang, Z and Magnotti, J and Beauchamp, MS and Pouratian, N and Toga, AW and Duncan, D},
  journal = {ArXiv},
  year = {2023},
  pmid = {37426452},
  url = {https://pubmed.ncbi.nlm.nih.gov/37426452/},
  abstract = {As data sharing has become more prevalent, three pillars - archives, standards, and analysis tools - have emerged as critical components in facilitating effective data sharing and collaboration. This paper compares four freely available intracranial neuroelectrophysiology data repositories: Data Archive for the BRAIN Initiative (DABI), Distributed Archives for Neurophysiology Data Integration (DANDI), OpenNeuro, and Brain-CODE. The aim of this review is to describe archives that provide researchers with tools to store, share, and reanalyze both human and non-human neurophysiology data based on criteria that are of interest to the neuroscientific community. The Brain Imaging Data Structure (BIDS) and Neurodata Without Borders (NWB) are utilized by these archives to make data more accessible to researchers by implementing a common standard. As the necessity for integrating large-scale analysis into data repository platforms continues to grow within the neuroscientific community, this article will highlight the various analytical and customizable tools developed within the chosen archives that may advance the field of neuroinformatics.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Cao202236310493,
  title = {[Research advances in non-invasive brain-computer interface control strategies].},
  author = {Cao, H and Jung, TP and Chen, Y and Mei, J and Li, A and Xu, M and Ming, D},
  journal = {Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi},
  year = {2022},
  doi = {10.7507/1001-5515.202205013},
  pmid = {36310493},
  url = {https://pubmed.ncbi.nlm.nih.gov/36310493/},
  abstract = {Brain-computer interface (BCI) can establish a direct communications pathway between the human brain and the external devices, which is independent of peripheral nerves and muscles. Compared with invasive BCI, non-invasive BCI has the advantages of low cost, low risk, and ease of operation. In recent years, using non-invasive BCI technology to control devices has gradually evolved into a new type of human-computer interaction manner. Moreover, the control strategy for BCI is an essential component of this manner. First, this study introduced how the brain control techniques were developed and classified. Second, the basic characteristics of direct and shared control strategies were thoroughly explained. And then the benefits and drawbacks of these two strategies were compared and further analyzed. Finally, the development direction and application prospects for non-invasive brain control strategies were suggested.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Yang202235523564,
  title = {[A review of researches on decoding algorithms of steady-state visual evoked potentials].},
  author = {Yang, M and Jung, TP and Han, J and Xu, M and Ming, D},
  journal = {Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi},
  year = {2022},
  doi = {10.7507/1001-5515.202111066},
  pmid = {35523564},
  url = {https://pubmed.ncbi.nlm.nih.gov/35523564/},
  abstract = {Brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) have become one of the major paradigms in BCI research due to their high signal-to-noise ratio and short training time required by users. Fast and accurate decoding of SSVEP features is a crucial step in SSVEP-BCI research. However, the current researches lack a systematic overview of SSVEP decoding algorithms and analyses of the connections and differences between them, so it is difficult for researchers to choose the optimum algorithm under different situations. To address this problem, this paper focuses on the progress of SSVEP decoding algorithms in recent years and divides them into two categories-trained and non-trained-based on whether training data are needed. This paper also explains the fundamental theories and application scopes of decoding algorithms such as canonical correlation analysis (CCA), task-related component analysis (TRCA) and the extended algorithms, concludes the commonly used strategies for processing decoding algorithms, and discusses the challenges and opportunities in this field in the end.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gola202234329192,
  title = {What should be included in the criteria for compulsive sexual behavior disorder?},
  author = {Gola, M and Lewczuk, K and Potenza, MN and Kingston, DA and Grubbs, JB and Stark, R and Reid, RC},
  journal = {Journal of behavioral addictions},
  year = {2022},
  doi = {10.1556/2006.2020.00090},
  pmid = {34329192},
  url = {https://pubmed.ncbi.nlm.nih.gov/34329192/},
  abstract = {Compulsive sexual behavior disorder (CSBD) is currently defined in the eleventh revision of the International Classification of Diseases (ICD-11) as an impulse control disorder. Criteria for hypersexual disorder (HD) had been proposed in 2010 for the fifth revision of Diagnostic and Statistical Manual (DSM-5). In this article, we compare differences between HD and CSBD and discuss their relevance. Significant differences between HD and CSBD criteria include: (1) the role of sexual behavior as a maladaptive coping and emotion regulation strategy listed in criteria for HD but not in those for CSBD; (2) different exclusionary criteria including bipolar and substance use disorders in HD but not in CSBD, and (3) inclusion of new considerations in CSBD, such as moral incongruence (as an exclusion criterion), and diminished pleasure from sexual activity. Each of these aspects has clinical and research-related implications. The inclusion of CSBD in the ICD-11 will have a significant impact on clinical practice and research. Researchers should continue to investigate core and related features of CSBD, inlcuding those not included in the current criteria, in order to provide additional insight into the disorder and to help promote clinical advances.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wahbeh202236160593,
  title = {What if consciousness is not an emergent property of the brain? Observational and empirical challenges to materialistic models.},
  author = {Wahbeh, H and Radin, D and Cannard, C and Delorme, A},
  journal = {Frontiers in psychology},
  year = {2022},
  doi = {10.3389/fpsyg.2022.955594},
  pmid = {36160593},
  url = {https://pubmed.ncbi.nlm.nih.gov/36160593/},
  abstract = {The nature of consciousness is considered one of science's most perplexing and persistent mysteries. We all know the subjective experience of consciousness, but where does it arise? What is its purpose? What are its full capacities? The assumption within today's neuroscience is that all aspects of consciousness arise solely from interactions among neurons in the brain. However, the origin and mechanisms of  qualia  (i.e., subjective or phenomenological experience) are not understood. David Chalmers coined the term "the hard problem" to describe the difficulties in elucidating the origins of subjectivity from the point of view of reductive materialism. We propose that the hard problem arises because one or more assumptions within a materialistic worldview are either wrong or incomplete. If consciousness entails more than the activity of neurons, then we can contemplate new ways of thinking about the hard problem. This review examines phenomena that apparently contradict the notion that consciousness is exclusively dependent on brain activity, including phenomena where consciousness appears to extend beyond the physical brain and body in both space and time. The mechanisms underlying these "non-local" properties are vaguely suggestive of quantum entanglement in physics, but how such effects might manifest remains highly speculative. The existence of these non-local effects appears to support the proposal that post-materialistic models of consciousness may be required to break the conceptual impasse presented by the hard problem of consciousness.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Hsu202234998969,
  title = {Unsupervised learning of brain state dynamics during emotion imagination using high-density EEG.},
  author = {Hsu, SH and Lin, Y and Onton, J and Jung, TP and Makeig, S},
  journal = {NeuroImage},
  year = {2022},
  doi = {10.1016/j.neuroimage.2022.118873},
  pmid = {34998969},
  url = {https://pubmed.ncbi.nlm.nih.gov/34998969/},
  abstract = {This study applies adaptive mixture independent component analysis (AMICA) to learn a set of ICA models, each optimized by fitting a distributional model for each identified component process while maximizing component process independence within some subsets of time points of a multi-channel EEG dataset. Here, we applied 20-model AMICA decomposition to long-duration (1-2 h), high-density (128-channel) EEG data recorded while participants used guided imagination to imagine situations stimulating the experience of 15 specified emotions. These decompositions tended to return models identifying spatiotemporal EEG patterns or states within single emotion imagination periods. Model probability transitions reflected time-courses of EEG dynamics during emotion imagination, which varied across emotions. Transitions between models accounting for imagined "grief" and "happiness" were more abrupt and better aligned with participant reports, while transitions for imagined "contentment" extended into adjoining "relaxation" periods. The spatial distributions of brain-localizable independent component processes (ICs) were more similar within participants (across emotions) than emotions (across participants). Across participants, brain regions with differences in IC spatial distributions (i.e., dipole density) between emotion imagination versus relaxation were identified in or near the left rostrolateral prefrontal, posterior cingulate cortex, right insula, bilateral sensorimotor, premotor, and associative visual cortex. No difference in dipole density was found between positive versus negative emotions. AMICA models of changes in high-density EEG dynamics may allow data-driven insights into brain dynamics during emotional experience, possibly enabling the improved performance of EEG-based emotion decoding and advancing our understanding of emotion.},
  note = {PubMed query source: Scott Makeig}
}

@article{Papp202235144325,
  title = {Triggers and Characteristics of Brain Zaps According to the Findings of an Internet Questionnaire.},
  author = {Papp, A and Onton, JA},
  journal = {The primary care companion for CNS disorders},
  year = {2022},
  doi = {10.4088/PCC.21m02972},
  pmid = {35144325},
  url = {https://pubmed.ncbi.nlm.nih.gov/35144325/},
  abstract = {Objective:  To build on the findings of our prior study of spontaneous posts made about brain zaps on a popular lay mental health website using questions specifically targeting brain zaps in a web-based questionnaire.  Methods:  3,141 responses were examined from an online questionnaire made available between June 2016 and February 2018. The questions probed the specifics of the medications taken, the temporal characteristics of medication taken, the symptoms associated with the brain zaps, the specifics of the "zap" experience itself, and their effect on quality of life. Special attention was paid to gathering data regarding the triggers of brain zaps, because in our previous study, eye movements triggering brain zaps emerged as an unexpected finding. As this was a convenience sample, qualitative analysis was primarily performed, except regarding the interaction between the half-life of antidepressants and the time to the onset of the first brain zaps, for which the numerical data appeared to be specific enough to allow such analyses.  Results:  The data from the targeted questionnaire showed a pattern of responses that was very similar to that obtained from analysis of the spontaneous posts. These data include the types of medications taken, the length of time these medications were taken before the onset of the zaps, the length of the zaps, the feeling quality of the zaps, and the effect of gradual versus sudden discontinuation on their onset and presence. Lateral eye movement as a trigger emerged with even more clarity than in the previous study. The positive correlation between the time from onset of the brain zaps and the half-life of the drugs strongly suggests that brain zaps are indeed associated with antidepressant discontinuation.  Conclusions:  Brain zaps remain a barely examined and poorly understood symptom of antidepressant discontinuation. Further studies are needed from both a prevention and treatment perspective. There is now an even stronger indication that brain zaps are typically triggered by lateral eye movements, which may open avenues for investigating this process.},
  note = {PubMed query source: Julie Onton}
}

@article{LewStarowicz202236073700,
  title = {Tolerability and efficacy of paroxetine and naltrexone for treatment of compulsive sexual behaviour disorder.},
  author = {Lew-Starowicz, M and Draps, M and Kowalewska, E and Obarska, K and Kraus, SW and Gola, M},
  journal = {World psychiatry : official journal of the World Psychiatric Association (WPA)},
  year = {2022},
  doi = {10.1002/wps.21026},
  pmid = {36073700},
  url = {https://pubmed.ncbi.nlm.nih.gov/36073700/},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wiza202236252343,
  title = {The relation of perceived social support to compulsive sexual behavior.},
  author = {Wizła, M and Glica, A and Gola, M and Lewczuk, K},
  journal = {Journal of psychiatric research},
  year = {2022},
  doi = {10.1016/j.jpsychires.2022.10.021},
  pmid = {36252343},
  url = {https://pubmed.ncbi.nlm.nih.gov/36252343/},
  abstract = {We conducted two studies to investigate the links between perceived social support, problematic pornography use (PPU) and compulsive sexual behavior disorder (CSBD). In Study 1 (n=807, convenience sample recruited via social media) we collected preliminary data and in Study 2 (n=1526) we checked whether the results replicate in a sample representative of the Polish adult population. In both studies participants completed the Brief Pornography Screen, Compulsive Sexual Behavior Disorder Scale and Multidimensional Scale of Perceived Social Support. In Study 1 and 2, general social support was a weak protective factor against CSBD (β = -0.15 and β = -0.10) and PPU (β = -0.12 and β = -0.09 respectively, all p values ≤ .001) adjusting for gender, age, sexual orientation and relationship status. The results for three domains of social support (from friends, significant other and family), however, largely differed between the two studies. In Study 1, perceived friends' support weakly protected against PPU and CSBD symptoms. In Study 2 higher support from friends weakly predicted lower CSBD symptoms among men; and stronger family support predicted lower PPU. Support from a significant other was weakly related to lower CSBD for women in Study 1. The conducted studies provided evidence that perceived social support is a protective factor against problematic sexual behavior; however, its predictive power is limited and further studies are needed to assess the importance of various domains of social support in the development of CSBD and PPU symptoms.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Obarska202236590610,
  title = {Reducing craving and lapse risk in alcohol and stimulants dependence using mobile app involving ecological momentary assessment and self-guided psychological interventions: Protocol for a randomized controlled trial.},
  author = {Obarska, K and Binkowska, AA and Marcowski, P and Szymczak, K and Lewczuk, K and Sollich, K and Banaszak, M and Woronowicz, B and Nowicka, M and Skorko, M and Gola, M},
  journal = {Frontiers in psychiatry},
  year = {2022},
  doi = {10.3389/fpsyt.2022.1011585},
  pmid = {36590610},
  url = {https://pubmed.ncbi.nlm.nih.gov/36590610/},
  abstract = {The prevalence of alcohol consumption in Poland is estimated to be as high as 80% of the adult population. The use of stimulants is the second most common reason for seeking addiction treatment. However, treatment outcomes remain unsatisfactory, as 40-85% of individuals who complete various treatment programs relapse and fall back into addiction within 2 years following program completion. The 13-armed randomized controlled trial aimed to assess the effectiveness of a mobile app-based self-guided psychological intervention delivered  via  a smartphone app ( Nałogometr ) in reducing craving and lapse risk in problematic alcohol or stimulants use. Participant recruitment and data collection will be performed from June 2022 to September 2022. The 4-week mobile intervention program will include short-term and long-term intervention modules based mainly on mindfulness and cognitive-behavioral therapy. Intervention effectiveness assessment will include Ecological Momentary Assessment. That is, we will collect longitudinal data on a set of characteristics of day-to-day functioning. The primary outcomes will include a self-reported number of lapses and addiction craving level. In contrast, the secondary outcomes will be the severity of problematic substance use, anxiety and depression scores, and life satisfaction scores. This study will establish how mobile app-based self-guided psychological interventions can help reduce craving and lapse risk in alcohol and stimulant dependence. If successful, this randomized controlled trial (RCT) may provide an innovative, easily available, and cost-effective mHealth approach for craving and lapse risk in substance addictions. [https://clinicaltrials.gov/], identifier [NCT054 34429].},
  note = {PubMed query source: Mateusz Gola}
}

@article{Kowalewska202235653876,
  title = {Predictors of Compulsive Sexual Behavior Among Treatment-Seeking Women.},
  author = {Kowalewska, E and Gola, M and Lew-Starowicz, M and Kraus, SW},
  journal = {Sexual medicine},
  year = {2022},
  doi = {10.1016/j.esxm.2022.100525},
  pmid = {35653876},
  url = {https://pubmed.ncbi.nlm.nih.gov/35653876/},
  abstract = {Compulsive Sexual Behavior Disorder is currently included in the forthcoming eleventh revision of the International Classification of Diseases (ICD-11); however, prior studies have been conducted mostly on heterosexual, White/European male samples. To examine the correlates of compulsive sexual behaviors (CSB) with sociodemographic and sexual history characteristics, as well as predictors of CSB in a sample of treatment-seeking Polish women. Six hundred seventy-four (674) Polish women aged 18-66 completed an online-based survey. Polish adaptation of the Sexual Addiction Screening Test-Revised (SAST-PL) was used to assess the severity of CSB symptoms. Brief Pornography Screen was used to measure problematic pornography use. The bivariate associations between SAST-PL scores and demographic and sexual history characteristics were also examined. A linear regression analysis was performed to identify variables related to the severity of CSB symptoms. Thirty one percent (31.8%) of women in the studied sample reported treatment seeking for CSB in the past. Problematic pornography use was the strongest predictor of CSB symptoms. Higher severity of CSB symptoms were observed among divorced/separated and single women compared to those who were married or in informal relation. Severity of CSB was positively related to the number of sexual partners during the last year, number of dyadic sexual intercourse during the last 7 days, and negatively associated with age of first sexual intercourse. Our results suggest that CSB is a significant concern among women and more research is needed to identify protective (eg, relationship status) and risk (eg, problematic pornography use, number of past year sexual partners, frequency of past week masturbation) factors associated with CSB symptom severity among treatment-seeking women. Our study is one of very few investigating predictors of CSB among women. Given the lack of precise estimates of the prevalence, as well as lack of psychometrically validated instruments measuring CSB in women, present findings should not be considered indicative of CSB prevalence among Polish women. The lack of clinical data on women reporting issues with CSB remains an important target for future clinical research exploration. Kowalewska E, Gola M, Lew-Starowicz M, et al. Predictors of Compulsive Sexual Behavior Among Treatment-Seeking Women. Sex Med 2022;10:100525.},
  note = {PubMed query source: Mateusz Gola}
}

@article{OKeeffe202235594214,
  title = {Perilaryngeal-Cranial Functional Muscle Network Differentiates Vocal Tasks: A Multi-Channel sEMG Approach.},
  author = {O'Keeffe, R and Shirazi, SY and Mehrdad, S and Crosby, T and Johnson, AM and Atashzar, SF},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2022},
  doi = {10.1109/TBME.2022.3175948},
  pmid = {35594214},
  url = {https://pubmed.ncbi.nlm.nih.gov/35594214/},
  abstract = {Objective evaluation of physiological responses using non-invasive methods for the assessment of vocal performance and voice disorders has attracted great interest. This paper, for the first time, aims to implement and evaluate perilaryngeal-cranial functional muscle networks. The study investigates the variations in topographical characteristics of the network and the corresponding ability to differentiate vocal tasks. Twelve surface electromyography (sEMG) signals were collected bilaterally from six perilaryngeal and cranial muscles. Data were collected from eight subjects (four females) without a known history of voice disorders. The proposed muscle network is composed of pairwise coherence between sEMG recordings. The network metrics include (a) network degree and (b) weighted clustering coefficient (WCC). The varied phonation tasks showed the median degree, and WCC of the muscle network ascend monotonically, with a high effect size ( |r rb | ∼ 0.5). Pitch glide, singing, and speech tasks were significantly distinguishable using degree and WCC ( |r rb | ∼ 0.8). Also, pitch glide had the highest degree and WCC among all tasks (degree , WCC ). In comparison, classic spectrotemporal measures showed far less effectiveness (max |r rb |=0.12) in differentiating the vocal tasks. Perilaryngeal-cranial functional muscle network was proposed in this paper. The study showed that the functional muscle network could robustly differentiate the vocal tasks while the classic assessment of muscle activation fails to differentiate. For the first time, we demonstrate the power of a perilaryngeal-cranial muscle network as a neurophysiological window to vocal performance. In addition, the study also discovers tasks with the highest network involvement, which may be utilized in the future to monitor voice disorders and rehabilitation.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Wong202234882542,
  title = {Online Adaptation Boosts SSVEP-Based BCI Performance.},
  author = {Wong, CM and Wang, Z and Nakanishi, M and Wang, B and Rosa, A and Chen, CLP and Jung, TP and Wan, F},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2022},
  doi = {10.1109/TBME.2021.3133594},
  pmid = {34882542},
  url = {https://pubmed.ncbi.nlm.nih.gov/34882542/},
  abstract = {A user-friendly steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) prefers no calibration for its target recognition algorithm, however, the existing calibration-free schemes perform still far behind their calibration-based counterparts. To tackle this issue, learning online from the subject's unlabeled data is investigated as a potential approach to boost the performance of the calibration-free SSVEP-based BCIs. An online adaptation scheme is developed to tune the spatial filters using the online unlabeled data from previous trials, and then developing the online adaptive canonical correlation analysis (OACCA) method. A simulation study on two public SSVEP datasets (Dataset I and II) with a total of 105 subjects demonstrated that the proposed online adaptation scheme can boost the CCA's averaged information transfer rate (ITR) from 94.60 to 158.87 bits/min in Dataset I and from 85.80 to 123.91 bits/min in Dataset II. Furthermore, in our online experiment it boosted the CCA's ITR from 55.81 bits/min to 95.73 bits/min. More importantly, this online adaptation scheme can be easily combined with any spatial filtering-based algorithms to achieve online learning. By online adaptation, the proposed OACCA performed much better than the calibration-free CCA, and comparable to the calibration-based algorithms. This work provides a general way for the SSVEP-based BCIs to learn online from unlabeled data and thus avoid calibration.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gorowska202235405548,
  title = {Novel approaches for treating Internet Gaming Disorder: A review of technology-based interventions.},
  author = {Gorowska, M and Tokarska, K and Zhou, X and Gola, MK and Li, Y},
  journal = {Comprehensive psychiatry},
  year = {2022},
  doi = {10.1016/j.comppsych.2022.152312},
  pmid = {35405548},
  url = {https://pubmed.ncbi.nlm.nih.gov/35405548/},
  abstract = {Internet Gaming Disorder (IGD) has become a significant issue in mental healthcare over the past decades as the number of people engaging in excessive and unhealthy gaming increases with each year. Despite its inclusion in the 5th Edition of Diagnostic Statistical Manual and the development of a number of treatment methods that have been designed and tested for IGD, treatment remains a challenge. This review attempts to give an overview of the current state of IGD and its treatment with a specific focus on the potential of technology-based solutions, such as web-based programs, mobile applications, and virtual reality. The review also highlights the need for additional work in the area of treatment development for IGD and the preliminary evidence for the usefulness and importance of technology-based treatment methods which offer unique advantages, such as accessibility, scalability, and cost-effectiveness, over other existing treatment options.},
  note = {PubMed query source: Mateusz Gola}
}

@article{OKeeffe202235906239,
  title = {Nonlinear functional muscle network based on information theory tracks sensorimotor integration post stroke.},
  author = {O'Keeffe, R and Shirazi, SY and Bilaloglu, S and Jahed, S and Bighamian, R and Raghavan, P and Atashzar, SF},
  journal = {Scientific reports},
  year = {2022},
  doi = {10.1038/s41598-022-16483-x},
  pmid = {35906239},
  url = {https://pubmed.ncbi.nlm.nih.gov/35906239/},
  abstract = {Sensory information is critical for motor coordination. However, understanding sensorimotor integration is complicated, especially in individuals with impairment due to injury to the central nervous system. This research presents a novel functional biomarker, based on a nonlinear network graph of muscle connectivity, called InfoMuNet, to quantify the role of sensory information on motor performance. Thirty-two individuals with post-stroke hemiparesis performed a grasp-and-lift task, while their muscle activity from 8 muscles in each arm was measured using surface electromyography. Subjects performed the task with their affected hand before and after sensory exposure to the task performed with the less-affected hand. For the first time, this work shows that InfoMuNet robustly quantifies changes in functional muscle connectivity in the affected hand after exposure to sensory information from the less-affected side. > 90% of the subjects conformed with the improvement resulting from this sensory exposure. InfoMuNet also shows high sensitivity to tactile, kinesthetic, and visual input alterations at the subject level, highlighting its potential use in precision rehabilitation interventions.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Delorme202236367313,
  title = {NEMAR: an open access data, tools and compute resource operating on neuroelectromagnetic data.},
  author = {Delorme, A and Truong, D and Youn, C and Sivagnanam, S and Stirm, C and Yoshimoto, K and Poldrack, RA and Majumdar, A and Makeig, S},
  journal = {Database : the journal of biological databases and curation},
  year = {2022},
  doi = {10.1093/database/baac096},
  pmid = {36367313},
  url = {https://pubmed.ncbi.nlm.nih.gov/36367313/},
  abstract = {To preserve scientific data created by publicly and/or philanthropically funded research projects and to make it ready for exploitation using recent and ongoing advances in advanced and large-scale computational modeling methods, publicly available data must use in common, now-evolving standards for formatting, identifying and annotating should share data. The OpenNeuro.org archive, built first as a repository for magnetic resonance imaging data based on the Brain Imaging Data Structure formatting standards, aims to house and share all types of human neuroimaging data. Here, we present NEMAR.org, a web gateway to OpenNeuro data for human neuroelectromagnetic data. NEMAR allows users to search through, visually explore and assess the quality of shared electroencephalography (EEG), magnetoencephalography and intracranial EEG data and then to directly process selected data using high-performance computing resources of the San Diego Supercomputer Center via the Neuroscience Gateway (nsgportal.org, NSG), a freely available web portal to high-performance computing serving a variety of neuroscientific analysis environments and tools. Combined, OpenNeuro, NEMAR and NSG form an efficient, integrated data, tools and compute resource for human neuroimaging data analysis and meta-analysis. Database URL: https://nemar.org.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{McLoughlin202234756560,
  title = {Midfrontal Theta Activity in Psychiatric Illness: An Index of Cognitive Vulnerabilities Across Disorders.},
  author = {McLoughlin, G and Gyurkovics, M and Palmer, J and Makeig, S},
  journal = {Biological psychiatry},
  year = {2022},
  doi = {10.1016/j.biopsych.2021.08.020},
  pmid = {34756560},
  url = {https://pubmed.ncbi.nlm.nih.gov/34756560/},
  abstract = {There is an urgent need to identify the mechanisms that contribute to atypical thinking and behavior associated with psychiatric illness. Behavioral and brain measures of cognitive control are associated with a variety of psychiatric disorders and conditions as well as daily life functioning. Recognition of the importance of cognitive control in human behavior has led to intensive research into behavioral and neurobiological correlates. Oscillations in the theta band (4-8 Hz) over medial frontal recording sites are becoming increasingly established as a direct neural index of certain aspects of cognitive control. In this review, we point toward evidence that theta acts to coordinate multiple neural processes in disparate brain regions during task processing to optimize behavior. Theta-related signals in human electroencephalography include the N2, the error-related negativity, and measures of theta power in the (time-)frequency domain. We investigate how these theta signals are affected in a wide range of psychiatric conditions with known deficiencies in cognitive control: anxiety, obsessive-compulsive disorder, attention-deficit/hyperactivity disorder, and substance abuse. Theta-related control signals and their temporal consistency were found to differ in most patient groups compared with healthy control subjects, suggesting fundamental deficits in reactive and proactive control. Notably, however, clinical studies directly investigating the role of theta in the coordination of goal-directed processes across different brain regions are uncommon and are encouraged in future research. A finer-grained analysis of flexible, subsecond-scale functional networks in psychiatric disorders could contribute to a dimensional understanding of psychopathology.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lewczuk202234750777,
  title = {Increase in the Prevalence of Online Pornography Use: Objective Data Analysis from the Period Between 2004 and 2016 in Poland.},
  author = {Lewczuk, K and Wójcik, A and Gola, M},
  journal = {Archives of sexual behavior},
  year = {2022},
  doi = {10.1007/s10508-021-02090-w},
  pmid = {34750777},
  url = {https://pubmed.ncbi.nlm.nih.gov/34750777/},
  abstract = {Despite the considerable amount of attention presently devoted to the high accessibility of online pornography, very little formal analyses have been carried out to show how the advent and proliferation of Internet technology has changed the prevalence of pornography use in populations. We conducted a preliminary analysis based on objective website traffic data, representing the changes in the number of (1) Internet users generally and (2) online pornography users specifically, between 2004 and 2016 in Poland. We observed a clear increase in the estimated number of people using online pornography in the analyzed period. The estimated number of general population members viewing pornography on the Internet increased over three times (310%) between October 2004 and October 2016-starting from an estimated 2.76 million in the first period to 8.54 million in the last. At the same time, we did not observe a clear increase in the percentage of Internet users who viewed online pornography in the same time period. Additionally, pornography viewership on the Internet was almost 2 times more prevalent among male (47%) than female Internet users (27%), and most popular in the 18-27 age group. Since our analysis is based on objective data, it does not share the limitations inherent in self-reports. However, our approach also has several important limitations (e.g., the analysis does not include online activity generated on mobile devices and under a private browsing mode); thus, the results should be interpreted with caution.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Chuang202236031182,
  title = {IC-U-Net: A U-Net-based Denoising Autoencoder Using Mixtures of Independent Components for Automatic EEG Artifact Removal.},
  author = {Chuang, CH and Chang, KY and Huang, CS and Jung, TP},
  journal = {NeuroImage},
  year = {2022},
  doi = {10.1016/j.neuroimage.2022.119586},
  pmid = {36031182},
  url = {https://pubmed.ncbi.nlm.nih.gov/36031182/},
  abstract = {Electroencephalography (EEG) signals are often contaminated with artifacts. It is imperative to develop a practical and reliable artifact removal method to prevent the misinterpretation of neural signals and the underperformance of brain-computer interfaces. Based on the U-Net architecture, we developed a new artifact removal model, IC-U-Net, for removing pervasive EEG artifacts and reconstructing brain signals. IC-U-Net was trained using mixtures of brain and non-brain components decomposed by independent component analysis. It uses an ensemble of loss functions to model complex signal fluctuations in EEG recordings. The effectiveness of the proposed method in recovering brain activities and removing various artifacts (e.g., eye blinks/movements, muscle activities, and line/channel noise) was demonstrated in a simulation study and four real-world EEG experiments. IC-U-Net can reconstruct a multi-channel EEG signal and is applicable to most artifact types, offering a promising end-to-end solution for automatically removing artifacts from EEG recordings. It also meets the increasing need to image natural brain dynamics in a mobile setting. The code and pre-trained IC-U-Net model are available at https://github.com/roseDwayane/AIEEG.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Draps202235831231,
  title = {Functional Connectivity in Compulsive Sexual Behavior Disorder - Systematic Review of Literature and Study on Heterosexual Males.},
  author = {Draps, M and Adamus, S and Wierzba, M and Gola, M},
  journal = {The journal of sexual medicine},
  year = {2022},
  doi = {10.1016/j.jsxm.2022.05.146},
  pmid = {35831231},
  url = {https://pubmed.ncbi.nlm.nih.gov/35831231/},
  abstract = {Compulsive Sexual Behavior Disorder (CSBD) was recently included in ICD-11 as a new impulse control disorder. While this certainly improved the diagnosis of CSBD, the underlying brain mechanisms of the disorder are still poorly understood. Better description of brain functional deficits is required. Here we investigate patterns of resting-state brain functional connectivity (fc) in a group of CSBD patients compared to a group of healthy controls (HC). A MATLAB toolbox named CONN functional connectivity toolbox was employed to study patterns of brain connectivity. Also correlation between fc and severity of CSBD symptoms and other psychological characteristics, assessed with questionnaires, were examined. We collected resting-state functional magnetic resonance imaging data from 81 heterosexual males: 52 CSBD patients and 29 HC. We found increased fc between left inferior frontal gyrus and right planum temporale and polare, right and left insula, right Supplementary Motor Cortex (SMA), right parietal operculum, and also between left supramarginal gyrus and right planum polare, and between left orbitofrontal cortex and left insula when compared CSBD and HC. The decreased fc was observed between left middle temporal gyrus and bilateral insula and right parietal operculum. No significant correlations between psychological questionnaires assessing CSBD symptoms and resting-state functional connectivity were observed. Results from our study extend the knowledge of brain mechanisms differentiating CSBD from HC. The study was the first large sample study showing 5 distinct functional brain networks differentiating CSBD patients and HC. However, the sample was limited only to heterosexual men, in the future a greater diversity in studied sample and longitudinal studies are needed. Also, the present study examined functional connectivity at the level of regions of interest (ROIs). Future studies could verify these results by examining functional connectivity at the voxel level. The identified functional brain networks differentiate CSBD from HC and provide some support for incentive sensitization as mechanism underlying CSBD symptoms. The correlation between psychological assessment (ie, severity of CSBD, depression and anxiety symptoms, level of impulsivity and compulsivity) and resting-state functional connectivity need further examination. Draps M, Adamus S, Wierzba M, et al. Functional Connectivity in Compulsive Sexual Behavior Disorder - Systematic Review of Literature and Study on Heterosexual Males. J Sex Med 2022;19:1463-1471.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wahbeh202235085021,
  title = {Exploring Personal Development Workshops' Effect on Well-Being and Interconnectedness.},
  author = {Wahbeh, H and Yount, G and Vieten, C and Radin, D and Delorme, A},
  journal = {Journal of integrative and complementary medicine},
  year = {2022},
  doi = {10.1089/jicm.2021.0043},
  pmid = {35085021},
  url = {https://pubmed.ncbi.nlm.nih.gov/35085021/},
  abstract = {Introduction:  Personal development workshops are increasingly popular. This study evaluated the relationships between the measures of well-being, interconnectedness, and extended perception in various workshops and explored which kinds of workshops and individual characteristics predicted changes in these outcomes.  Materials and Methods:  In a prospective, uncontrolled, within-participant design study, adult participants completed questionnaires and online tasks before and after personal development workshops. Three analyses were conducted: (1) examining the relationships between measures by using only pre-workshop measures using Spearman correlations; (2) exploring change scores pre- to post-workshop and workshop using Wilcoxon signed-rank test; (3) assessing workshop format and content, and individual characteristics as predictors of those change scores multivariate nonparametric regression. The following outcomes were collected: Well-being-Arizona Integrative Outcomes Scale, positive and negative affect, Dispositional Positive Emotions Scale-Compassion subscale, Sleep Quality Scale, Numeric Pain Rating Scale; Interconnectedness-Cloninger Self-Transcendence Scale, Inclusion of Nature in Self and Inclusion of the Other in Self; and Extended perception tasks-Intuition Jar, Quick Remote Viewing, Psychokinesis Bubble, and Time Estimation. The following potential predictor variables were collected: demographic, mental health, psychiatric and meditation history, Single General Self-Rated Health Question, Brief Five-Factor Inventory-10, and the Noetic Experience and Belief Scale. Workshop leaders also selected which format and content characteristics applied to their workshop.  Results:  Interconnectedness measures were significantly and positively correlated with well-being ( ρ : 0.27 to 0.33), positive affect ( ρ : 0.20 to 0.27), and compassion ( ρ : 0.21 to 0.32), and they were negatively correlated with sleep disturbance ( ρ : -0.13 to -0.16) and pain ( ρ : -0.11 to -0.16). Extended perception task performance was not correlated with interconnectedness or well-being. General personal development workshops improved subjective interconnectedness, well-being, positive emotion, and compassion, and they reduced sleep disturbances, negative emotion, and pain (all  p' s < 0.00005). The lecture ( p  = 0.03), small groups ( p  = 0.001), pairs ( p  = 0.01), and discussion ( p  = 0.03) workshop formats were significant predictors of well-being outcomes. The workshop content categories of meditation ( p  = 0.0002) and technology tools ( p  = 0.01) were also predictive of well-being outcomes, with meditation being the most consistent predictor of positive well-being changes. Conscientiousness was the only significant individual characteristic predictor ( p  = 0.002), although it was associated with increases in some well-being measures and decreases in others.  Conclusions:  This study provides preliminary evidence for the positive relationship between the subjective sense of interconnectedness and multiple well-being measures and the beneficial effects of some personal development workshops.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Acar202236086241,
  title = {Evaluation of skull conductivity using SCALE head tissue conductivity estimation using EEG.},
  author = {Acar, ZA and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2022},
  doi = {10.1109/EMBC48229.2022.9872004},
  pmid = {36086241},
  url = {https://pubmed.ncbi.nlm.nih.gov/36086241/},
  abstract = {Inaccurate estimation of skull conductivity is the largest impediment to high-resolution EEG source imaging because of its strong influence and wide variability across individuals. Nonetheless, there is yet no widely applied method for noninvasively measuring individual skull conductivity. We presented a skull conductivity and source location estimation algorithm (SCALE) for simultaneously estimating skull conductivity and the cortical distributions of 18-20 effective sources derived from the EEG data by independent component analysis (ICA). SCALE combines a realistic Finite Element Method (FEM) head model built from a magnetic resonance (MR) head image with the effective source scalp maps to estimate brain-to-skull conductivity ratio (BSCR) and to map the effective sources on the cortical surface. To estimate the robustness of SCALE BSCR estimates, we applied SCALE to MR image and high-density EEG data from ten participants, five having data from 2-3 different tasks and sessions. As expected, across participants SCALE BSCR estimates differed widely (mean 32.8, range 18-78). Within-participant SCALE BSCR estimates were far more consistent than between participants. By incorporating SCALE-optimized distributed EEG source localization, stable functional imaging of cortical EEG effective sources can become routine, giving relatively low-cost EEG imaging a spatial resolution compatible with other brain imaging results and uniquely capable for studying brain dynamics supporting thought and action in laboratory, virtual, and natural environments.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme202235495048,
  title = {Editorial: From Raw MEG/EEG to Publication: How to Perform MEG/EEG Group Analysis With Free Academic Software.},
  author = {Delorme, A and Oostenveld, R and Tadel, F and Gramfort, A and Nagarajan, S and Litvak, V},
  journal = {Frontiers in neuroscience},
  year = {2022},
  doi = {10.3389/fnins.2022.854471},
  pmid = {35495048},
  url = {https://pubmed.ncbi.nlm.nih.gov/35495048/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Tsai202235714085,
  title = {Development of an Adaptive Artifact Subspace Reconstruction Based on Hebbian/Anti-Hebbian Learning Networks for Enhancing BCI Performance.},
  author = {Tsai, BY and Diddi, SVS and Ko, LW and Wang, SJ and Chang, CY and Jung, TP},
  journal = {IEEE transactions on neural networks and learning systems},
  year = {2022},
  doi = {10.1109/TNNLS.2022.3174528},
  pmid = {35714085},
  url = {https://pubmed.ncbi.nlm.nih.gov/35714085/},
  abstract = {Brain-computer interface (BCI) actively translates the brain signals into executable actions by establishing direct communication between the human brain and external devices. Recording brain activity through electroencephalography (EEG) is generally contaminated with both physiological and nonphysiological artifacts, which significantly hinders the BCI performance. Artifact subspace reconstruction (ASR) is a well-known statistical technique that automatically removes artifact components by determining the rejection threshold based on the initial reference EEG segment in multichannel EEG recordings. In real-world applications, the fixed threshold may limit the efficacy of the artifact correction, especially when the quality of the reference data is poor. This study proposes an adaptive online ASR technique by integrating the Hebbian/anti-Hebbian neural networks into the ASR algorithm, namely, principle subspace projection ASR (PSP-ASR) and principal subspace whitening ASR (PSW-ASR) that segmentwise self-organize the artifact subspace by updating the synaptic weights according to the Hebbian and anti-Hebbian learning rules. The effectiveness of the proposed algorithm is compared to the conventional ASR approaches on benchmark EEG dataset and three BCI frameworks, including steady-state visual evoked potential (SSVEP), rapid serial visual presentation (RSVP), and motor imagery (MI) by evaluating the root-mean-square error (RMSE), the signal-to-noise ratio (SNR), the Pearson correlation, and classification accuracy. The results demonstrated that the PSW-ASR algorithm effectively removed the EEG artifacts and retained the activity-specific brain signals compared to the PSP-ASR, standard ASR (Init-ASR), and moving-window ASR (MW-ASR) methods, thereby enhancing the SSVEP, RSVP, and MI BCI performances. Finally, our empirical results from the PSW-ASR algorithm suggested the choice of an aggressive cutoff range of c = 1-10 for activity-specific BCI applications and a moderate range of for the benchmark dataset and general BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Ross202234936516,
  title = {Cortical mu rhythms during action and passive music listening.},
  author = {Ross, JM and Comstock, DC and Iversen, JR and Makeig, S and Balasubramaniam, R},
  journal = {Journal of neurophysiology},
  year = {2022},
  doi = {10.1152/jn.00346.2021},
  pmid = {34936516},
  url = {https://pubmed.ncbi.nlm.nih.gov/34936516/},
  abstract = {Brain systems supporting body movement are active during music listening in the absence of overt movement. This covert motor activity is not well understood, but some theories propose a role in auditory timing prediction facilitated by motor simulation. One question is how music-related covert motor activity relates to motor activity during overt movement. We address this question using scalp electroencephalogram by measuring mu rhythms-cortical field phenomena associated with the somatomotor system that appear over sensorimotor cortex. Lateralized mu enhancement over hand sensorimotor cortex during/just before foot movement in foot versus hand movement paradigms is thought to reflect hand movement inhibition during current/prospective movement of another effector. Behavior of mu during music listening with movement suppressed has yet to be determined. We recorded 32-channel EEG ( n  = 17) during silence without movement, overt movement (foot/hand), and music listening without movement. Using an independent component analysis-based source equivalent dipole clustering technique, we identified three mu-related clusters, localized to left primary motor and right and midline premotor cortices. Right foot tapping was accompanied by mu enhancement in the left lateral source cluster, replicating previous work. Music listening was accompanied by similar mu enhancement in the left, as well as midline, clusters. We are the first, to our knowledge, to report, and also to source-resolve, music-related mu modulation in the absence of overt movements. Covert music-related motor activity has been shown to play a role in beat perception (Ross JM, Iversen JR, Balasubramaniam R.  Neurocase  22: 558-565, 2016). Our current results show enhancement in somatotopically organized mu, supporting overt motor inhibition during beat perception. NEW & NOTEWORTHY  We are the first to report music-related mu enhancement in the absence of overt movements and the first to source-resolve mu activity during music listening. We suggest that music-related mu modulation reflects overt motor inhibition during passive music listening. This work is relevant for the development of theories relating to the involvement of covert motor system activity for predictive beat perception.},
  note = {PubMed query source: Scott Makeig}
}

@article{Iraniparast202235121669,
  title = {Cognitive Reserve and Mild Cognitive Impairment: Predictors and Rates of Reversion to Intact Cognition vs Progression to Dementia.},
  author = {Iraniparast, M and Shi, Y and Wu, Y and Zeng, L and Maxwell, CJ and Kryscio, RJ and St John, PD and SantaCruz, KS and Tyas, SL},
  journal = {Neurology},
  year = {2022},
  doi = {10.1212/WNL.0000000000200051},
  pmid = {35121669},
  url = {https://pubmed.ncbi.nlm.nih.gov/35121669/},
  abstract = {Little is known about the effect of education or other indicators of cognitive reserve on the rate of reversion from mild cognitive impairment (MCI) to normal cognition (NC) or the relative rate (RR) of reversion from MCI to NC vs progression from MCI to dementia. Our objectives were to (1) estimate transition rates from MCI to NC and dementia and (2) determine the effect of age,  APOE , and indicators of cognitive reserve on the RR of reversion vs progression using multistate Markov modeling. We estimated instantaneous transition rates between NC, MCI, and dementia after accounting for transition to death across up to 12 assessments in the Nun Study, a cohort study of religious sisters aged 75+ years. We estimated RRs of reversion vs progression for age,  APOE , and potential cognitive reserve indicators: education, academic performance (high school grades), and written language skills (idea density, grammatical complexity). Of the 619 participants, 472 were assessed with MCI during the study period. Of these 472, 143 (30.3%) experienced at least one reverse transition to NC, and 120 of the 143 (83.9%) never developed dementia (mean follow-up = 8.6 years). In models adjusted for age group and  APOE , higher levels of education more than doubled the RR ratio of reversion vs progression. Novel cognitive reserve indicators were significantly associated with a higher adjusted RR of reversion vs progression (higher vs lower levels for English grades: RR ratio = 1.83; idea density: RR ratio = 3.93; and grammatical complexity: RR ratio = 5.78). Knowledge of frequent reversion from MCI to NC may alleviate concerns of inevitable cognitive decline in those with MCI. Identification of characteristics predicting the rate of reversion from MCI to NC vs progression from MCI to dementia may guide population-level interventions targeting these characteristics to prevent or postpone MCI and dementia. Research on cognitive trajectories would benefit from incorporating predictors of reverse transitions and competing events, such as death, into statistical modeling. These results may inform the design and interpretation of MCI clinical trials, given that a substantial proportion of participants may experience improvement without intervention.},
  note = {PubMed query source: Ying Wu}
}

@article{Robbins202234970709,
  title = {Building FAIR Functionality: Annotating Events in Time Series Data Using Hierarchical Event Descriptors (HED).},
  author = {Robbins, K and Truong, D and Jones, A and Callanan, I and Makeig, S},
  journal = {Neuroinformatics},
  year = {2022},
  doi = {10.1007/s12021-021-09537-4},
  pmid = {34970709},
  url = {https://pubmed.ncbi.nlm.nih.gov/34970709/},
  abstract = {Human electrophysiological and related time series data are often acquired in complex, event-rich environments. However, the resulting recorded brain or other dynamics are often interpreted in relation to more sparsely recorded or subsequently-noted events. Currently a substantial gap exists between the level of event description required by current digital data archiving standards and the level of annotation required for successful analysis of event-related data across studies, environments, and laboratories. Manifold challenges must be addressed, most prominently ontological clarity, vocabulary extensibility, annotation tool availability, and overall usability, to allow and promote sharing of data with an effective level of descriptive detail for labeled events. Motivating data authors to perform the work needed to adequately annotate their data is a key challenge. This paper describes new developments in the Hierarchical Event Descriptor (HED) system for addressing these issues. We recap the evolution of HED and its acceptance by the Brain Imaging Data Structure (BIDS) movement, describe the recent release of HED-3G, a third generation HED tools and design framework, and discuss directions for future development. Given consistent, sufficiently detailed, tool-enabled, field-relevant annotation of the nature of recorded events, prospects are bright for large-scale analysis and modeling of aggregated time series data, both in behavioral and brain imaging sciences and beyond.},
  note = {PubMed query source: Scott Makeig}
}

@article{Truong202236085766,
  title = {A streamable large-scale clinical EEG dataset for Deep Learning.},
  author = {Truong, D and Sinha, M and Venkataraju, KU and Milham, M and Delorme, A},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2022},
  doi = {10.1109/EMBC48229.2022.9871708},
  pmid = {36085766},
  url = {https://pubmed.ncbi.nlm.nih.gov/36085766/},
  abstract = {Deep Learning has revolutionized various fields, including Computer Vision, Natural Language Processing, as well as Biomedical research. Within the field of neuroscience, specifically in electrophysiological neuroimaging, researchers are starting to explore leveraging deep learning to make predictions on their data without extensive feature engineering. The availability of large-scale datasets is a crucial aspect of allowing the experimentation of Deep Learning models. We are publishing the first large-scale clinical EEG dataset that simplifies data access and management for Deep Learning. This dataset contains eyes-closed EEG data prepared from a collection of 1,574 juvenile participants from the Healthy Brain Network. We demonstrate a use case integrating this framework, and discuss why providing such neuroinformatics infrastructure to the community is critical for future scientific discoveries.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Sun202134180191,
  title = {[Classification algorithms of error-related potentials in brain-computer interface].},
  author = {Sun, J and Jung, TP and Xiao, X and Meng, J and Xu, M and Ming, D},
  journal = {Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi},
  year = {2021},
  doi = {10.7507/1001-5515.202012013},
  pmid = {34180191},
  url = {https://pubmed.ncbi.nlm.nih.gov/34180191/},
  abstract = {Error self-detection based on error-related potentials (ErrP) is promising to improve the practicability of brain-computer interface systems. But the single trial recognition of ErrP is still a challenge that hinters the development of this technology. To assess the performance of different algorithms on decoding ErrP, this paper test four kinds of linear discriminant analysis algorithms, two kinds of support vector machines, logistic regression, and discriminative canonical pattern matching (DCPM) on two open accessed datasets. All algorithms were evaluated by their classification accuracies and their generalization ability on different sizes of training sets. The study results show that DCPM has the best performance. This study shows a comprehensive comparison of different algorithms on ErrP classification, which could give guidance for the selection of ErrP algorithm.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Draps202133570504,
  title = {White matter microstructural and Compulsive Sexual Behaviors Disorder - Diffusion Tensor Imaging study.},
  author = {Draps, M and Kowalczyk-Grębska, N and Marchewka, A and Shi, F and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2021},
  doi = {10.1556/2006.2021.00002},
  pmid = {33570504},
  url = {https://pubmed.ncbi.nlm.nih.gov/33570504/},
  abstract = {Even though the Compulsive Sexual Behavior Disorder (CSBD) was added to the ICD-11 under the impulse control category in 2019, its neural mechanisms are still debated. Researchers have noted its similarity both to addiction and to Obssesive-Compulsive Disorder (OCD). The aim of our study was to address this question by investigating the pattern of anatomical brain abnormalities among CSBD patients. Reviewing 39 publications on Diffusion Tensor Imaging (DTI) we have identified main abnormalities specific for addictions and OCD. Than we have collected DTI data from 36 heterosexual males diagnosed with CSBD and 31 matched healthy controls. These results were then compared to the addiction and OCD patterns. Compared to controls, CSBD individuals showed significant fractional anisotropy (FA) reduction in the superior corona radiata tract, the internal capsule tract, cerebellar tracts and occipital gyrus white matter. Interestingly, all these regions were also identified in previous studies as shared DTI correlates in both OCD and addiction. Results of our study suggest that CSBD shares similar pattern of abnormalities with both OCD and addiction. As one of the first DTI study comparing structural brain differences between CSBD, addictions and OCD, although it reveals new aspects of CSBD, it is insufficient to determine whether CSBD resembles more an addiction or OCD. Further research, especially comparing directly individuals with all three disorders may provide more conclusive results.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Lewczuk202133302242,
  title = {Variability of Pornographic Content Consumed and Longest Session of Pornography Use Associated With Treatment Seeking and Problematic Sexual Behavior Symptoms.},
  author = {Lewczuk, K and Lesniak, J and Lew-Starowicz, M and Gola, M},
  journal = {Sexual medicine},
  year = {2021},
  doi = {10.1016/j.esxm.2020.10.004},
  pmid = {33302242},
  url = {https://pubmed.ncbi.nlm.nih.gov/33302242/},
  abstract = {Most of the previous studies on problematic pornography use and related behavior have focused on such descriptors of pornography use habits as frequency or time devoted to pornography use. We argue that this constitutes a narrow view and indicators that characterize other aspects of explicit content consumption, namely (i) longest session of pornography viewing (which may be related to binge behavior), as well as (ii) variability of consumed pornographic content, can also be useful indicators. An online study based on a sample of 132 heterosexual men seeking treatment for problematic pornography use, referred by therapists after their initial visit and 437 non-treatment seekers in the control group. The main outcomes of this study are reported longest, non-stop session of viewing pornography, variability in consumed pornographic content (including paraphilic and violent pornography), actual treatment seeking for problematic pornography use and severity of symptoms, and average weekly time devoted to pornography use. Our analysis showed that longest session of viewing pornographic content as well as the variety of consumed pornography influenced the decision to seek treatment and the severity of symptoms even when the sheer amount of time devoted to pornography use was controlled. This is one of the few studies examining the role of engagement in prolonged sessions of pornography use and the variability of consumed pornographic content in the clinical context of problematic sexual behavior. The study's main limitations are its relatively narrow method of operationalization of variability of pornographic content and longest session of pornography viewing, as well as its cross-sectional, online, and anonymous character. As the described factors have an important influence on treatment seeking and the severity of experienced symptoms, they should be considered in the process of assessing compulsive sexual behavior disorder and related symptoms. Lewczuk K, Leśniak J, Lew-Starowicz M, et al. Variability of Pornographic Content Consumed and Longest Session of Pornography Use Associated With Treatment Seeking and Problematic Sexual Behavior Symptoms. Sex Med 2021;9:100276.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Zhang202134691612,
  title = {Tiny noise, big mistakes: adversarial perturbations induce errors in brain-computer interface spellers.},
  author = {Zhang, X and Wu, D and Ding, L and Luo, H and Lin, CT and Jung, TP and Chavarriaga, R},
  journal = {National science review},
  year = {2021},
  doi = {10.1093/nsr/nwaa233},
  pmid = {34691612},
  url = {https://pubmed.ncbi.nlm.nih.gov/34691612/},
  abstract = {An electroencephalogram (EEG)-based brain-computer interface (BCI) speller allows a user to input text to a computer by thought. It is particularly useful to severely disabled individuals, e.g. amyotrophic lateral sclerosis patients, who have no other effective means of communication with another person or a computer. Most studies so far focused on making EEG-based BCI spellers faster and more reliable; however, few have considered their security. This study, for the first time, shows that P300 and steady-state visual evoked potential BCI spellers are very vulnerable, i.e. they can be severely attacked by adversarial perturbations, which are too tiny to be noticed when added to EEG signals, but can mislead the spellers to spell anything the attacker wants. The consequence could range from merely user frustration to severe misdiagnosis in clinical applications. We hope our research can attract more attention to the security of EEG-based BCI spellers, and more broadly, EEG-based BCIs, which has received little attention before.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chen202134059833,
  title = {The trans-ancestral genomic architecture of glycemic traits.},
  author = {Chen, J and Spracklen, CN and Marenne, G and Varshney, A and Corbin, LJ and Luan, J and Willems, SM and Wu, Y and Zhang, X and Horikoshi, M and Boutin, TS and Mägi, R and Waage, J and Li-Gao, R and Chan, KHK and Yao, J and Anasanti, MD and Chu, AY and Claringbould, A and Heikkinen, J and Hong, J and Hottenga, JJ and Huo, S and Kaakinen, MA and Louie, T and März, W and Moreno-Macias, H and Ndungu, A and Nelson, SC and Nolte, IM and North, KE and Raulerson, CK and Ray, D and Rohde, R and Rybin, D and Schurmann, C and Sim, X and Southam, L and Stewart, ID and Wang, CA and Wang, Y and Wu, P and Zhang, W and Ahluwalia, TS and Appel, EVR and Bielak, LF and Brody, JA and Burtt, NP and Cabrera, CP and Cade, BE and Chai, JF and Chai, X and Chang, LC and Chen, CH and Chen, BH and Chitrala, KN and Chiu, YF and de Haan, HG and Delgado, GE and Demirkan, A and Duan, Q and Engmann, J and Fatumo, SA and Gayán, J and Giulianini, F and Gong, JH and Gustafsson, S and Hai, Y and Hartwig, FP and He, J and Heianza, Y and Huang, T and Huerta-Chagoya, A and Hwang, MY and Jensen, RA and Kawaguchi, T and Kentistou, KA and Kim, YJ and Kleber, ME and Kooner, IK and Lai, S and Lange, LA and Langefeld, CD and Lauzon, M and Li, M and Ligthart, S and Liu, J and Loh, M and Long, J and Lyssenko, V and Mangino, M and Marzi, C and Montasser, ME and Nag, A and Nakatochi, M and Noce, D and Noordam, R and Pistis, G and Preuss, M and Raffield, L and Rasmussen-Torvik, LJ and Rich, SS and Robertson, NR and Rueedi, R and Ryan, K and Sanna, S and Saxena, R and Schraut, KE and Sennblad, B and Setoh, K and Smith, AV and Sparsø, T and Strawbridge, RJ and Takeuchi, F and Tan, J and Trompet, S and van den Akker, E and van der Most, PJ and Verweij, N and Vogel, M and Wang, H and Wang, C and Wang, N and Warren, HR and Wen, W and Wilsgaard, T and Wong, A and Wood, AR and Xie, T and Zafarmand, MH and Zhao, JH and Zhao, W and Amin, N and Arzumanyan, Z and Astrup, A and Bakker, SJL and Baldassarre, D and Beekman, M and Bergman, RN and Bertoni, A and Blüher, M and Bonnycastle, LL and Bornstein, SR and Bowden, DW and Cai, Q and Campbell, A and Campbell, H and Chang, YC and de Geus, EJC and Dehghan, A and Du, S and Eiriksdottir, G and Farmaki, AE and Frånberg, M and Fuchsberger, C and Gao, Y and Gjesing, AP and Goel, A and Han, S and Hartman, CA and Herder, C and Hicks, AA and Hsieh, CH and Hsueh, WA and Ichihara, S and Igase, M and Ikram, MA and Johnson, WC and Jørgensen, ME and Joshi, PK and Kalyani, RR and Kandeel, FR and Katsuya, T and Khor, CC and Kiess, W and Kolcic, I and Kuulasmaa, T and Kuusisto, J and Läll, K and Lam, K and Lawlor, DA and Lee, NR and Lemaitre, RN and Li, H and Lifelines Cohort Study and Lin, SY and Lindström, J and Linneberg, A and Liu, J and Lorenzo, C and Matsubara, T and Matsuda, F and Mingrone, G and Mooijaart, S and Moon, S and Nabika, T and Nadkarni, GN and Nadler, JL and Nelis, M and Neville, MJ and Norris, JM and Ohyagi, Y and Peters, A and Peyser, PA and Polasek, O and Qi, Q and Raven, D and Reilly, DF and Reiner, A and Rivideneira, F and Roll, K and Rudan, I and Sabanayagam, C and Sandow, K and Sattar, N and Schürmann, A and Shi, J and Stringham, HM and Taylor, KD and Teslovich, TM and Thuesen, B and Timmers, PRHJ and Tremoli, E and Tsai, MY and Uitterlinden, A and van Dam, RM and van Heemst, D and van Hylckama Vlieg, A and van Vliet-Ostaptchouk, JV and Vangipurapu, J and Vestergaard, H and Wang, T and Willems van Dijk, K and Zemunik, T and Abecasis, GR and Adair, LS and Aguilar-Salinas, CA and Alarcón-Riquelme, ME and An, P and Aviles-Santa, L and Becker, DM and Beilin, LJ and Bergmann, S and Bisgaard, H and Black, C and Boehnke, M and Boerwinkle, E and Böhm, BO and Bønnelykke, K and Boomsma, DI and Bottinger, EP and Buchanan, TA and Canouil, M and Caulfield, MJ and Chambers, JC and Chasman, DI and Chen, YI and Cheng, CY and Collins, FS and Correa, A and Cucca, F and de Silva, HJ and Dedoussis, G and Elmståhl, S and Evans, MK and Ferrannini, E and Ferrucci, L and Florez, JC and Franks, PW and Frayling, TM and Froguel, P and Gigante, B and Goodarzi, MO and Gordon-Larsen, P and Grallert, H and Grarup, N and Grimsgaard, S and Groop, L and Gudnason, V and Guo, X and Hamsten, A and Hansen, T and Hayward, C and Heckbert, SR and Horta, BL and Huang, W and Ingelsson, E and James, PS and Jarvelin, MR and Jonas, JB and Jukema, JW and Kaleebu, P and Kaplan, R and Kardia, SLR and Kato, N and Keinanen-Kiukaanniemi, SM and Kim, BJ and Kivimaki, M and Koistinen, HA and Kooner, JS and Körner, A and Kovacs, P and Kuh, D and Kumari, M and Kutalik, Z and Laakso, M and Lakka, TA and Launer, LJ and Leander, K and Li, H and Lin, X and Lind, L and Lindgren, C and Liu, S and Loos, RJF and Magnusson, PKE and Mahajan, A and Metspalu, A and Mook-Kanamori, DO and Mori, TA and Munroe, PB and Njølstad, I and O'Connell, JR and Oldehinkel, AJ and Ong, KK and Padmanabhan, S and Palmer, CNA and Palmer, ND and Pedersen, O and Pennell, CE and Porteous, DJ and Pramstaller, PP and Province, MA and Psaty, BM and Qi, L and Raffel, LJ and Rauramaa, R and Redline, S and Ridker, PM and Rosendaal, FR and Saaristo, TE and Sandhu, M and Saramies, J and Schneiderman, N and Schwarz, P and Scott, LJ and Selvin, E and Sever, P and Shu, XO and Slagboom, PE and Small, KS and Smith, BH and Snieder, H and Sofer, T and Sørensen, TIA and Spector, TD and Stanton, A and Steves, CJ and Stumvoll, M and Sun, L and Tabara, Y and Tai, ES and Timpson, NJ and Tönjes, A and Tuomilehto, J and Tusie, T and Uusitupa, M and van der Harst, P and van Duijn, C and Vitart, V and Vollenweider, P and Vrijkotte, TGM and Wagenknecht, LE and Walker, M and Wang, YX and Wareham, NJ and Watanabe, RM and Watkins, H and Wei, WB and Wickremasinghe, AR and Willemsen, G and Wilson, JF and Wong, TY and Wu, JY and Xiang, AH and Yanek, LR and Yengo, L and Yokota, M and Zeggini, E and Zheng, W and Zonderman, AB and Rotter, JI and Gloyn, AL and McCarthy, MI and Dupuis, J and Meigs, JB and Scott, RA and Prokopenko, I and Leong, A and Liu, CT and Parker, SCJ and Mohlke, KL and Langenberg, C and Wheeler, E and Morris, AP and Barroso, I and Meta-Analysis of Glucose and Insulin-related Traits Consortium (MAGIC)},
  journal = {Nature genetics},
  year = {2021},
  doi = {10.1038/s41588-021-00852-9},
  pmid = {34059833},
  url = {https://pubmed.ncbi.nlm.nih.gov/34059833/},
  abstract = {Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10 -8 ), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.},
  note = {PubMed query source: Ying Wu}
}

@article{MartnezCancino202132289453,
  title = {The open EEGLAB portal Interface: High-Performance computing with EEGLAB.},
  author = {Martínez-Cancino, R and Delorme, A and Truong, D and Artoni, F and Kreutz-Delgado, K and Sivagnanam, S and Yoshimoto, K and Majumdar, A and Makeig, S},
  journal = {NeuroImage},
  year = {2021},
  doi = {10.1016/j.neuroimage.2020.116778},
  pmid = {32289453},
  url = {https://pubmed.ncbi.nlm.nih.gov/32289453/},
  abstract = {EEGLAB signal processing environment is currently the leading open-source software for processing electroencephalographic (EEG) data. The Neuroscience Gateway (NSG, nsgportal.org) is a web and API-based portal allowing users to easily run a variety of neuroscience-related software on high-performance computing (HPC) resources in the U.S. XSEDE network. We have reported recently (Delorme et al., 2019) on the Open EEGLAB Portal expansion of the free NSG services to allow the neuroscience community to build and run MATLAB pipelines using the EEGLAB tool environment. We are now releasing an EEGLAB plug-in, nsgportal, that interfaces EEGLAB with NSG directly from within EEGLAB running on MATLAB on any personal lab computer. The plug-in features a flexible MATLAB graphical user interface (GUI) that allows users to easily submit, interact with, and manage NSG jobs, and to retrieve and examine their results. Command line nsgportal tools supporting these GUI functionalities allow EEGLAB users and plug-in tool developers to build largely automated functions and workflows that include optional NSG job submission and processing. Here we present details on nsgportal implementation and documentation, provide user tutorials on example applications, and show sample test results comparing computation times using HPC versus laptop processing.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wen202133373308,
  title = {The Current Research of Combining Multi-Modal Brain-Computer Interfaces With Virtual Reality.},
  author = {Wen, D and Liang, B and Zhou, Y and Chen, H and Jung, TP},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2021},
  doi = {10.1109/JBHI.2020.3047836},
  pmid = {33373308},
  url = {https://pubmed.ncbi.nlm.nih.gov/33373308/},
  abstract = {Combing brain-computer interfaces (BCI) and virtual reality (VR) is a novel technique in the field of medical rehabilitation and game entertainment. However, the limitations of BCI such as a limited number of action commands and low accuracy hinder the widespread use of BCI-VR. Recent studies have used hybrid BCIs that combine multiple BCI paradigms and/or the multi-modal biosensors to alleviate these issues, which may become the mainstream of BCIs in the future. The main purpose of this review is to discuss the current status of multi-modal BCI-VR. This study first reviewed the development of the BCI-VR, and explored the advantages and disadvantages of incorporating eye tracking, motor capture, and myoelectric sensing into the BCI-VR system. Then, this study discussed the development trend of the multi-modal BCI-VR, hoping to provide a pathway for further research in this field.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Miyakoshi202133497490,
  title = {The AudioMaze: An EEG and motion capture study of human spatial navigation in sparse augmented reality.},
  author = {Miyakoshi, M and Gehrke, L and Gramann, K and Makeig, S and Iversen, J},
  journal = {The European journal of neuroscience},
  year = {2021},
  doi = {10.1111/ejn.15131},
  pmid = {33497490},
  url = {https://pubmed.ncbi.nlm.nih.gov/33497490/},
  abstract = {Spatial navigation is one of the fundamental cognitive functions central to survival in most animals. Studies in humans investigating the neural foundations of spatial navigation traditionally use stationary, desk-top protocols revealing the hippocampus, parahippocampal place area (PPA), and retrosplenial complex to be involved in navigation. However, brain dynamics, while freely navigating the real world remain poorly understood. To address this issue, we developed a novel paradigm, the AudioMaze, in which participants freely explore a room-sized virtual maze, while EEG is recorded synchronized to motion capture. Participants (n = 16) were blindfolded and explored different mazes, each in three successive trials, using their right hand as a probe to "feel" for virtual maze walls. When their hand "neared" a virtual wall, they received directional noise feedback. Evidence for spatial learning include shortening of time spent and an increase of movement velocity as the same maze was repeatedly explored. Theta-band EEG power in or near the right lingual gyrus, the posterior portion of the PPA, decreased across trials, potentially reflecting the spatial learning. Effective connectivity analysis revealed directed information flow from the lingual gyrus to the midcingulate cortex, which may indicate an updating process that integrates spatial information with future action. To conclude, we found behavioral evidence of navigational learning in a sparse-AR environment, and a neural correlate of navigational learning was found near the lingual gyrus.},
  note = {PubMed query source: Scott Makeig}
}

@article{Ko202133291083,
  title = {SSVEP-assisted RSVP brain-computer interface paradigm for multi-target classification.},
  author = {Ko, LW and Sandeep Vara Sankar, D and Huang, Y and Lu, YC and Shaw, S and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/abd1c0},
  pmid = {33291083},
  url = {https://pubmed.ncbi.nlm.nih.gov/33291083/},
  abstract = {Brain-computer Interface (BCI) is actively involved in optimizing the communication medium between the human brain and external devices. Objective. Rapid serial visual presentation (RSVP) is a robust and highly efficient BCI technique in recognizing target objects but suffers from limited target selections. Hybrid BCI systems that combine steady-state visual evoked potential (SSVEP) and RSVP can mitigate this limitation and allow users to operate on multiple targets. Approach. This study proposes a novel hybrid SSVEP-RSVP BCI to improve the performance of classifying the target/non-target objects in a multi-target scenario. In this paradigm, SSVEP stimulation helps in identifying the user's focus location and RSVP stimuli that elicit event-related potentials differentiate target and non-target objects. Main results. The proposed model achieved an offline accuracy of 81.59% by using 12 electroencephalography (EEG) channels and an online (real-time) accuracy of 78.10% when only four EEG channels are considered. Further, the biomarkers of physiological states are analyzed to assess the cognitive states (mental fatigue and user attention) of the participants based on resting theta and alpha band powers. The results indicate an inverse relationship between the BCI performance and the resting EEG power, validating that the subjects' performance is affected by physiological states for long-term use of the BCI. Significance. Our findings demonstrate that the combination of SSVEP and RSVP stimuli improves the BCI performance and further enhances the possibility of performing multiple user command tasks, which are inevitable in real-world applications. Additionally, the cognitive state biomarkers discussed imply the need for an efficient and attractive experimental paradigm that reduces the physiological state disparities and provide enhanced BCI performance.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202134367361,
  title = {Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.},
  author = {Xu, L and Xu, M and Jung, TP and Ming, D},
  journal = {Cognitive neurodynamics},
  year = {2021},
  doi = {10.1007/s11571-021-09676-z},
  pmid = {34367361},
  url = {https://pubmed.ncbi.nlm.nih.gov/34367361/},
  abstract = {A brain-computer interface (BCI) can connect humans and machines directly and has achieved successful applications in the past few decades. Many new BCI paradigms and algorithms have been developed in recent years. Therefore, it is necessary to review new progress in BCIs. This paper summarizes progress for EEG-based BCIs from the perspective of encoding paradigms and decoding algorithms, which are two key elements of BCI systems. Encoding paradigms are grouped by their underlying neural meachanisms, namely sensory- and motor-related, vision-related, cognition-related and hybrid paradigms. Decoding algorithms are reviewed in four categories, namely decomposition algorithms, Riemannian geometry, deep learning and transfer learning. This review will provide a comprehensive overview of both modern primary paradigms and algorithms, making it helpful for those who are developing BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Do202133544675,
  title = {Retrosplenial Segregation Reflects the Navigation Load During Ambulatory Movement.},
  author = {Do, TN and Jung, TP and Lin, CT},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2021},
  doi = {10.1109/TNSRE.2021.3057384},
  pmid = {33544675},
  url = {https://pubmed.ncbi.nlm.nih.gov/33544675/},
  abstract = {Spatial navigation is a complex cognitive process based on vestibular, proprioceptive, and visualcues that are integrated and processed by an extensive network of brain areas. The retrosplenial complex (RSC) is an integral part of coordination and translation between spatial reference frames. Previous studies have demonstrated that the RSC is active during a spatial navigation tasks. The specifics of RSC activity under various navigation loads, however, are still not characterized. This study investigated the local information processed by the RSC under various navigation load conditions manipulated by the number of turns in the physical navigation setup. The results showed that the local information processed via the RSC, which was reflected by the segregation network, was higher when the number of turns increased, suggesting that RSC activity is associated with the navigation task load. The present findings shed light on how the brain processes spatial information in a physical navigation task.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu202134940256,
  title = {Resting-State EEG Signal for Major Depressive Disorder Detection: A Systematic Validation on a Large and Diverse Dataset.},
  author = {Wu, CT and Huang, HC and Huang, S and Chen, IM and Liao, SC and Chen, CK and Lin, C and Lee, SH and Chen, MH and Tsai, CF and Weng, CH and Ko, LW and Jung, TP and Liu, YH},
  journal = {Biosensors},
  year = {2021},
  doi = {10.3390/bios11120499},
  pmid = {34940256},
  url = {https://pubmed.ncbi.nlm.nih.gov/34940256/},
  abstract = {Major depressive disorder (MDD) is a global healthcare issue and one of the leading causes of disability. Machine learning combined with non-invasive electroencephalography (EEG) has recently been shown to have the potential to diagnose MDD. However, most of these studies analyzed small samples of participants recruited from a single source, raising serious concerns about the generalizability of these results in clinical practice. Thus, it has become critical to re-evaluate the efficacy of various common EEG features for MDD detection across large and diverse datasets. To address this issue, we collected resting-state EEG data from 400 participants across four medical centers and tested classification performance of four common EEG features: band power (BP), coherence, Higuchi's fractal dimension, and Katz's fractal dimension. Then, a sequential backward selection (SBS) method was used to determine the optimal subset. To overcome the large data variability due to an increased data size and multi-site EEG recordings, we introduced the conformal kernel (CK) transformation to further improve the MDD as compared with the healthy control (HC) classification performance of support vector machine (SVM). The results show that (1) coherence features account for 98% of the optimal feature subset; (2) the CK-SVM outperforms other classifiers such as K-nearest neighbors (K-NN), linear discriminant analysis (LDA), and SVM; (3) the combination of the optimal feature subset and CK-SVM achieves a high five-fold cross-validation accuracy of 91.07% on the training set (140 MDD and 140 HC) and 84.16% on the independent test set (60 MDD and 60 HC). The current results suggest that the coherence-based connectivity is a more reliable feature for achieving high and generalizable MDD detection performance in real-life clinical practice.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cummings202133679342,
  title = {Phonological Underspecification: An Explanation for How a Rake Can Become Awake.},
  author = {Cummings, AE and Wu, YC and Ogiela, DA},
  journal = {Frontiers in human neuroscience},
  year = {2021},
  doi = {10.3389/fnhum.2021.585817},
  pmid = {33679342},
  url = {https://pubmed.ncbi.nlm.nih.gov/33679342/},
  abstract = {Neural markers, such as the mismatch negativity (MMN), have been used to examine the phonological underspecification of English feature contrasts using the Featurally Underspecified Lexicon (FUL) model. However, neural indices have not been examined within the approximant phoneme class, even though there is evidence suggesting processing asymmetries between liquid (e.g., /ɹ/) and glide (e.g., /w/) phonemes. The goal of this study was to determine whether glide phonemes elicit electrophysiological asymmetries related to [consonantal] underspecification when contrasted with liquid phonemes in adult English speakers. Specifically, /ɹɑ/ is categorized as [+consonantal] while /wɑ/ is not specified [i.e., (-consonantal)]. Following the FUL framework, if /w/ is less specified than /ɹ/, the former phoneme should elicit a larger MMN response than the latter phoneme. Fifteen English-speaking adults were presented with two syllables, /ɹɑ/ and /wɑ/, in an event-related potential (ERP) oddball paradigm in which both syllables served as the standard and deviant stimulus in opposite stimulus sets. Three types of analyses were used: (1) traditional mean amplitude measurements; (2) cluster-based permutation analyses; and (3) event-related spectral perturbation (ERSP) analyses. The less specified /wɑ/ elicited a large MMN, while a much smaller MMN was elicited by the more specified /ɹɑ/. In the standard and deviant ERP waveforms, /wɑ/ elicited a significantly larger negative response than did /ɹɑ/. Theta activity elicited by /ɹɑ/ was significantly greater than that elicited by /wɑ/ in the 100-300 ms time window. Also, low gamma activation was significantly lower for /ɹɑ/ vs. /wɑ/ deviants over the left hemisphere, as compared to the right, in the 100-150 ms window. These outcomes suggest that the [consonantal] feature follows the underspecification predictions of FUL previously tested with the place of articulation and voicing features. Thus, this study provides new evidence for phonological underspecification. Moreover, as neural oscillation patterns have not previously been discussed in the underspecification literature, the ERSP analyses identified potential new indices of phonological underspecification.},
  note = {PubMed query source: Ying Wu}
}

@article{Riley202134399133,
  title = {Pervasiveness of speech-language disorders and fatigue in stroke: A systematic scoping review.},
  author = {Riley, EA and Hart, E and Preston, JL and Wu, Y and Ashaie, S},
  journal = {Journal of communication disorders},
  year = {2021},
  doi = {10.1016/j.jcomdis.2021.106145},
  pmid = {34399133},
  url = {https://pubmed.ncbi.nlm.nih.gov/34399133/},
  abstract = {After a stroke, it is highly likely that an individual will experience substantial fatigue that can significantly affect recovery and function; stroke survivors also have more than a 50% chance of having at least one speech-language disorder. Current reviews of post-stroke fatigue have not provided evidence focused on speech-language disorders or the potential influence they may have on post-stroke fatigue and related recovery. The aim of this review was to determine how speech-language disorders are represented in post-stroke fatigue research and to catalogue methods used to identify speech-language disorders and measure fatigue. A systematic scoping review was conducted to identify studies measuring post-stroke fatigue. To identify these studies, a comprehensive literature search was conducted using relevant databases and grey literature sources, followed by several stages of review that adhered to PRISMA guidelines. We evaluated these studies using pre-established eligibility criteria and extracted data regarding the inclusion/exclusion of persons with speech-language disorders and the assessment methods used. The scoping review analysis was conducted on 161 studies. Of these, 41 (26%) excluded all speech-language disorders, 71 (44%) excluded severe speech-language disorders, and 49 (30%) included participants with speech-language disorders. Of the 120 studies that did not explicitly exclude all speech-language disorders, only 34 were confirmed to report data from at least one person with a speech-language disorder. Further, only 5 studies reported data that could be used to determine a relationship between speech-language disorders and fatigue. Persons with speech-language disorders are underrepresented in post-stroke fatigue research and very few studies have examined the relationship between post-stroke fatigue and speech-language disorders, limiting conclusions that can be drawn. This is problematic because medical professionals relying on this evidence to guide clinical practice are likely to be treating individuals with co-occurring fatigue and speech-language disorders and the current research does not provide enough information about the potential impact of fatigue on speech-language disorders or vice versa. To bridge this gap, we suggest methods of assessment that could provide ways to more accurately 1) reflect the real population in post-stroke fatigue studies, and 2) measure and document fatigue in post-stroke speech-language disorder studies. We also propose the Filter-Funnel Model of Post-Stroke Fatigue, which considers the role of speech-language disorders and communicative demands in the context of post-stroke fatigue.},
  note = {PubMed query source: Ying Wu}
}

@article{Chuang202134706357,
  title = {Near-zero phase-lag hyperscanning in a novel wireless EEG system.},
  author = {Chuang, CH and Lu, SW and Chao, YP and Peng, PH and Hsu, HC and Hung, CC and Chang, CL and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/ac33e6},
  pmid = {34706357},
  url = {https://pubmed.ncbi.nlm.nih.gov/34706357/},
  abstract = {Objective . Hyperscanning is an emerging technology that concurrently scans the neural dynamics of multiple individuals to study interpersonal interactions. In particular, hyperscanning with electroencephalography (EEG) is increasingly popular owing to its mobility and its ability to allow studying social interactions in naturalistic settings at the millisecond scale. Approach. To align multiple EEG time series with sophisticated event markers in a single time domain, a precise and unified timestamp is required for stream synchronization. This study proposes a clock-synchronized method that uses a custom-made RJ45 cable to coordinate the sampling between wireless EEG amplifiers to prevent incorrect estimation of interbrain connectivity due to asynchronous sampling. In this method, analog-to-digital converters are driven by the same sampling clock. Additionally, two clock-synchronized amplifiers leverage additional radio frequency channels to keep the counter of their receiving dongles updated, which guarantees that binding event markers received by the dongle with the EEG time series have the correct timestamp. Main results. The results of two simulation experiments and one video gaming experiment reveal that the proposed method ensures synchronous sampling in a system with multiple EEG devices, achieving near-zero phase lag and negligible amplitude difference between the signals. Significance. According to all of the signal-similarity metrics, the suggested method is a promising option for wireless EEG hyperscanning and can be utilized to precisely assess the interbrain couplings underlying social-interaction behaviors.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Zhang202132396071,
  title = {Mining Interpretable AOG Representations From Convolutional Networks via Active Question Answering.},
  author = {Zhang, Q and Ren, J and Huang, G and Cao, R and Wu, YN and Zhu, SC},
  journal = {IEEE transactions on pattern analysis and machine intelligence},
  year = {2021},
  doi = {10.1109/TPAMI.2020.2993147},
  pmid = {32396071},
  url = {https://pubmed.ncbi.nlm.nih.gov/32396071/},
  abstract = {In this paper, we present a method to mine object-part patterns from conv-layers of a pre-trained convolutional neural network (CNN). The mined object-part patterns are organized by an And-Or graph (AOG). This interpretable AOG representation consists of a four-layer semantic hierarchy, i.e., semantic parts, part templates, latent patterns, and neural units. The AOG associates each object part with certain neural units in feature maps of conv-layers. The AOG is constructed with very few annotations (e.g., 3-20) of object parts. We develop a question-answering (QA) method that uses active human-computer communications to mine patterns from a pre-trained CNN, in order to explain features in conv-layers incrementally. During the learning process, our QA method uses the current AOG for part localization. The QA method actively identifies objects, whose feature maps cannot be explained by the AOG. Then, our method asks people to annotate parts on the unexplained objects, and uses answers to discover CNN patterns corresponding to newly labeled parts. In this way, our method gradually grows new branches and refines existing branches on the AOG to semanticize CNN representations. In experiments, our method exhibited a high learning efficiency. Our method used about 1/6- 1/3 of the part annotations for training, but achieved similar or better part-localization performance than fast-RCNN methods.},
  note = {PubMed query source: Ying Wu}
}

@article{Szumska202132223344,
  title = {Mindfulness-based cognitive therapy reduces clinical symptoms, but do not change frontal alpha asymmetry in people with major depression disorder.},
  author = {Szumska, I and Gola, M and Rusanowska, M and Krajewska, M and Żygierewicz, J and Krejtz, I and Nezlek, JB and Holas, P},
  journal = {The International journal of neuroscience},
  year = {2021},
  doi = {10.1080/00207454.2020.1748621},
  pmid = {32223344},
  url = {https://pubmed.ncbi.nlm.nih.gov/32223344/},
  abstract = {Mindfulness-based cognitive therapy (MBCT) has demonstrated to be successful in the reduction of relapse rates in patients with recurrent major depressive disorder (MDD). Little is known if MBCT is effective for treating individuals with current MDD episode and about underlying psychophysiological mechanisms of symptoms reduction. The aim of the present study was to assess effects of MBCT on depressed individuals in terms of reduction of depressive and anxiety symptoms and to evaluate if this therapeutic improvement would be reflected on neurophysiological level by shift in frontal alpha asymmetry (FAA). We studied 20 individuals with current MDD. Participants were randomly assigned either to waiting list or 8-week MBCT. Before and after the treatment we have assessed depression, anxiety, and FAA in resting-state electroencephalogram (EEG) - an indicator of approach vs. withdrawal-related response dispositions and a vulnerability factor of MDD. In line with previous findings, reduction of depressive and anxiety symptoms, but no change in mean values of FAA in MBCT group was found. These results provide a support for the beneficial effects of MBCT in current MDD treatment, however, they do not support the hypothesis on alpha asymmetry change as a neural correlate of MDD improvement.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Pernet202133624219,
  title = {Mindfulness related changes in grey matter: a systematic review and meta-analysis.},
  author = {Pernet, CR and Belov, N and Delorme, A and Zammit, A},
  journal = {Brain imaging and behavior},
  year = {2021},
  doi = {10.1007/s11682-021-00453-4},
  pmid = {33624219},
  url = {https://pubmed.ncbi.nlm.nih.gov/33624219/},
  abstract = {Knowing target regions undergoing strfuncti changes caused by behavioural interventions is paramount in evaluating the effectiveness of such practices. Here, using a systematic review approach, we identified 25 peer-reviewed magnetic resonance imaging (MRI) studies demonstrating grey matter changes related to mindfulness meditation. An activation likelihood estimation (ALE) analysis (n = 16) revealed the right anterior ventral insula as the only significant region with consistent effect across studies, whilst an additional functional connectivity analysis indicates that both left and right insulae, and the anterior cingulate gyrus with adjacent paracingulate gyri should also be considered in future studies. Statistical meta-analyses suggest medium to strong effect sizes from Cohen's d ~ 0.8 in the right insula to ~ 1 using maxima across the whole brain. The systematic review revealed design issues with selection, information, attrition and confirmation biases, in addition to weak statistical power. In conclusion, our analyses show that mindfulness meditation practice does induce grey matter changes but also that improvements in methodology are needed to establish mindfulness as a therapeutic intervention.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Ng202134777144,
  title = {Mindfulness Training Associated With Resting-State Electroencephalograms Dynamics in Novice Practitioners via Mindful Breathing and Body-Scan.},
  author = {Ng, HH and Wu, CW and Huang, FY and Cheng, YT and Guu, SF and Huang, CM and Hsu, CF and Chao, YP and Jung, TP and Chuang, CH},
  journal = {Frontiers in psychology},
  year = {2021},
  doi = {10.3389/fpsyg.2021.748584},
  pmid = {34777144},
  url = {https://pubmed.ncbi.nlm.nih.gov/34777144/},
  abstract = {Objectives:  Mindfulness-based stress reduction has been proven to improve mental health and quality of life. This study examined how mindfulness training and various types of mindfulness practices altered brain activity.  Methods : Specifically, the spectral powers of scalp electroencephalography of the mindfulness-based stress reduction (MBSR) group ( n =17) who underwent an 8-week MBSR training-including mindful breathing and body-scan-were evaluated and compared with those of the waitlist controls ( n =14).  Results:  Empirical results indicated that the post-intervention effect of MBSR significantly elevated the resting-state beta powers and reduced resting-state delta powers in both practices; such changes were not observed in the waitlist control. Compared with mindful breathing, body-scanning resulted in an overall decline in electroencephalograms (EEG) spectral powers at both delta and low-gamma bands among trained participants.  Conclusion : Together with our preliminary data of expert mediators, the aforementioned spectral changes were salient after intervention, but mitigated along with expertise. Additionally, after receiving training, the MBSR group's mindfulness and emotion regulation levels improved significantly, which were correlated with the EEG spectral changes in the theta, alpha, and low-beta bands. The results supported that MBSR might function as a unique internal processing tool that involves increased vigilant capability and induces alterations similar to other cognitive training.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gouraud202138236482,
  title = {Mind Wandering Influences EEG Signal in Complex Multimodal Environments.},
  author = {Gouraud, J and Delorme, A and Berberian, B},
  journal = {Frontiers in neuroergonomics},
  year = {2021},
  doi = {10.3389/fnrgo.2021.625343},
  pmid = {38236482},
  url = {https://pubmed.ncbi.nlm.nih.gov/38236482/},
  abstract = {The phenomenon of mind wandering (MW), as a family of experiences related to internally directed cognition, heavily influences vigilance evolution. In particular, humans in teleoperations monitoring partially automated fleet before assuming manual control whenever necessary may see their attention drift due to internal sources; as such, it could play an important role in the emergence of out-of-the-loop (OOTL) situations and associated performance problems. To follow, quantify, and mitigate this phenomenon, electroencephalogram (EEG) systems already demonstrated robust results. As MW creates an attentional decoupling, both ERPs and brain oscillations are impacted. However, the factors influencing these markers in complex environments are still not fully understood. In this paper, we specifically addressed the possibility of gradual emergence of attentional decoupling and the differences created by the sensory modality used to convey targets. Eighteen participants were asked to (1) supervise an automated drone performing an obstacle avoidance task (visual task) and (2) respond to infrequent beeps as fast as possible (auditory task). We measured event-related potentials and alpha waves through EEG. We also added a 40-Hz amplitude modulated brown noise to evoke steady-state auditory response (ASSR). Reported MW episodes were categorized between task-related and task-unrelated episodes. We found that N1 ERP component elicited by beeps had lower amplitude during task-unrelated MW, whereas P3 component had higher amplitude during task-related MW, compared with other attentional states. Focusing on parieto-occipital regions, alpha-wave activity was higher during task-unrelated MW compared with others. These results support the decoupling hypothesis for task-unrelated MW but not task-related MW, highlighting possible variations in the "depth" of decoupling depending on MW episodes. Finally, we found no influence of attentional states on ASSR amplitude. We discuss possible reasons explaining why. Results underline both the ability of EEG to track and study MW in laboratory tasks mimicking ecological environments, as well as the complex influence of perceptual decoupling on operators' behavior and, in particular, EEG measures.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Brandmeyer202132598855,
  title = {Meditation and the Wandering Mind: A Theoretical Framework of Underlying Neurocognitive Mechanisms.},
  author = {Brandmeyer, T and Delorme, A},
  journal = {Perspectives on psychological science : a journal of the Association for Psychological Science},
  year = {2021},
  doi = {10.1177/1745691620917340},
  pmid = {32598855},
  url = {https://pubmed.ncbi.nlm.nih.gov/32598855/},
  abstract = {During the practice of meditation, the tendency of the mind to wander away from the object of focus is ubiquitous. The occurrence of mind wandering in the context of meditation provides individuals a unique and intimate opportunity to closely examine the nature of the wandering mind by cultivating an awareness of ongoing thought patterns, while simultaneously aiming to cultivate equanimity (evenness of temper or disposition) and compassion toward the content of thoughts, interpretations, and bodily sensations. In this article we provide a theoretical framework that highlights the neurocognitive mechanisms by which contemplative practices influence the neural and phenomenological processes underlying spontaneous thought. Our theoretical model focuses on several converging mechanisms: the role of meta-awareness in facilitating an increased moment-to-moment awareness of spontaneous thought processes, the effects of meditation practice on key structures underlying both the top-down cognitive processes and bottom-up sensory processes implicated in attention and emotion regulation, and the influence of contemplative practice on the neural substrates underlying perception and perceptual decoupling.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Jeng202132960770,
  title = {Low-Dimensional Subject Representation-Based Transfer Learning in EEG Decoding.},
  author = {Jeng, PY and Wei, CS and Jung, TP and Wang, LC},
  journal = {IEEE journal of biomedical and health informatics},
  year = {2021},
  doi = {10.1109/JBHI.2020.3025865},
  pmid = {32960770},
  url = {https://pubmed.ncbi.nlm.nih.gov/32960770/},
  abstract = {Recently, the advances in passive brain-computer interfaces (BCIs) based on electroencephalogram (EEG) have shed light on real-world neuromonitoring technologies. However, human variability in the EEG activities hinders the development of practical applications of EEG-based BCI. To tackle this problem, many transfer-learning techniques perform supervised calibration. This kind of calibration approach requires task-relevant data, which is impractical in real-life scenarios such as drowsiness during driving. This study presents a transfer-learning framework for EEG decoding based on the low-dimensional representations of subjects learned from the pre-trial EEG. Tensor decomposition was applied to the pre-trial EEG of subjects to extract the underlying characteristics in subject, spatial, and spectral domains. Then, the proposed framework assessed the characteristics to obtain the low-dimensional subject representations such that the subjects with similar brain dynamics can be identified. This method can leverage the existing data from other users, and a small number of data from a rapid, non-task, unsupervised calibration from a new user to build an accurate BCI. Our results demonstrated that, in terms of prediction accuracy, the proposed low-dimensional subject representation-based transfer learning (LDSR-TL) framework outperformed the random selection, and the Riemannian manifold approach in cognitive-state tracking, while requiring fewer training data. The results can greatly improve the practicability, and usability of EEG-based BCI in the real world.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Miao202133819158,
  title = {Learning Common Time-Frequency-Spatial Patterns for Motor Imagery Classification.},
  author = {Miao, Y and Jin, J and Daly, I and Zuo, C and Wang, X and Cichocki, A and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2021},
  doi = {10.1109/TNSRE.2021.3071140},
  pmid = {33819158},
  url = {https://pubmed.ncbi.nlm.nih.gov/33819158/},
  abstract = {The common spatial patterns (CSP) algorithm is the most popular spatial filtering method applied to extract electroencephalogram (EEG) features for motor imagery (MI) based brain-computer interface (BCI) systems. The effectiveness of the CSP algorithm depends on optimal selection of the frequency band and time window from the EEG. Many algorithms have been designed to optimize frequency band selection for CSP, while few algorithms seek to optimize the time window. This study proposes a novel framework, termed common time-frequency-spatial patterns (CTFSP), to extract sparse CSP features from multi-band filtered EEG data in multiple time windows. Specifically, the whole MI period is first segmented into multiple subseries using a sliding time window approach. Then, sparse CSP features are extracted from multiple frequency bands in each time window. Finally, multiple support vector machine (SVM) classifiers with the Radial Basis Function (RBF) kernel are trained to identify the MI tasks and the voting result of these classifiers determines the final output of the BCI. This study applies the proposed CTFSP algorithm to three public EEG datasets (BCI competition III dataset IVa, BCI competition III dataset IIIa, and BCI competition IV dataset 1) to validate its effectiveness, compared against several other state-of-the-art methods. The experimental results demonstrate that the proposed algorithm is a promising candidate for improving the performance of MI-BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Jurgiel202133977267,
  title = {Inhibitory control in children with tic disorder: aberrant fronto-parietal network activity and connectivity.},
  author = {Jurgiel, J and Miyakoshi, M and Dillon, A and Piacentini, J and Makeig, S and Loo, SK},
  journal = {Brain communications},
  year = {2021},
  doi = {10.1093/braincomms/fcab067},
  pmid = {33977267},
  url = {https://pubmed.ncbi.nlm.nih.gov/33977267/},
  abstract = {Chronic tic disorders, including Tourette syndrome, are typically thought to have deficits in cognitive inhibition and top down cognitive control due to the frequent and repetitive occurrence of tics, yet studies reporting task performance results have been equivocal. Despite similar behavioural performance, individuals with chronic tic disorder have exhibited aberrant patterns of neural activation in multiple frontal and parietal regions relative to healthy controls during inhibitory control paradigms. In addition to these top down attentional control regions, widespread alterations in brain activity across multiple neural networks have been reported. There is a dearth, however, of studies examining event-related connectivity during cognitive inhibitory paradigms among affected individuals. The goal of this study was to characterize neural oscillatory activity and effective connectivity, using a case-control design, among children with and without chronic tic disorder during performance of a cognitive inhibition task. Electroencephalogram data were recorded in a cohort of children aged 8-12 years old (60 with chronic tic disorder, 35 typically developing controls) while they performed a flanker task. While task accuracy did not differ by diagnosis, children with chronic tic disorder displayed significant cortical source-level, event-related spectral power differences during incongruent flanker trials, which required inhibitory control. Specifically, attenuated broad band oscillatory power modulation within the anterior cingulate cortex was observed relative to controls. Whole brain effective connectivity analyses indicated that children with chronic tic disorder exhibit greater information flow between the anterior cingulate and other fronto-parietal network hubs (midcingulate cortex and precuneus) relative to controls, who instead showed stronger connectivity between central and posterior nodes. Spectral power within the anterior cingulate was not significantly correlated with any connectivity edges, suggesting lower power and higher connectivity are independent (versus resultant) neural mechanisms. Significant correlations between clinical features, task performance and anterior cingulate spectral power and connectivity suggest this region is associated with tic impairment ( r  = -0.31,  P  = 0.03) and flanker task incongruent trial accuracy ( r 's = -0.27 to -0.42,  P 's = 0.0008-0.04). Attenuated activation of the anterior cingulate along with dysregulated information flow between and among nodes within the fronto-parietal attention network may be neural adaptations that result from frequent engagement of neural pathways needed for inhibitory control in chronic tic disorder.},
  note = {PubMed query source: Scott Makeig}
}

@article{Xu202134892438,
  title = {Improving Transfer Performance of Deep Learning with Adaptive Batch Normalization for Brain-computer Interfaces.},
  author = {Xu, L and Ma, Z and Meng, J and Xu, M and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2021},
  doi = {10.1109/EMBC46164.2021.9629529},
  pmid = {34892438},
  url = {https://pubmed.ncbi.nlm.nih.gov/34892438/},
  abstract = {Recently, transfer learning and deep learning have been introduced to solve intra- and inter-subject variability problems in Brain-Computer Interfaces. However, the generalization ability of these BCIs is still to be further verified in a cross-dataset scenario. This study compared the transfer performance of manifold embedded knowledge transfer and pre-trained EEGNet with three preprocessing strategies. This study also introduced AdaBN for target domain adaptation. The results showed that EEGNet with Riemannian alignment and AdaBN could achieve the best transfer accuracy about 65.6% on the target dataset. This study may provide new insights into the design of transfer neural networks for BCIs by separating source and target batch normalization layers in the domain adaptation process.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lewczuk202132955140,
  title = {Frequency of use, moral incongruence and religiosity and their relationships with self-perceived addiction to pornography, internet use, social networking and online gaming.},
  author = {Lewczuk, K and Nowakowska, I and Lewandowska, K and Potenza, MN and Gola, M},
  journal = {Addiction (Abingdon, England)},
  year = {2021},
  doi = {10.1111/add.15272},
  pmid = {32955140},
  url = {https://pubmed.ncbi.nlm.nih.gov/32955140/},
  abstract = {Moral incongruence involves disapproval of a behavior in which people engage despite their moral beliefs. Although considerable research has been conducted on how moral incongruence relates to pornography use, potential roles for moral incongruence in other putative behavioral addictions have not been investigated. The aim of this study was to investigate the role of moral incongruence in self-perceived addiction to: (i) pornography; (ii) internet addiction; (iii) social networking; and (iv) online gaming. A cross-sectional, preregistered, online survey using multivariable regression. Online study conducted in Poland. 1036 Polish adults aged between 18 and 69 years. Measures included self-perceived behavioral addiction to pornography, internet use, social networking and online gaming and their hypothesized determinants (moral incongruence, frequency of use, time of use, religiosity, age and gender). Higher moral incongruence (β = 0.20, P < 0.001) and higher religiosity (β = 0.08, P < 0.05) were independently associated with higher self-perceived addiction to pornography. Additionally, frequency of pornography use was the strongest of the analyzed predictors (β = 0.43, P < 0.001). A similar, positive relationship between high moral incongruence and self-perceived addiction was also present for internet (β = 0.16, P < 0.001), social networking (β = 0.18, P < 0.001) and gaming addictions (β = 0.16, P < 0.001). Religiosity was uniquely, although weakly, connected to pornography addiction, but not to other types of addictive behaviors. Moral incongruence may be positively associated with self-perception of behavioral addictions including not only pornography viewing, but also internet use, social networking and online gaming.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Momsen202133652372,
  title = {Event related spectral perturbations of gesture congruity: Visuospatial resources are recruited for multimodal discourse comprehension.},
  author = {Momsen, J and Gordon, J and Wu, YC and Coulson, S},
  journal = {Brain and language},
  year = {2021},
  doi = {10.1016/j.bandl.2021.104916},
  pmid = {33652372},
  url = {https://pubmed.ncbi.nlm.nih.gov/33652372/},
  abstract = {Here we examine the role of visuospatial working memory (WM) during the comprehension of multimodal discourse with co-speech iconic gestures. EEG was recorded as healthy adults encoded either a sequence of one (low load) or four (high load) dot locations on a grid and rehearsed them until a free recall response was collected later in the trial. During the rehearsal period of the WM task, participants observed videos of a speaker describing objects in which half of the trials included semantically related co-speech gestures (congruent), and the other half included semantically unrelated gestures (incongruent). Discourse processing was indexed by oscillatory EEG activity in the alpha and beta bands during the videos. Across all participants, effects of speech and gesture incongruity were more evident in low load trials than in high load trials. Effects were also modulated by individual differences in visuospatial WM capacity. These data suggest visuospatial WM resources are recruited in the comprehension of multimodal discourse.},
  note = {PubMed query source: Ying Wu}
}

@article{Xu202134407522,
  title = {Enhancing transfer performance across datasets for brain-computer interfaces using a combination of alignment strategies and adaptive batch normalization.},
  author = {Xu, L and Xu, M and Ma, Z and Wang, K and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/ac1ed2},
  pmid = {34407522},
  url = {https://pubmed.ncbi.nlm.nih.gov/34407522/},
  abstract = {Objective . Recently, transfer learning (TL) and deep learning (DL) have been introduced to solve intra- and inter-subject variability problems in brain-computer interfaces (BCIs). However, current TL and DL algorithms are usually validated within a single dataset, assuming that data of the test subjects are acquired under the same condition as that of training (source) subjects. This assumption is generally violated in practice because of different acquisition systems and experimental settings across studies and datasets. Thus, the generalization ability of these algorithms needs further validations in a cross-dataset scenario, which is closer to the actual situation. This study compared the transfer performance of pre-trained deep-learning models with different preprocessing strategies in a cross-dataset scenario. Approach . This study used four publicly available motor imagery datasets, each was successively selected as a source dataset, and the others were used as target datasets. EEGNet and ShallowConvNet with four preprocessing strategies, namely channel normalization, trial normalization, Euclidean alignment, and Riemannian alignment, were trained with the source dataset. The transfer performance of pre-trained models was validated on the target datasets. This study also used adaptive batch normalization (AdaBN) for reducing interval covariate shift across datasets. This study compared the transfer performance of using the four preprocessing strategies and that of a baseline approach based on manifold embedded knowledge transfer (MEKT). This study also explored the possibility and performance of fusing MEKT and EEGNet. Main results . The results show that DL models with alignment strategies had significantly better transfer performance than the other two preprocessing strategies. As an unsupervised domain adaptation method, AdaBN could also significantly improve the transfer performance of DL models. The transfer performance of DL models that combined AdaBN and alignment strategies significantly outperformed MEKT. Moreover, the generalizability of EEGNet models that combined AdaBN and alignment strategies could be further improved via the domain adaptation step in MEKT, achieving the best generalization ability among multiple datasets (BNCI2014001: 0.788, PhysionetMI: 0.679, Weibo2014: 0.753, Cho2017: 0.650). Significance . The combination of alignment strategies and AdaBN could easily improve the generalizability of DL models without fine-tuning. This study may provide new insights into the design of transfer neural networks for BCIs by separating source and target batch normalization layers in the domain adaptation process.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xiao202134096888,
  title = {Enhancement for P300-speller classification using multi-window discriminative canonical pattern matching.},
  author = {Xiao, X and Xu, M and Han, J and Yin, E and Liu, S and Zhang, X and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/ac028b},
  pmid = {34096888},
  url = {https://pubmed.ncbi.nlm.nih.gov/34096888/},
  abstract = {Objective. P300s are one of the most studied event-related potentials (ERPs), which have been widely used for brain-computer interfaces (BCIs). Thus, fast and accurate recognition of P300s is an important issue for BCI study. Recently, there emerges a lot of novel classification algorithms for P300-speller. Among them, discriminative canonical pattern matching (DCPM) has been proven to work effectively, in which discriminative spatial pattern (DSP) filter can significantly enhance the spatial features of P300s. However, the pattern of ERPs in space varies with time, which was not taken into consideration in the traditional DCPM algorithm. Approach. In this study, we developed an advanced version of DCPM, i.e. multi-window DCPM, which contained a series of time-dependent DSP filters to fine-tune the extraction of spatial ERP features. To verify its effectiveness, 25 subjects were recruited and they were asked to conduct the typical P300-speller experiment. Main results. As a result, multi-window DCPM achieved the character recognition accuracy of 91.84% with only five training characters, which was significantly better than the traditional DCPM algorithm. Furthermore, it was also compared with eight other popular methods, including SWLDA, SKLDA, STDA, BLDA, xDAWN, HDCA, sHDCA and EEGNet. The results showed multi-window DCPM preformed the best, especially using a small calibration dataset. The proposed algorithm was applied to the BCI Controlled Robot Contest of P300 paradigm in 2019 World Robot Conference, and won the first place. Significance. These results demonstrate that multi-window DCPM is a promising method for improving the performance and enhancing the practicability of P300-speller.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cannard202135002651,
  title = {Electroencephalography Correlates of Well-Being Using a Low-Cost Wearable System.},
  author = {Cannard, C and Wahbeh, H and Delorme, A},
  journal = {Frontiers in human neuroscience},
  year = {2021},
  doi = {10.3389/fnhum.2021.745135},
  pmid = {35002651},
  url = {https://pubmed.ncbi.nlm.nih.gov/35002651/},
  abstract = {Electroencephalography (EEG) alpha asymmetry is thought to reflect crucial brain processes underlying executive control, motivation, and affect. It has been widely used in psychopathology and, more recently, in novel neuromodulation studies. However, inconsistencies remain in the field due to the lack of consensus in methodological approaches employed and the recurrent use of small samples. Wearable technologies ease the collection of large and diversified EEG datasets that better reflect the general population, allow longitudinal monitoring of individuals, and facilitate real-world experience sampling. We tested the feasibility of using a low-cost wearable headset to collect a relatively large EEG database ( N  = 230, 22-80 years old, 64.3% female), and an open-source automatic method to preprocess it. We then examined associations between well-being levels and the alpha center of gravity (CoG) as well as trait EEG asymmetries, in the frontal and temporoparietal (TP) areas. Robust linear regression models did not reveal an association between well-being and alpha (8-13 Hz) asymmetry in the frontal regions, nor with the CoG. However, well-being was associated with alpha asymmetry in the TP areas (i.e., corresponding to relatively less left than right TP cortical activity as well-being levels increased). This effect was driven by oscillatory activity in lower alpha frequencies (8-10.5 Hz), reinforcing the importance of dissociating sub-components of the alpha band when investigating alpha asymmetries. Age was correlated with both well-being and alpha asymmetry scores, but gender was not. Finally, EEG asymmetries in the other frequency bands were not associated with well-being, supporting the specific role of alpha asymmetries with the brain mechanisms underlying well-being levels. Interpretations, limitations, and recommendations for future studies are discussed. This paper presents novel methodological, experimental, and theoretical findings that help advance human neurophysiological monitoring techniques using wearable neurotechnologies and increase the feasibility of their implementation into real-world applications.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Kagawa202133284075,
  title = {Electroencephalographic Study on Sensory Integration in Visually Induced Postural Sway.},
  author = {Kagawa, T and Makeig, S and Miyakoshi, M},
  journal = {Journal of cognitive neuroscience},
  year = {2021},
  doi = {10.1162/jocn_a_01659},
  pmid = {33284075},
  url = {https://pubmed.ncbi.nlm.nih.gov/33284075/},
  abstract = {A periodically reversing optic flow animation, experienced while standing, induces an involuntary sway termed visually induced postural sway (VIPS). Interestingly, VIPS is suppressed during light finger touch to a stationary object. Here, we explored whether VIPS is mediated by parietal field activity in the dorsal visual stream as well as by activity in early visual areas, as has been suggested. We performed a mobile brain/body imaging study using high-density electroencephalographic recording from human participants (11 men and 3 women) standing during exposure to periodically reversing optic flow with and without light finger touch to a stable surface. We also performed recording their visuo-postural tracking movements as a typical visually guided movement to explore differences of cortical process of VIPS from the voluntary visuomotor process involving the dorsal stream. In the visuo-postural tracking condition, the participants moved their center of pressure in time with a slowly oscillating (expanding, shrinking) target rectangle. Source-resolved results showed that alpha band (8-13 Hz) activity in the medial and right occipital cortex during VIPS was modulated by the direction and velocity of optic flow and increased significantly during light finger touch. However, source-resolved potentials from the parietal association cortex showed no such modulation. During voluntary postural sway with feedback (but no visual flow) in which the dorsal stream is involved, sensorimotor areas produced more theta band (4-7 Hz) and less beta band (14-35 Hz) activity than during involuntary VIPS. These results suggest that VIPS involves cortical field dynamic changes in the early visual cortex rather than in the posterior parietal cortex of the visual dorsal stream.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme202133262082,
  title = {Effect of meditation on intracerebral EEG in a patient with temporal lobe epilepsy: A case report.},
  author = {Delorme, A and Grandchamp, R and Curot, J and Barragan-Jason, G and Denuelle, M and Sol, JC and Valton, L},
  journal = {Explore (New York, N.Y.)},
  year = {2021},
  doi = {10.1016/j.explore.2020.11.005},
  pmid = {33262082},
  url = {https://pubmed.ncbi.nlm.nih.gov/33262082/},
  abstract = {Meditation has been deemed a miracle cure for a wide range of neurological disorders. However, it is unclear whether meditation practice would be beneficial for patients suffering from epilepsy. Here we report on the comparison of the effects of focused-attention meditation and a control task on electroencephalographic (EEG) activity in a patient undergoing stereoencephalographic (SEEG) investigation for drug-resistant epilepsy. The patient routinely practiced focused-attention meditation and reported that she found it beneficial. During the SEEG investigation, intracerebral EEG data were recorded during meditation as well as during mind-wandering task. The EEG data were analyzed for type of electrical activity (labeled) by two expert epileptologists. We found that the proportion of EEG segments containing activity classified as interictal epileptiform discharges (IEDs; abnormal electrical activity that occurs between seizures) increased significantly during meditation practice. Although the finding was surprising, this increase in IEDs may not correlate with an increase in seizure frequency, and the patient might still benefit from practicing meditation. The finding does, however, warrant further studies on the influence of meditation on epileptic activity.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wei202134912203,
  title = {Editorial: Inter- and Intra-subject Variability in Brain Imaging and Decoding.},
  author = {Wei, CS and Keller, CJ and Li, J and Lin, YP and Nakanishi, M and Wagner, J and Wu, W and Zhang, Y and Jung, TP},
  journal = {Frontiers in computational neuroscience},
  year = {2021},
  doi = {10.3389/fncom.2021.791129},
  pmid = {34912203},
  url = {https://pubmed.ncbi.nlm.nih.gov/34912203/},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gu202133465029,
  title = {EEG-Based Brain-Computer Interfaces (BCIs): A Survey of Recent Studies on Signal Sensing Technologies and Computational Intelligence Approaches and Their Applications.},
  author = {Gu, X and Cao, Z and Jolfaei, A and Xu, P and Wu, D and Jung, TP and Lin, CT},
  journal = {IEEE/ACM transactions on computational biology and bioinformatics},
  year = {2021},
  doi = {10.1109/TCBB.2021.3052811},
  pmid = {33465029},
  url = {https://pubmed.ncbi.nlm.nih.gov/33465029/},
  abstract = {Brain-Computer interfaces (BCIs) enhance the capability of human brain activities to interact with the environment. Recent advancements in technology and machine learning algorithms have increased interest in electroencephalographic (EEG)-based BCI applications. EEG-based intelligent BCI systems can facilitate continuous monitoring of fluctuations in human cognitive states under monotonous tasks, which is both beneficial for people in need of healthcare support and general researchers in different domain areas. In this review, we survey the recent literature on EEG signal sensing technologies and computational intelligence approaches in BCI applications, compensating for the gaps in the systematic summary of the past five years. Specifically, we first review the current status of BCI and signal sensing technologies for collecting reliable EEG signals. Then, we demonstrate state-of-the-art computational intelligence techniques, including fuzzy models and transfer learning in machine learning and deep learning algorithms, to detect, monitor, and maintain human cognitive states and task performance in prevalent applications. Finally, we present a couple of innovative BCI-inspired healthcare applications and discuss future research directions in EEG-based BCI research.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202132548801,
  title = {Dynamic Brain Responses Modulated by Precise Timing Prediction in an Opposing Process.},
  author = {Xu, M and Meng, J and Yu, H and Jung, TP and Ming, D},
  journal = {Neuroscience bulletin},
  year = {2021},
  doi = {10.1007/s12264-020-00527-1},
  pmid = {32548801},
  url = {https://pubmed.ncbi.nlm.nih.gov/32548801/},
  abstract = {The brain function of prediction is fundamental for human beings to shape perceptions efficiently and successively. Through decades of effort, a valuable brain activation map has been obtained for prediction. However, much less is known about how the brain manages the prediction process over time using traditional neuropsychological paradigms. Here, we implemented an innovative paradigm for timing prediction to precisely study the temporal dynamics of neural oscillations. In the experiment recruiting 45 participants, expectation suppression was found for the overall electroencephalographic activity, consistent with previous hemodynamic studies. Notably, we found that N1 was positively associated with predictability while N2 showed a reversed relation to predictability. Furthermore, the matching prediction had a similar profile with no timing prediction, both showing an almost saturated N1 and an absence of N2. The results indicate that the N1 process showed a 'sharpening' effect for predictable inputs, while the N2 process showed a 'dampening' effect. Therefore, these two paradoxical neural effects of prediction, which have provoked wide confusion in accounting for expectation suppression, actually co-exist in the procedure of timing prediction but work in separate time windows. These findings strongly support a recently-proposed opposing process theory.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Shirazi202133539300,
  title = {Differential Theta-Band Signatures of the Anterior Cingulate and Motor Cortices During Seated Locomotor Perturbations.},
  author = {Shirazi, SY and Huang, HJ},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2021},
  doi = {10.1109/TNSRE.2021.3057054},
  pmid = {33539300},
  url = {https://pubmed.ncbi.nlm.nih.gov/33539300/},
  abstract = {Quantifying motor and cortical responses to perturbations during seated locomotor tasks such as recumbent stepping and cycling will expand and improve the understanding of locomotor adaptation processes beyond just perturbed gait. Using a perturbed recumbent stepping protocol, we hypothesized motor errors and anterior cingulate activity would decrease with time, and perturbation timing would influence electrocortical elicitation. Young adults (n = 17) completed four 10-minute arms and legs stepping tasks, with perturbations applied at every left or right leg extension-onset or mid-extension. A random no-perturbation "catch" stride occurred in every five perturbed strides. We instructed subjects to follow a pacing cue and to step smoothly, and we quantified temporal and spatial motor errors. We used high-density electroencephalography to estimate sources of electrocortical fluctuations shared among >70% of subjects. Temporal and spatial errors did not decrease from early to late for either perturbed or catch strides. Interestingly, spatial errors post-perturbation did not return to pre-perturbation levels, suggesting use-dependent learning occurred. Theta (3-8 Hz) synchronization in the anterior cingulate cortex and left and right supplementary motor areas (SMA) emerged near the perturbation event, and extension-onset perturbations elicited greater theta-band power than mid-extension perturbations. Even though motor errors did not adapt, anterior cingulate theta synchronization decreased from early to late perturbed strides, but only during the right-side tasks. Additionally, SMA mainly demonstrated specialized, not contralateral, lateralization. Overall, seated locomotor perturbations produced differential theta-band responses in the anterior cingulate and SMAs, suggesting that tuning perturbation parameters, e.g., timing, can potentially modify electrocortical responses.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Zhou202134130268,
  title = {Detection of fixation points using a small visual landmark for brain-computer interfaces.},
  author = {Zhou, X and Xu, M and Xiao, X and Wang, Y and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/ac0b51},
  pmid = {34130268},
  url = {https://pubmed.ncbi.nlm.nih.gov/34130268/},
  abstract = {Objective. The speed of visual brain-computer interfaces (v-BCIs) has been greatly improved in recent years. However, the traditional v-BCI paradigms require users to directly gaze at the intensive flickering items, which would cause severe problems such as visual fatigue and excessive visual resource consumption in practical applications. Therefore, it is imperative to develop a user-friendly v-BCI. Approach. According to the retina-cortical relationship, this study developed a novel BCI paradigm to detect the fixation point of eyes using a small visual stimulus that subtended only 0.6° in visual angle and was out of the central visual field. Specifically, the visual stimulus was treated as a landmark to judge the eccentricity and polar angle of the fixation point. Sixteen different fixation points were selected around the visual landmark, i.e. different combinations of two eccentricities (2° and 4°) and eight polar angles (0,π4,π2,3π4,π,5π4,3π2and7π4). Twelve subjects participated in this study, and they were asked to gaze at one out of the 16 points for each trial. A multi-class discriminative canonical pattern matching (Multi-DCPM) algorithm was proposed to decode the user's fixation point. Main results. We found the visual stimulation landmark elicited different spatial event-related potential patterns for different fixation points. Multi-DCPM could achieve an average accuracy of 66.2% with a standard deviation of 15.8% for the classification of the sixteen fixation points, which was significantly higher than traditional algorithms (p⩽0.001). Experimental results of this study demonstrate the feasibility of using a small visual stimulus as a landmark to track the relative position of the fixation point. Significance. The proposed new paradigm provides a potential approach to alleviate the problem of irritating stimuli in v-BCIs, which can broaden the applications of BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Truong202134891466,
  title = {Deep Convolutional Neural Network Applied to Electroencephalography: Raw Data vs Spectral Features.},
  author = {Truong, D and Milham, M and Makeig, S and Delorme, A},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2021},
  doi = {10.1109/EMBC46164.2021.9630708},
  pmid = {34891466},
  url = {https://pubmed.ncbi.nlm.nih.gov/34891466/},
  abstract = {The success of deep learning in computer vision has inspired the scientific community to explore new analysis methods. Within the field of neuroscience, specifically in electrophysiological neuroimaging, researchers are starting to explore leveraging deep learning to make predictions on EEG data. Research remains open on the network architecture and the feature space that is most effective for EEG decoding. This paper compares deep learning using minimally processed EEG raw data versus deep learning using EEG spectral features using two different deep convolutional neural architectures. One of them from Putten et al. (2018) is tailored to process raw data; the other was derived from the VGG16 vision network (Simonyan and Zisserman, 2015) which is designed to process EEG spectral features. We apply them to classify sex on 24-channel EEG from a large corpus of 1,574 participants. Not only do we improve on state-of-the-art classification performance for this type of classification problem, but we also show that in all cases, raw data classification leads to superior performance as compared to spectral EEG features. Interestingly we show that the neural network tailored to process EEG spectral features has increased performance when applied to raw data classification. Our approach suggests that the same convolutional networks used to process EEG spectral features yield superior performance when applied to EEG raw data.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Xu202134603552,
  title = {Correction to: Review of brain encoding and decoding mechanisms for EEG-based brain-computer interface.},
  author = {Xu, L and Xu, M and Jung, TP and Ming, D},
  journal = {Cognitive neurodynamics},
  year = {2021},
  doi = {10.1007/s11571-021-09686-x},
  pmid = {34603552},
  url = {https://pubmed.ncbi.nlm.nih.gov/34603552/},
  abstract = {[This corrects the article DOI: 10.1007/s11571-021-09676-z.].},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Huang202134181544,
  title = {Comparing the Differences in Brain Activities and Neural Comodulations Associated With Motion Sickness Between Drivers and Passengers.},
  author = {Huang, KC and John, AR and Jung, TP and Tsai, WF and Yu, YH and Lin, CT},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2021},
  doi = {10.1109/TNSRE.2021.3092876},
  pmid = {34181544},
  url = {https://pubmed.ncbi.nlm.nih.gov/34181544/},
  abstract = {It is common to believe that passengers are more adversely affected by motion sickness than drivers. However, no study has compared passengers and drivers' neural activities and drivers experiencing motion sickness (MS). Therefore, this study attempts to explore brain dynamics in motion sickness among passengers and drivers. Eighteen volunteers participated in simulating the driving winding road experiment while their subjective motion sickness levels and electroencephalogram (EEG) signals were simultaneously recorded. Independent Component Analysis (ICA) was employed to isolate MS-related independent components (ICs) from EEG. Furthermore, comodulation analysis was applied to decompose spectra of interest ICs, related to MS, to find the specific spectra-related temporally independent modulators (IMs). The results showed that passengers' alpha band (8-12 Hz) power increased in correlation with the MS level in the parietal, occipital midline and left and right motor areas, and drivers' alpha band (8-12 Hz) power showed relatively smaller increases than those in the passenger. Further, the results also indicate that the enhanced activation of alpha IMs in the passenger than the driver is due to a higher degree of motion sickness. In conclusion, compared to the driver, the passenger experience more conflicts among multimodal sensory systems and demand neuro-physiological regulation.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202134710045,
  title = {Classification of Left-Versus Right-Hand Motor Imagery in Stroke Patients Using Supplementary Data Generated by CycleGAN.},
  author = {Xu, F and Rong, F and Leng, J and Sun, T and Zhang, Y and Siddharth, S and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2021},
  doi = {10.1109/TNSRE.2021.3123969},
  pmid = {34710045},
  url = {https://pubmed.ncbi.nlm.nih.gov/34710045/},
  abstract = {Acquiring Electroencephalography (EEG) data is often time-consuming, laborious, and costly, posing practical challenges to train powerful but data-demanding deep learning models. This study proposes a surrogate EEG data-generation system based on cycle-consistent adversarial networks (CycleGAN) that can expand the number of training data. This study used EEG2Image based on a modified S-transform (MST) to convert EEG data into EEG-topography. This method retains the frequency-domain characteristics and spatial information of the EEG signals. Then, the CycleGAN is used to learn and generate motor-imagery EEG data of stroke patients. From the visual inspection, there is no difference between the EEG topographies of the generated and original EEG data collected from the stroke patients. Finally, we used convolutional neural networks (CNN) to evaluate and analyze the generated EEG data. The experimental results show that the generated data effectively improved the classification accuracy.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Robbins202134848298,
  title = {Capturing the nature of events and event context using hierarchical event descriptors (HED).},
  author = {Robbins, K and Truong, D and Appelhoff, S and Delorme, A and Makeig, S},
  journal = {NeuroImage},
  year = {2021},
  doi = {10.1016/j.neuroimage.2021.118766},
  pmid = {34848298},
  url = {https://pubmed.ncbi.nlm.nih.gov/34848298/},
  abstract = {Event-related data analysis plays a central role in EEG and MEG (MEEG) and other neuroimaging modalities including fMRI. Choices about which events to report and how to annotate their full natures significantly influence the value, reliability, and reproducibility of neuroimaging datasets for further analysis and meta- or mega-analysis. A powerful annotation strategy using the new third-generation formulation of the Hierarchical Event Descriptors (HED) framework and tools (hedtags.org) combines robust event description with details of experiment design and metadata in a human-readable as well as machine-actionable form, making event annotation relevant to the full range of neuroimaging and other time series data. This paper considers the event design and annotation process using as a case study the well-known multi-subject, multimodal dataset of Wakeman and Henson made available by its authors as a Brain Imaging Data Structure (BIDS) dataset (bids.neuroimaging.io). We propose a set of best practices and guidelines for event annotation integrated in a natural way into the BIDS metadata file architecture, examine the impact of event design decisions, and provide a working example of organizing events in MEEG and other neuroimaging data. We demonstrate how annotations using HED can document events occurring during neuroimaging experiments as well as their interrelationships, providing machine-actionable annotation enabling automated within- and across-experiment analysis and comparisons. We discuss the evolution of HED software tools and have made available an accompanying HED-annotated BIDS-formated edition of the MEEG data of the Wakeman and Henson dataset (openneuro.org, ds003645).},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Stuart202134505536,
  title = {Brain Activity Response to Visual Cues for Gait Impairment in Parkinson's Disease: An EEG Study.},
  author = {Stuart, S and Wagner, J and Makeig, S and Mancini, M},
  journal = {Neurorehabilitation and neural repair},
  year = {2021},
  doi = {10.1177/15459683211041317},
  pmid = {34505536},
  url = {https://pubmed.ncbi.nlm.nih.gov/34505536/},
  abstract = {Background.  Gait impairments are common in Parkinson's disease (PD) and increase falls risk. Visual cues can improve gait in PD, particularly freezing of gait (FOG), but mechanisms involved in visual cue response are unknown. This study aimed to examine brain activity in response to visual cues in people with PD who do (PD+FOG) and do not report FOG (PD-FOG) and explore relationships between attention, brain activity and gait.  Methods . Mobile EEG measured brain activity during gait in 20 healthy older adults and 43 PD participants (n=22 PD+FOG, n=21 PD-FOG). Participants walked for 2-minutes with and without visual cues (transverse lines to step over). We report power spectral density (PSD) in Delta (1-4 Hz), Theta (4-7 Hz), Alpha (8-12 Hz), Beta (14-24 Hz) and Gamma (30-50 Hz) bands within clusters of similarly brain localized independent component sources.  Results . PSDs within the parietal and occipital lobes were altered when walking with visual cues in PD, particularly in PD+FOG. Between group, differences suggested that parietal sources in PD, particularly with PD+FOG, had larger activity compared to healthy older adults when walking. Within group, visual cues altered brain activity in PD, particularly in PD+FOG, within visual processing brain regions. In PD participants, brain activity differences with cues correlated with gait improvements, and in PD+FOG those with worse attention required more visual attentional processing (reduced alpha PSD) in the occipital lobe.  Conclusions . Visual cues improve gait and influence brain activity during walking in PD, particularly in PD+FOG. Findings may allow development of more effective therapeutics.},
  note = {PubMed query source: Scott Makeig}
}

@article{Chiang202133203813,
  title = {Boosting template-based SSVEP decoding by cross-domain transfer learning.},
  author = {Chiang, KJ and Wei, CS and Nakanishi, M and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2021},
  doi = {10.1088/1741-2552/abcb6e},
  pmid = {33203813},
  url = {https://pubmed.ncbi.nlm.nih.gov/33203813/},
  abstract = {Objective . This study aims to establish a generalized transfer-learning framework for boosting the performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) by leveraging cross-domain data transferring. Approach . We enhanced the state-of-the-art template-based SSVEP decoding through incorporating a least-squares transformation (LST)-based transfer learning to leverage calibration data across multiple domains (sessions, subjects, and electroencephalogram montages). Main results . Study results verified the efficacy of LST in obviating the variability of SSVEPs when transferring existing data across domains. Furthermore, the LST-based method achieved significantly higher SSVEP-decoding accuracy than the standard task-related component analysis (TRCA)-based method and the non-LST naive transfer-learning method. Significance . This study demonstrated the capability of the LST-based transfer learning to leverage existing data across subjects and/or devices with an in-depth investigation of its rationale and behavior in various circumstances. The proposed framework significantly improved the SSVEP decoding accuracy over the standard TRCA approach when calibration data are limited. Its performance in calibration reduction could facilitate plug-and-play SSVEP-based BCIs and further practical applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Shikauchi202133237612,
  title = {Bayesian models of human navigation behaviour in an augmented reality audiomaze.},
  author = {Shikauchi, Y and Miyakoshi, M and Makeig, S and Iversen, JR},
  journal = {The European journal of neuroscience},
  year = {2021},
  doi = {10.1111/ejn.15061},
  pmid = {33237612},
  url = {https://pubmed.ncbi.nlm.nih.gov/33237612/},
  abstract = {We investigated Bayesian modelling of human whole-body motion capture data recorded during an exploratory real-space navigation task in an "Audiomaze" environment (see the companion paper by Miyakoshi et al. in the same volume) to study the effect of map learning on navigation behaviour. There were three models, a feedback-only model (no map learning), a map resetting model (single-trial limited map learning), and a map updating model (map learning accumulated across three trials). The estimated behavioural variables included step sizes and turning angles. Results showed that the estimated step sizes were constantly more accurate using the map learning models than the feedback-only model. The same effect was confirmed for turning angle estimates, but only for data from the third trial. We interpreted these results as Bayesian evidence of human map learning on navigation behaviour. Furthermore, separating the participants into groups of egocentric and allocentric navigators revealed an advantage for the map updating model in estimating step sizes, but only for the allocentric navigators. This interaction indicated that the allocentric navigators may take more advantage of map learning than do egocentric navigators. We discuss relationships of these results to simultaneous localization and mapping (SLAM) problem.},
  note = {PubMed query source: Scott Makeig}
}

@article{Draps202134550905,
  title = {An empirical study of affective and cognitive functions in Compulsive Sexual Behavior Disorder.},
  author = {Draps, M and Sescousse, G and Wilk, M and Obarska, K and Szumska, I and Żukrowska, W and Majkowska, A and Kowalewska, E and Szymanowska, J and Hamerska, U and Trybuś, M and Golec, K and Adamska, I and Szymczak, K and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2021},
  doi = {10.1556/2006.2021.00056},
  pmid = {34550905},
  url = {https://pubmed.ncbi.nlm.nih.gov/34550905/},
  abstract = {Despite the inclusion of the Compulsive Sexual Behavior Disorder (CSBD) in the International Classification of Diseases, very little is known about the underlying affective and cognitive processes. To fill this gap, we compared CSBD subjects and Healthy-Controls (HC) across negative/positive valence, cognitive and sensorimotor systems, as proposed by the Research Domain Criteria framework. 74 heterosexual CSBD and 66 matched HC males were studied with 10 questionnaires and 8 behavioral tasks. Analyses were conducted with frequent and Bayesian statistics. CSBD individuals showed significantly higher (than HC) punishment sensitivity, anxiety, depression, compulsivity, and impulsivity symptoms. Frequentist statistical analysis revealed significant interaction between subject group and condition in Incentive Delay Task, concerning the strength of motivation and hedonic value of erotic rewards. Bayesian analysis produced evidence for the absence of group differences in Facial Discrimination Task, Risk-Ambiguity Task, and Learning Task. Also, Bayesian methods provided evidence for group differences in the Emotional Stroop Task and the Incentive Delay Task. Sexual Discounting Task, Attentional Network Task, and Stop Signal Task produced mixed results. Higher punishment sensitivity and impulsivity among CSBD subjects, along with significant interaction between these groups and erotic vs. non-erotic reward processing is in line with previous findings on negative/positive valence alterations in CSBD patients. This result shows that there are similarities to substance and behavioral addictions. The absence of group differences and mixed results related to cognitive and sensorimotor systems raise concerns to what extent CSBD resembles a wide spectrum of impairments observed in disorders, and demand further research.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Onton202134368501,
  title = {Amount of < 1Hz deep sleep correlates with melatonin dose in military veterans with PTSD.},
  author = {Onton, J and Le, LD},
  journal = {Neurobiology of sleep and circadian rhythms},
  year = {2021},
  doi = {10.1016/j.nbscr.2021.100072},
  pmid = {34368501},
  url = {https://pubmed.ncbi.nlm.nih.gov/34368501/},
  abstract = {Military veterans with posttraumatic stress disorder often complain of non-restful sleep, which further exacerbates their symptoms. Our previous study showed a deficit in Lo Deep sleep, or slow oscillations, in the PTSD population compared to healthy control sleepers. Because Lo Deep sleep is likely a stage when the brain eliminates protein debris, it is critical to find the cause and effective therapeutics to reverse Lo Deep deficiency. The current study aims to replicate and extend this finding by examining several physiological and medication factors that may be responsible for the Lo Deep deficiency. We recorded overnight sleep electroencephalogram (EEG) via a 2-channel headband device on 69 veterans in a residential treatment facility. Dried urine samples were collected at 4 time points during one day to measure melatonin, cortisol, norepinephrine and other factors. EEG data were transformed into frequency power and submitted to an automated sleep scoring algorithm. The scoring corresponds to clear spectral patterns in the overnight spectrogram but does not align exactly with traditional visual scoring stages. As expected ,  veterans showed decreased Lo Deep (activity < 1 Hz) and more Hi Deep sleep (1-3 Hz activity) than healthy controls, replicating our previous study. Multiple linear regressions showed that melatonin dose and morning urine melatonin correlated with more Lo Deep sleep. Buspirone dose also correlated with more Lo Deep, but only 6 subjects were taking buspirone. Also replicating the findings from our last study were independent reductions of REM sleep with prazosin and sertraline. Other findings included decreased Lo and increased Hi Deep sleep with higher caffeine dose, and less Hi Deep percentage with higher testosterone. Finally, evening cortisol levels correlated with a higher percentage of Wake after sleep onset. These results confirm Lo Deep deficiency in this PTSD population and suggests melatonin as a possible therapeutic to reverse Lo Deep deficiency. This is a critical first step to establishing a systematic sleep assessment and treatment program in this and potentially other populations to prevent future brain pathology.},
  note = {PubMed query source: Julie Onton}
}

@article{Patel202134892640,
  title = {Affective response to volitional input perturbations in obstacle avoidance and target tracking games.},
  author = {Patel, AN and Chau, G and Chang, C and Sun, A and Huang, J and Jung, TP and Gilja, V},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2021},
  doi = {10.1109/EMBC46164.2021.9630523},
  pmid = {34892640},
  url = {https://pubmed.ncbi.nlm.nih.gov/34892640/},
  abstract = {We present the use of two game-like tasks, Catnip and Dinorun, to explore affective responses to volitional control perturbations. We analyze behavioral and physiological measures with the self-assessment manikin (SAM), pupillometry, and electroencephalography (EEG) responses to provide intratrial emotional state as well as inter-trial correlates with selfreported survey responses. We find that subject gameplay characteristics significantly correlate with valence and dominance scores for both games, and that perturbations to the games produce a measurable decrease in response scores for Dinorun. During perturbation events, pupillometry analysis reveals considerable SAM-agnostic dilation, with stronger responses in more rigid trialized event structures. Furthermore, analyses of neural activity from central and parietal regions demonstrate significant measurable evoked responses to perturbed events across the majority of subjects for both games. By introducing perturbations, this set of experiments and analyses inform and enable further studies of affective responses to the loss of volitional control during engaging, game-like tasks.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wang202132919982,
  title = {Adipose-derived stem cell transplantation improves learning and memory via releasing neurotrophins in rat model of temporal lobe epilepsy.},
  author = {Wang, L and Zhao, Y and Pan, X and Zhang, Y and Lin, L and Wu, Y and Huang, Y and He, H},
  journal = {Brain research},
  year = {2021},
  doi = {10.1016/j.brainres.2020.147121},
  pmid = {32919982},
  url = {https://pubmed.ncbi.nlm.nih.gov/32919982/},
  abstract = {Epilepsy is a common neurological disease and its most common type is temporal lobe epilepsy (TLE). Novel therapeutics is needed as many TLE patients are resistant to treatments like anticonvulsants or temporal lobectomy. Stem cell therapy has great promise in regeneration medicine. In the current study, we tried to investigate the potential protective effects of adipose-derived stem cell (ADSC) transplantation in epileptic rats. Epilepsy model was established by intra-hippocampal injection of kainic acid (KA) in rats. ADSCs were isolated, differentiated and transplanted into hippocampus of KA rats. There were three groups of rats: normal control group receiving saline injection and no transplantation, KA + sham group receiving KA injection and sham transplantation surgery and KA + transplantation group receiving KA injection and ADSC transplantation. We found that ADSCs were highly positive for CD44, CD90, CD29 and CD105, and neural differentiation induced the expression of neuronal markers like Tuj1, MAP2, NeuN and PSD-95. EEG recording showed that KA induced seizure activity while ADSC transplantation inhibited seizure activity. In training session of Morris water maze task, KA injection impaired the learning capacity of rats while ADSC transplantation restored the learning capacity at 2-week or 2-month post transplantation. In probe session of Morris water maze task, KA injection impaired the memory of rats while ADSC transplantation restored the memory at 2-week or 2-month post transplantation. Transplanted ADSCs released BDNF, NT3 and NT4. Pro-apoptotic BAX was reduced while anti-apoptotic BCL-2 and BCL-xL were increased in hippocampus post ADSC transplantation. Our study suggests that ADSC transplantation inhibits KA-induced seizures and improves the learning and memory function of epileptic rats.},
  note = {PubMed query source: Ying Wu}
}

@article{Golec202134437297,
  title = {Aberrant orbitofrontal cortex reactivity to erotic cues in Compulsive Sexual Behavior Disorder.},
  author = {Golec, K and Draps, M and Stark, R and Pluta, A and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2021},
  doi = {10.1556/2006.2021.00051},
  pmid = {34437297},
  url = {https://pubmed.ncbi.nlm.nih.gov/34437297/},
  abstract = {Compulsive Sexual Behavior Disorder (CSBD) is characterized by increased reactivity to erotic reward cues. Cue-encoded reward parameters, such as type (e.g. erotic or monetary) or probability of anticipated reward, shape reward-related motivational processes, increase the attractiveness of cues and therefore might enhance maladaptive behavioral patterns in CSBD. Studies on the neural patterns of cue processing in individuals with CSBD have been limited mainly to ventral striatal responses. Therefore, here we aimed to examine the cue reactivity of multiple key structures in the brain's reward system, taking into account not only the type of predicted reward but also its probability. Twenty Nine men seeking professional help due to CSBD and 24 healthy volunteers took part in an fMRI study with a modified Incentive Delay Task with erotic and monetary rewards preceded by cues indicating a 25%, 50%, or 75% chance of reward. Analyses of functional patterns of activity related to cue type and probability were conducted on the whole-brain and ROI levels. Increased anticipatory response to cues predictive of erotic rewards was observed among CSBD participants when compared to controls, in the ventral striatum and anterior orbitofrontal cortex (aOFC). The activity in aOFC was modulated by reward probability. Type of anticipated reward (erotic vs monetary) affects reward-related behavioral motivation in CSBD more strongly than reward probability. We present evidence of abnormal aOFC function in CSBD by demonstrating the recruitment of additional subsections of this region by erotic reward cues.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Liu202133778069,
  title = {A Network Pharmacology to Explore the Mechanism of Calculus Bovis in the Treatment of Ischemic Stroke.},
  author = {Liu, F and Li, L and Chen, J and Wu, Y and Cao, Y and Zhong, P},
  journal = {BioMed research international},
  year = {2021},
  doi = {10.1155/2021/6611018},
  pmid = {33778069},
  url = {https://pubmed.ncbi.nlm.nih.gov/33778069/},
  abstract = {Calculus Bovis  is a valuable Chinese medicine, which is widely used in the clinical treatment of ischemic stroke. The present study is aimed at investigating its target and the mechanism involved in ischemic stroke treatment by network pharmacology. Effective compounds of  Calculus Bovis  were collected using methods of network pharmacology and using the Bioinformatics Analysis Tool for Molecular Mechanism of Traditional Chinese Medicine (BATMAN-TCM) and the Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP). Potential compound targets were searched in the TCMSP and SwissTargetPrediction databases. Ischemic stroke-related disease targets were searched in the Drugbank, DisGeNet, OMIM, and TTD databases. These two types of targets were uploaded to the STRING database, and a network of their interaction (PPI) was built with its characteristics calculated, aiming to reveal a number of key targets. Hub genes were selected using a plug-in of the Cytoscape software, and Gene Ontology (GO) biological processes and pathway enrichment analyses of Kyoto Encyclopedia of Genes and Genomes (KEGG) were conducted using the clusterProfiler package of R language. Among 12 compounds, deoxycorticosterone, methyl cholate, and biliverdin were potentially effective components. A total of 344  Calculus Bovis  compound targets and 590 ischemic stroke targets were found with 92 overlapping targets, including hub genes such as TP53, AKT, PIK2CA, MAPK3, MMP9, and MMP2. Biological functions of  Calculus Bovis  are associated with protein hydrolyzation, phosphorylation of serine/threonine residues of protein substrates, peptide bond hydrolyzation of peptides and proteins, hydrolyzation of intracellular second messengers, antioxidation and reduction, RNA transcription, and other biological processes. Calculus Bovis  may play a role in ischemic stroke by activating PI3K-AKT and MAPK signaling pathways, which are involved in regulating inflammatory response, cell apoptosis, and proliferation.},
  note = {PubMed query source: Ying Wu}
}

@article{MartnezCancino202033287030,
  title = {What Can Local Transfer Entropy Tell Us about Phase-Amplitude Coupling in Electrophysiological Signals?},
  author = {Martínez-Cancino, R and Delorme, A and Wagner, J and Kreutz-Delgado, K and Sotero, RC and Makeig, S},
  journal = {Entropy (Basel, Switzerland)},
  year = {2020},
  doi = {10.3390/e22111262},
  pmid = {33287030},
  url = {https://pubmed.ncbi.nlm.nih.gov/33287030/},
  abstract = {Modulation of the amplitude of high-frequency cortical field activity locked to changes in the phase of a slower brain rhythm is known as phase-amplitude coupling (PAC). The study of this phenomenon has been gaining traction in neuroscience because of several reports on its appearance in normal and pathological brain processes in humans as well as across different mammalian species. This has led to the suggestion that PAC may be an intrinsic brain process that facilitates brain inter-area communication across different spatiotemporal scales. Several methods have been proposed to measure the PAC process, but few of these enable detailed study of its time course. It appears that no studies have reported details of PAC dynamics including its possible directional delay characteristic. Here, we study and characterize the use of a novel information theoretic measure that may address this limitation: local transfer entropy. We use both simulated and actual intracranial electroencephalographic data. In both cases, we observe initial indications that local transfer entropy can be used to detect the onset and offset of modulation process periods revealed by mutual information estimated phase-amplitude coupling (MIPAC). We review our results in the context of current theories about PAC in brain electrical activity, and discuss technical issues that must be addressed to see local transfer entropy more widely applied to PAC analysis. The current work sets the foundations for further use of local transfer entropy for estimating PAC process dynamics, and extends and complements our previous work on using local mutual information to compute PAC (MIPAC).},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Momsen202033171343,
  title = {Verbal working memory and co-speech gesture processing.},
  author = {Momsen, J and Gordon, J and Wu, YC and Coulson, S},
  journal = {Brain and cognition},
  year = {2020},
  doi = {10.1016/j.bandc.2020.105640},
  pmid = {33171343},
  url = {https://pubmed.ncbi.nlm.nih.gov/33171343/},
  abstract = {Multimodal discourse requires an assembly of cognitive processes that are uniquely recruited for language comprehension in social contexts. In this study, we investigated the role of verbal working memory for the online integration of speech and iconic gestures. Participants memorized and rehearsed a series of auditorily presented digits in low (one digit) or high (four digits) memory load conditions. To observe how verbal working memory load impacts online discourse comprehension, ERPs were recorded while participants watched discourse videos containing either congruent or incongruent speech-gesture combinations during the maintenance portion of the memory task. While expected speech-gesture congruity effects were found in the low memory load condition, high memory load trials elicited enhanced frontal positivities that indicated a unique interaction between online speech-gesture integration and the availability of verbal working memory resources. This work contributes to an understanding of discourse comprehension by demonstrating that language processing in a multimodal context is subject to the relationship between cognitive resource availability and the degree of controlled processing required for task performance. We suggest that verbal working memory is less important for speech-gesture integration than it is for mediating speech processing under high task demands.},
  note = {PubMed query source: Ying Wu}
}

@article{Kraus202032644937,
  title = {Validation of a Brief Pornography Screen across multiple samples.},
  author = {Kraus, SW and Gola, M and Grubbs, JB and Kowalewska, E and Hoff, RA and Lew-Starowicz, M and Martino, S and Shirk, SD and Potenza, MN},
  journal = {Journal of behavioral addictions},
  year = {2020},
  doi = {10.1556/2006.2020.00038},
  pmid = {32644937},
  url = {https://pubmed.ncbi.nlm.nih.gov/32644937/},
  abstract = {To address current gaps around screening for problematic pornography use (PPU), we initially developed and tested a six-item Brief Pornography Screen (BPS) that asked about PPU in the past six months. We recruited five independent samples from the U.S. and Poland to evaluate the psychometric properties of the BPS. In Study 1, we evaluated the factor structure, reliability, and elements of validity using a sample of 224 U.S. veterans. One item from the BPS was dropped in Study 1 due to low item endorsement. In Studies 2 and 3, we further investigated the five-item the factor structure of the BPS and evaluated its reliability and validity in two national U.S. representative samples (N = 1,466, N = 1,063, respectively). In Study 4, we confirmed the factor structure and evaluated its validity and reliability using a sample of 703 Polish adults. In Study 5, we calculated the suggested cut-off score for the screen using a sample of 105 male patients seeking treatment for compulsive sexual behavior disorder (CSBD). Findings from a principal components analysis and confirmatory factor analysis supported a one-factor solution which yielded high internal consistency (α = 0.89-0.90), and analyses further supported elements of construct, convergent, criterion, and discriminant validity of the newly developed screen. Results from a Receiver Operating Characteristic (ROC) curve suggested a cut-off score of four or higher for detecting possible PPU. The BPS appears to be psychometrically sound, short, and easy to use in various settings with high potential for use in populations across international jurisdictions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Mei202033019051,
  title = {Using SSVEP-BCI to Continuous Control a Quadcopter with 4-DOF Motions.},
  author = {Mei, J and Xu, M and Wang, L and Ke, Y and Wang, Y and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9176131},
  pmid = {33019051},
  url = {https://pubmed.ncbi.nlm.nih.gov/33019051/},
  abstract = {Brain-computer interfaces (BCIs) allow for translating electroencephalogram (EEG) into control commands, e.g., to control a quadcopter. This study, we developed a practical BCI based on steady-state visually evoked potential (SSVEP) for continuous control of a quadcopter from the first-person perspective. Users watched with the video stream from a camera on the quadcopter. An innovative user interface was developed by embedding 12 SSVEP flickers into the video stream, which corresponded to the flight commands of 'take-off,' 'land,' 'hover,' 'keep-going,' 'clockwise,' 'counter-clockwise' and rectilinear motions in six directions, respectively. The command was updated every 400ms by decoding the collected EEG data using a combined classification algorithm based on task-related component analysis (TRCA) and linear discriminant analysis (LDA). The quadcopter flew in the 3-D space according to the control vector that was determined by the latest four commands. Three novices participated in this study. They were asked to control the quadcopter by either the brain or hands to fly through a circle and land on the target zone. As a result, the time consumption ratio of brain-control to hand-control was as low as 1.34, which means the BCI performance was close to hands. The information transfer rate reached a peak of 401.79 bits/min in the simulated online experiment. These results demonstrate the proposed SSVEP-BCI system is efficient for controlling the quadcopter.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Obarska202033281645,
  title = {Threats to Mental Health Facilitated by Dating Applications Use Among Men Having Sex With Men.},
  author = {Obarska, K and Szymczak, K and Lewczuk, K and Gola, M},
  journal = {Frontiers in psychiatry},
  year = {2020},
  doi = {10.3389/fpsyt.2020.584548},
  pmid = {33281645},
  url = {https://pubmed.ncbi.nlm.nih.gov/33281645/},
  abstract = {In the last years, dating applications (DAs) have had a significant impact on the way in which people seek sexual and romantic relationships. Social groups, such as men having sex with men (MSM), who can experience discrimination and social isolation, find DAs especially engaging and helpful in finding sexual partners. Previous studies have provided evidence showing vulnerability to mental health problems among the MSM population-these problems can be potentially facilitated by DAs use. Excessive use of DAs is associated with lower well-being and life satisfaction, depression, higher substance use, and lower sleep quality. Therefore, there is a need for a better understanding of psychological functioning and risk factors associated with the use of DAs among MSM, which we focus on in this review. We also discuss two relatively new research areas: compulsive sexual behavior disorder and chemsex, and their relation to geosocial-networking mobile technologies. Finally, we point out the limitations of available studies on the mental health of MSM using DAs and propose further research directions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Adam202031894624,
  title = {The role of midfrontal theta oscillations across the development of cognitive control in preschoolers and school-age children.},
  author = {Adam, N and Blaye, A and Gulbinaite, R and Delorme, A and Farrer, C},
  journal = {Developmental science},
  year = {2020},
  doi = {10.1111/desc.12936},
  pmid = {31894624},
  url = {https://pubmed.ncbi.nlm.nih.gov/31894624/},
  abstract = {The development of cognitive control enables children to better resist acting based on distracting information that interferes with the current action. Cognitive control improvement serves different functions that differ in part by the type of interference to resolve. Indeed, resisting to interference at the task-set level or at the response-preparation level is, respectively, associated with cognitive flexibility and inhibition. It is, however, unknown whether the same neural mechanism underlies these two functions across development. Studies in adults have revealed the contribution of midfrontal theta (MFT) oscillations in interference resolution. This study investigated whether MFT is involved in the resolution of different types of interference in two age groups identified as corresponding to different latent structures of executive functions. Preschool (4-6 years) and school children (6-8 years) were tested with a task involving interference at the response level and/or the task-set level while (electroencephalogram) EEG was recorded. Behaviorally, response time and accuracy were affected by task-set. Both age groups were less accurate when the interference occurred at the task-set level and only the younger group showed decreased accuracy when interference was presented at the response-preparation level. Furthermore, MFT power was increased, relative to the baseline, during the resolution of both types of interference and in both age groups. These findings suggest that MFT is involved in immature cognitive control (i.e., preschool and school-ages), by orchestrating its different cognitive processes, irrespective of the interference to resolve and of the level of cognitive control development (i.e., the degree of differentiation of executive functions).},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wen202032833638,
  title = {The EEG Signal Analysis for Spatial Cognitive Ability Evaluation Based on Multivariate Permutation Conditional Mutual Information-Multi-Spectral Image.},
  author = {Wen, D and Yuan, J and Zhou, Y and Xu, J and Song, H and Liu, Y and Xu, Y and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.3018959},
  pmid = {32833638},
  url = {https://pubmed.ncbi.nlm.nih.gov/32833638/},
  abstract = {This study aims to find an effective method to evaluate the efficacy of cognitive training of spatial memory under a virtual reality environment, by classifying the EEG signals of subjects in the early and late stages of spatial cognitive training. This study proposes a new EEG signal analysis method based on Multivariate Permutation Conditional Mutual Information-Multi-Spectral Image (MPCMIMSI). This method mainly considers the relationship between the coupled features of EEG signals in different channel pairs and transforms the multivariate permutation conditional mutual information features into multi-spectral images. Then, a convolutional neural networks (CNN) model classifies the resultant image data into different stages of cognitive training to objectively assess the efficacy of the training. Compared to the multi-spectral image transformation method based on Granger causality analysis (GCA) and permutation conditional mutual information (PCMI), the MPCMIMSI led to better classification performance, which can be as high as 95% accuracy. More specifically, the Theta-Beta2-Gamma-band combination has the best accuracy. The proposed MPCMIMSI method outperforms the multi-spectral image transformation methods based on GCA and PCMI in terms of classification performance. The MPCMIMSI feature in the Theta-Beta2-Gamma band is an effective biomarker for assessing the efficacy of spatial memory training. The proposed EEG feature-extraction method based on MPCMIMSI offers a new window to characterize spatial information of the noninvasive EEG recordings and might apply to assessing other brain functions.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Zhang202032746309,
  title = {Stress-Induced Effects in Resting EEG Spectra Predict the Performance of SSVEP-Based BCI.},
  author = {Zhang, HY and Stevenson, CE and Jung, TP and Ko, LW},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.3005771},
  pmid = {32746309},
  url = {https://pubmed.ncbi.nlm.nih.gov/32746309/},
  abstract = {Most research in Brain-Computer-Interfaces (BCI) focuses on technologies to improve accuracy and speed. Little has been done on the effects of subject variability, both across individuals and within the same individual, on BCI performance. For example, stress, arousal, motivation, and fatigue can all affect the electroencephalogram (EEG) signals used by a BCI, which in turn impacts performance. Overcoming the impact of such user variability on BCI performance is an impending and inevitable challenge for routine applications of BCIs in the real world. To systematically explore the factors affecting BCI performance, this study embeds a Steady-State Visually Evoked Potential (SSVEP) based BCI into a "game with a purpose" (GWAP) to obtain data over significant lengths of time, under both high- and low-stress conditions. Ten healthy volunteers played a GWAP that resembles popular match-three games, such as Jewel Quest, Zoo Boom, or Candy Crush. We recorded the target search time, target search accuracy, and EEG signals during gameplay to investigate the impacts of stress on EEG signals and BCI performance. We used Canonical Correlation Analysis (CCA) to determine whether the subject had found and attended to the correct target. The experimental results show that SSVEP target-classification accuracy is reduced by stress. We also found a negative correlation between EEG spectra and the SNR of EEG in the frontal and occipital regions during gameplay, with a larger negative correlation for the high-stress conditions. Furthermore, CCA also showed that when the EEG alpha and theta power increased, the search accuracy decreased, and the spectral amplitude drop was more evident under the high-stress situation. These results provide new, valuable insights into research on how to improve the robustness of BCIs in real-world applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chiang202033018653,
  title = {Statistically Optimized Spatial Filtering in Decoding Steady-State Visual Evoked Potentials Based on Task-Related Component Analysis.},
  author = {Chiang, KJ and Nakanishi, M and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9176205},
  pmid = {33018653},
  url = {https://pubmed.ncbi.nlm.nih.gov/33018653/},
  abstract = {Task-related component analysis (TRCA) has been the most effective spatial filtering method in implementing high-speed brain-computer interfaces (BCIs) based on steady-state visual evoked potentials (SSVEPs). TRCA is a data-driven method, in which spatial filters are optimized to maximize inter-trial covariance of time-locked electroencephalographic (EEG) data, formulated as a generalized eigenvalue problem. Although multiple eigenvectors can be obtained by TRCA, the traditional TRCA-based SSVEP detection considered only one that corresponds to the largest eigenvalue to reduce its computational cost. This study proposes using multiple eigen-vectors to classify SSVEPs. Specifically, this study integrates a task consistency test, which statistically identifies whether the component reconstructed by each eigenvector is task-related or not, with the TRCA-based SSVEP detection method. The proposed method was evaluated by using a 12-class SSVEP dataset recorded from 10 subjects. The study results indicated that the task consistency test usually identified and suggested more than one eigenvectors (i.e., spatial filters). Further, the use of additional spatial filters significantly improved the classification accuracy of the TRCA-based SSVEP detection.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Kowalewska202032943868,
  title = {Spotlight on Compulsive Sexual Behavior Disorder: A Systematic Review of Research on Women.},
  author = {Kowalewska, E and Gola, M and Kraus, SW and Lew-Starowicz, M},
  journal = {Neuropsychiatric disease and treatment},
  year = {2020},
  doi = {10.2147/NDT.S221540},
  pmid = {32943868},
  url = {https://pubmed.ncbi.nlm.nih.gov/32943868/},
  abstract = {World Health Organization recently included compulsive sexual behavior disorder (CSBD) to the upcoming 11th edition of International Classification of Diseases (6C72). Despite the potential benefits of this decision (eg, the acceleration of research in the field will allow the development of effective treatments), previous research focused mainly on men, and as a result, we do not have an accurate clinical picture of compulsive sexual behavior (CSB) among women. Therefore, in this systematic review, we aim to present available knowledge on this topical subject. Literature search was conducted in the guideline of PRISMA methodology. Studies were identified from multiple databases including Academic Search Ultimate, SocINDEX, PsycARTICLES, PsycINFO, PubMed, and MEDLINE. Out of a total of 10,531 articles identified and screened, 58 were included in this review. Included studies covered the following topics: prevalence and etiology of CSB, behavioral and cognitive processes involved, comorbidities, personality traits, psychosocial and interpersonal difficulties, traumatic experiences, and treatments. Available studies indicate that CSB symptom severity is lower in women than in men. Overall, women reported consuming pornography less often than men and exhibit lower rates of feeling urges to these materials. CSB symptoms (including problematic pornography use) have been found to be positively related to trait psychopathy, impulsivity, sensation seeking, attention-deficit/hyperactivity disorder symptoms, obsessive-compulsive disorder, pathological buying, sexual dysfunctions, general psychopathology, child sexual abuse, while negatively related to dispositional mindfulness. Conclusions that can be drawn from prior studies are considerably limited. There are no accurate estimates of the CSB prevalence or severity among women, and studies have been mostly conducted on non-clinical populations, which has limited application for women diagnosed with CSBD.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Cannard202032164854,
  title = {Self-health monitoring and wearable neurotechnologies.},
  author = {Cannard, C and Brandmeyer, T and Wahbeh, H and Delorme, A},
  journal = {Handbook of clinical neurology},
  year = {2020},
  doi = {10.1016/B978-0-444-63934-9.00016-0},
  pmid = {32164854},
  url = {https://pubmed.ncbi.nlm.nih.gov/32164854/},
  abstract = {Brain-computer interfaces and wearable neurotechnologies are now used to measure real-time neural and physiologic signals from the human body and hold immense potential for advancements in medical diagnostics, prevention, and intervention. Given the future role that wearable neurotechnologies will likely serve in the health sector, a critical state-of-the-art assessment is necessary to gain a better understanding of their current strengths and limitations. In this chapter we present wearable electroencephalography systems that reflect groundbreaking innovations and improvements in real-time data collection and health monitoring. We focus on specifications reflecting technical advantages and disadvantages, discuss their use in fundamental and clinical research, their current applications, limitations, and future directions. While many methodological and ethical challenges remain, these systems host the potential to facilitate large-scale data collection far beyond the reach of traditional research laboratory settings.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Nakanishi202032078554,
  title = {Questionable Classification Accuracy Reported in "Designing a Sum of Squared Correlations Framework for Enhancing SSVEP-Based BCIs".},
  author = {Nakanishi, M and Xu, M and Wang, Y and Chiang, KJ and Han, J and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.2974272},
  pmid = {32078554},
  url = {https://pubmed.ncbi.nlm.nih.gov/32078554/},
  abstract = {This commentary presents a replication study to verify the effectiveness of a sum of squared correlations (SSCOR)-based steady-state visual evoked potentials (SSVEPs) decoding method proposed by Kumar et al.. We implemented the SSCOR-based method in accordance with their descriptions and estimated its classification accuracy using a benchmark SSVEP dataset with cross validation. Our results showed significantly lower classification accuracy compared with the ones reported in Kumar et al.'s study. We further investigated the sources of performance discrepancy by simulating data leakage between training and test datasets. The classification performance of the simulation was remarkably similar to those reported by Kumar et al.. We, therefore, question the validity of evaluation and conclusions drawn in Kumar et al.'s study.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Grubbs202032027146,
  title = {Moral incongruence and compulsive sexual behavior: Results from cross-sectional interactions and parallel growth curve analyses.},
  author = {Grubbs, JB and Kraus, SW and Perry, SL and Lewczuk, K and Gola, M},
  journal = {Journal of abnormal psychology},
  year = {2020},
  doi = {10.1037/abn0000501},
  pmid = {32027146},
  url = {https://pubmed.ncbi.nlm.nih.gov/32027146/},
  abstract = {Despite controversies about the diagnosis, the World Health Organization recently elected to include compulsive sexual behavior disorder in the 11th edition of the International Classification of Diseases. Both recent and remote works have suggested that various cultural factors such as personal religiousness and morality can influence both the experience and expression of compulsive sexual behaviors. Because prior works have indicated that pornography use is likely to be the most common expression of compulsive sexual behavior, the present work sought to examine whether moral incongruence about pornography use may account for a substantive part of self-reports of compulsive sexual behavior. In 2 studies involving 4 samples, the present work tested the hypothesis that moral incongruence would positively predict self-reported compulsivity in pornography use. In Study 1, across 3 samples (Sample 1, N = 467; Sample 2, N = 739; Sample 3, N = 1,461), including 2 matched to U.S. nationally representative norms (Samples 2 and 3), results indicated that moral incongruence was a substantive and robust predictor of self-reported compulsivity. In Study 2 (baseline N = 850), parallel process latent growth curve analyses over the course of 1 year revealed that the trajectories of pornography use, self-reported compulsivity, and moral disapproval of such use covaried together over time. Collectively, these results underscore the contention that personal morality may influence individuals' self-perceptions of their sexual behaviors, which, in turn, may complicate efforts to accurately diagnose compulsive sexual behavior disorder. (PsycInfo Database Record (c) 2020 APA, all rights reserved).},
  note = {PubMed query source: Mateusz Gola}
}

@article{Miyakoshi202034296114,
  title = {Modulation of Frontal Oscillatory Power during Blink Suppression in Children: Effects of Premonitory Urge and Reward.},
  author = {Miyakoshi, M and Jurgiel, J and Dillon, A and Chang, S and Piacentini, J and Makeig, S and Loo, SK},
  journal = {Cerebral cortex communications},
  year = {2020},
  doi = {10.1093/texcom/tgaa046},
  pmid = {34296114},
  url = {https://pubmed.ncbi.nlm.nih.gov/34296114/},
  abstract = {There is a dearth of studies examining the underlying mechanisms of blink suppression and the effects of urge and reward, particularly those measuring subsecond electroencephalogram (EEG) brain dynamics. To address these issues, we designed an EEG study to ask 3 questions: 1) How does urge develop? 2) What are EEG-correlates of blink suppression? 3) How does reward change brain dynamics related to urge suppression? This study examined healthy children ( N  = 26, age 8-12 years) during blink suppression under 3 conditions: blink freely (i.e., no suppression), blink suppressed, and blink suppressed for reward. During suppression conditions, children used a joystick to indicate their subjective urge to blink. Results showed that 1) half of the trials were associated with clearly defined urge time course of ~7 s, which was accompanied by EEG delta (1-4 Hz) power reduction localized at anterior cingulate cortex (ACC); 2) the EEG correlates of blink suppression were found in left prefrontal theta (4-8 Hz) power elevation; and 3) reward improved blink suppression performance while reducing the EEG delta power observed in ACC. We concluded that the empirically supported urge time course and underlying EEG modulations provide a subsecond chronospatial model of the brain dynamics during urge- and reward-mediated blink suppression.},
  note = {PubMed query source: Scott Makeig}
}

@article{Panwar202032746311,
  title = {Modeling EEG Data Distribution With a Wasserstein Generative Adversarial Network to Predict RSVP Events.},
  author = {Panwar, S and Rad, P and Jung, TP and Huang, Y},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.3006180},
  pmid = {32746311},
  url = {https://pubmed.ncbi.nlm.nih.gov/32746311/},
  abstract = {Electroencephalography (EEG) data are difficult to obtain due to complex experimental setups and reduced comfort with prolonged wearing. This poses challenges to train powerful deep learning model with the limited EEG data. Being able to generate EEG data computationally could address this limitation. We propose a novel Wasserstein Generative Adversarial Network with gradient penalty (WGAN-GP) to synthesize EEG data. This network addresses several modeling challenges of simulating time-series EEG data including frequency artifacts and training instability. We further extended this network to a class-conditioned variant that also includes a classification branch to perform event-related classification. We trained the proposed networks to generate one and 64-channel data resembling EEG signals routinely seen in a rapid serial visual presentation (RSVP) experiment and demonstrated the validity of the generated samples. We also tested intra-subject cross-session classification performance for classifying the RSVP target events and showed that class-conditioned WGAN-GP can achieve improved event-classification performance over EEGNet.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lewczuk202032903803,
  title = {Mobile Internet Technologies, Ecological Momentary Assessment, and Intervention-Poison and Remedy for New Online Problematic Behaviors in ICD-11.},
  author = {Lewczuk, K and Gorowska, M and Li, Y and Gola, MK},
  journal = {Frontiers in psychiatry},
  year = {2020},
  doi = {10.3389/fpsyt.2020.00807},
  pmid = {32903803},
  url = {https://pubmed.ncbi.nlm.nih.gov/32903803/},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wong202032841119,
  title = {Inter- and Intra-Subject Transfer Reduces Calibration Effort for High-Speed SSVEP-Based BCIs.},
  author = {Wong, CM and Wang, Z and Wang, B and Lao, KF and Rosa, A and Xu, P and Jung, TP and Chen, CLP and Wan, F},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.3019276},
  pmid = {32841119},
  url = {https://pubmed.ncbi.nlm.nih.gov/32841119/},
  abstract = {Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) that can deliver a high information transfer rate (ITR) usually require subject's calibration data to learn the class- and subject-specific model parameters (e.g. the spatial filters and SSVEP templates). Normally, the amount of the calibration data for learning is proportional to the number of classes (or visual stimuli), which could be huge and consequently lead to a time-consuming calibration. This study presents a transfer learning scheme to substantially reduce the calibration effort. Inspired by the parameter-based and instance-based transfer learning techniques, we propose a subject transfer based canonical correlation analysis (stCCA) method which utilizes the knowledge within subject and between subjects, thus requiring few calibration data from a new subject. The evaluation study on two SSVEP datasets (from Tsinghua and UCSD) shows that the stCCA method performs well with only a small amount of calibration data, providing an ITR at 198.18±59.12 (bits/min) with 9 calibration trials in the Tsinghua dataset and 111.04±57.24 (bits/min) with 3 trials in the UCSD dataset. Such performances are comparable to those from using the multi-stimulus CCA (msCCA) and the ensemble task-related component analysis (eTRCA) methods with the minimally required calibration data (i.e., at least 40 trials in the Tsinghua dataset and at least 12 trials in the UCSD dataset), respectively. Inter- and intra-subject transfer helps the recognition method achieve high ITR with extremely little calibration effort. The proposed approach saves much calibration effort without sacrificing the ITR, which would be significant for practical SSVEP-based BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu202032149621,
  title = {Implementing Over 100 Command Codes for a High-Speed Hybrid Brain-Computer Interface Using Concurrent P300 and SSVEP Features.},
  author = {Xu, M and Han, J and Wang, Y and Jung, TP and Ming, D},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2020},
  doi = {10.1109/TBME.2020.2975614},
  pmid = {32149621},
  url = {https://pubmed.ncbi.nlm.nih.gov/32149621/},
  abstract = {Recently, electroencephalography (EEG)- based brain-computer interfaces (BCIs) have made tremendous progress in increasing communication speed. However, current BCI systems could only implement a small number of command codes, which hampers their applicability. This study developed a high-speed hybrid BCI system containing as many as 108 instructions, which were encoded by concurrent P300 and steady-state visual evoked potential (SSVEP) features and decoded by an ensemble task-related component analysis method. Notably, besides the frequency-phase-modulated SSVEP and time-modulated P300 features as contained in the traditional hybrid P300 and SSVEP features, this study found two new distinct EEG features for the concurrent P300 and SSVEP features, i.e., time-modulated SSVEP and frequency-phase- modulated P300. Ten subjects spelled in both offline and online cued-guided spelling experiments. Other ten subjects took part in online copy-spelling experiments. Offline analyses demonstrate that the concurrent P300 and SSVEP features can provide adequate classification information to correctly select the target from 108 characters in 1.7 seconds. Online cued-guided spelling and copy-spelling tests further show that the proposed BCI system can reach an average information transfer rate (ITR) of 172.46 ± 32.91 bits/min and 164.69 ± 33.32 bits/min respectively, with a peak value of 238.41 bits/min (The demo video of online copy-spelling can be found at https://www.youtube.com/watch?v=EW2Q08oHSBo). We expand a BCI instruction set to over 100 command codes with high-speed in an efficient manner, which significantly improves the degree of freedom of BCIs. This study hold promise for broadening the applications of BCI systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Liang202033110406,
  title = {Human Brain Dynamics Reflect the Correctness and Presentation Modality of Physics Concept Memory Retrieval.},
  author = {Liang, CP and She, HC and Huang, LY and Chou, WC and Chen, SC and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2020},
  doi = {10.3389/fnhum.2020.00331},
  pmid = {33110406},
  url = {https://pubmed.ncbi.nlm.nih.gov/33110406/},
  abstract = {Human memory retrieval is the core cognitive process of the human brain whenever it is processing the information. Less study has focused on exploring the neural correlates of the memory retrieval of scientific concepts when presented in word and picture modalities. Fewer studies have investigated the differences in the involved brain regions and how the brain dynamics in these regions would associate with the accuracy of the memory retrieval process. Therefore, this study specifically focused on investigating the human brain dynamics of participants when they retrieve physics concepts in word vs. pictorial modalities, and whether electroencephalogram (EEG) activities can predict the correctness of the retrieval of physics concepts. The results indicated that word modality induced a significant stronger right frontal theta augmentation than pictorial modality during the physics concepts retrieval process, whereas the picture modality induced a significantly greater right parietal alpha suppression than the word modality throughout the retrieval process spurred by the physics concept presentations. In addition, greater frontal midline theta augmentation was observed for incorrect responses than the correct responses during retrieve physics concepts. Moreover, the frontal midline theta power has greater negative predictive power for predicting the accuracy of physics concepts retrieval. In summary, the participants were more likely to retrieve physics concepts correctly if a lower amount of theta were allocated during the maintaining period from 2,000 ms through 3,500 ms before making responses. It provides insight for our future application of brain computer interface (BCI) in real-time science learning. This study implies that the lower frontal midline theta power is associated with a lower degree of cognitive control and active maintenance of representations as participants approach a correct answer.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Draps202032690426,
  title = {Gray Matter Volume Differences in Impulse Control and Addictive Disorders-An Evidence From a Sample of Heterosexual Males.},
  author = {Draps, M and Sescousse, G and Potenza, MN and Marchewka, A and Duda, A and Lew-Starowicz, M and Kopera, M and Jakubczyk, A and Wojnar, M and Gola, M},
  journal = {The journal of sexual medicine},
  year = {2020},
  doi = {10.1016/j.jsxm.2020.05.007},
  pmid = {32690426},
  url = {https://pubmed.ncbi.nlm.nih.gov/32690426/},
  abstract = {The classification of addictions and impulse control disorders is changing as reflected in the 11th version of International Classification of Disorders (WHO, 2018). However, studies focusing on direct comparison of structural brain differences in behavioral and substance addictions are limited. Here, we contrast gray matter volumes (GMVs) across groups of individuals with compulsive sexual behavior disorder (CSBD), gambling disorder (GD), and alcohol use disorder (AUD) with those with none of these disorders (healthy controls participants; HCs). Voxel-based morphometry was used to study brain structure, and severities of addiction symptoms were assessed with questionnaires. To identify brain regions related to severities of addictions, correlations between questionnaire scores and GMVs were computed. We collected magnetic resonance imaging (GMVs) data from 26 patients with CSBD, 26 patients with GD, 21 patients with AUD, and 25 HC participants (all heterosexual males; age: 24-60; mean = 34.5, standard deviation = 6.48). Affected individuals (CSBD, GD, AUD) compared with HC participants showed smaller GMVs in the left frontal pole, specifically in the orbitofrontal cortex. The most pronounced differences were observed in the GD and AUD groups, and the least in the CSBD group. In addition, a negative correlation was found between GMVs and disorder severity in the CSBD group. Higher severity of CSBD symptoms was correlated with decreased GMVs in the right anterior cingulate gyrus. Our findings suggest similarities between CSBD and addictions. This study is the first showing smaller GMVs in 3 clinical groups of CSBD, GD, and AUD. But the study was limited only to heterosexual men. Longitudinal studies should examine the extent to which ventral prefrontal decrements in volume may represent preexisting vulnerability factors or whether they may develop with disorder progression. Our research extends prior findings in substance use disorders of lower GMVs in prefrontal cortical volumes among 3 clinical groups of patients with specific impulse control (CSBD) and behavioral (GD) and substance (AUD) addictive disorders. The negative correlation between CSBD symptoms and GMV of right anterior cingulate gyrus suggests a link with clinical symptomatology. Draps M, Sescousse G, Potenza MN, et al. Gray Matter Volume Differences in Impulse Control and Addictive Disorders-An Evidence From a Sample of Heterosexual Males. J Sex Med 2020;17:1761-1769.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Pernet202033519362,
  title = {From BIDS-Formatted EEG Data to Sensor-Space Group Results: A Fully Reproducible Workflow With EEGLAB and LIMO EEG.},
  author = {Pernet, CR and Martinez-Cancino, R and Truong, D and Makeig, S and Delorme, A},
  journal = {Frontiers in neuroscience},
  year = {2020},
  doi = {10.3389/fnins.2020.610388},
  pmid = {33519362},
  url = {https://pubmed.ncbi.nlm.nih.gov/33519362/},
  abstract = {Reproducibility is a cornerstone of scientific communication without which one cannot build upon each other's work. Because modern human brain imaging relies on many integrated steps with a variety of possible algorithms, it has, however, become impossible to report every detail of a data processing workflow. In response to this analytical complexity, community recommendations are to share data analysis pipelines (scripts that implement workflows). Here we show that this can easily be done using EEGLAB and tools built around it. BIDS tools allow importing all the necessary information and create a study from electroencephalography (EEG)-Brain Imaging Data Structure compliant data. From there preprocessing can be carried out in only a few steps using EEGLAB and statistical analyses performed using the LIMO EEG plug-in. Using Wakeman and Henson (2015) face dataset, we illustrate how to prepare data and build different statistical models, a standard factorial design (faces  ∗  repetition), and a more modern trial-based regression approach for the stimulus repetition effect, all in a few reproducible command lines.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Nakanishi202031329104,
  title = {Facilitating Calibration in High-Speed BCI Spellers via Leveraging Cross-Device Shared Latent Responses.},
  author = {Nakanishi, M and Wang, YT and Wei, CS and Chiang, KJ and Jung, TP},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2020},
  doi = {10.1109/TBME.2019.2929745},
  pmid = {31329104},
  url = {https://pubmed.ncbi.nlm.nih.gov/31329104/},
  abstract = {This paper proposes a novel device-to-device transfer-learning algorithm for reducing the calibration cost in a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) speller by leveraging electroencephalographic (EEG) data previously acquired by different EEG systems. The transferring is done by projecting the scalp-channel EEG signals onto a shared latent domain across devices. Three spatial filtering techniques, including channel averaging, canonical correlation analysis (CCA), and task-related component analysis (TRCA), were employed to extract the shared responses from different devices. The transferred data were integrated into a template-matching-based algorithm to detect SSVEPs. To evaluate its transferability, this paper conducted two sessions of simulated online BCI experiments with ten subjects using 40 visual stimuli modulated by joint frequency-phase coding method. In each session, two different EEG devices were used: first, the Quick-30 system (Cognionics, Inc.) with dry electrodes, and second, the ActiveTwo system (BioSemi, Inc.) with wet electrodes. The proposed method with CCA- and TRCA-based spatial filters achieved significantly higher classification accuracy compared with the calibration-free standard CCA-based method. This paper validated the feasibility and effectiveness of the proposed method in implementing calibration-free SSVEP-based BCIs. The proposed method has great potentials to enhance practicability and usability of real-world SSVEP-based BCI applications by leveraging user-specific data recorded in previous sessions even with different EEG systems and montages.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Ko202032375139,
  title = {Eyeblink recognition improves fatigue prediction from single-channel forehead EEG in a realistic sustained attention task.},
  author = {Ko, LW and Komarov, O and Lai, WK and Liang, WG and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2020},
  doi = {10.1088/1741-2552/ab909f},
  pmid = {32375139},
  url = {https://pubmed.ncbi.nlm.nih.gov/32375139/},
  abstract = {A passive brain-computer interface recognizes its operator's cognitive state without an explicitly performed control task. This technique is commonly used in conjunction with consumer-grade EEG devices for detecting the conditions of fatigue, attention, emotional arousal, or motion sickness. While it is easy to mount the sensors in the forehead area, which is not covered with hair, the recorded signals become greatly contaminated with eyeblink and movement artifacts, which makes it a challenge to acquire the data of suitable for analysis quality, particularly in few channel systems where a lack of spatial information limits the applicability of sophisticated signal cleaning algorithms. In this article, we demonstrate that by combining the features associated with electrocortical activities and eyeblink recognition analysis, it becomes feasible to design an accurate system for the inattention state prediction using just a single EEG sensor. Fifteen healthy 22-28 years old participants took part in the experiment that implemented a realistic sustained attention task of nighttime highway driving in a virtual environment. The EEG data were collected using a portable wireless Mindo-4 device, which constitutes an adjustable elastic strip with foam-based sensors, a data-acquisition module, an amplification and digitizing unit, and a Bluetooth[Formula: see text] module. The spectral analysis of the EEG samples that immediately preceded the lane departure events revealed alterations in the tonic power spectral density, which accompanied elongations in the drivers' reaction times. The RMSE of the predicted reaction times, which are based on a combination of the brain-related and eyeblink features, is 0.034 ± 0.019 s, and the r 2  is 0.885 ± 0.057 according to a within-session leave-one-trial-out cross-validation. The drowsiness prediction from a frontal single-channel setup can achieve a comparable performance with using an array of occipital EEG sensors. As a direct result of utilizing a dry sensor placed in the non-covered with hair head area, the proposed approach in this study is low-cost and user-friendly.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cummings202033414710,
  title = {Evidence for [Coronal] Underspecification in Typical and Atypical Phonological Development.},
  author = {Cummings, AE and Ogiela, DA and Wu, YC},
  journal = {Frontiers in human neuroscience},
  year = {2020},
  doi = {10.3389/fnhum.2020.580697},
  pmid = {33414710},
  url = {https://pubmed.ncbi.nlm.nih.gov/33414710/},
  abstract = {The Featurally Underspecified Lexicon (FUL) theory predicts that [coronal] is the language universal default place of articulation for phonemes. This assumption has been consistently supported with adult behavioral and event-related potential (ERP) data; however, this underspecification claim has not been tested in developmental populations. The purpose of this study was to determine whether children demonstrate [coronal] underspecification patterns similar to those of adults. Two English consonants differing in place of articulation, [labial] /b/ and [coronal] /d/, were presented to 24 children (ages 4-6 years) characterized by either a typically developing phonological system (TD) or a phonological disorder (PD). Two syllables, /bɑ/ and /dɑ/, were presented in an ERP oddball paradigm where both syllables served as the standard and deviant stimulus in opposite stimulus sets. Underspecification was examined with three analyses: traditional mean amplitude measurements, cluster-based permutation tests, and single-trial general linear model (GLM) analyses of single-subject data. Contrary to previous adult findings, children with PD demonstrated a large positive mismatch response (PMR) to /bɑ/ while the children with TD exhibited a negative mismatch response (MMN); significant group differences were not observed in the /dɑ/ responses. Moreover, the /bɑ/ deviant ERP response was significantly larger in the TD children than in the children with PD. At the single-subject level, more children demonstrated mismatch responses to /dɑ/ than to /bɑ/, though some children had a /bɑ/ mismatch response and no /dɑ/ mismatch response. While both groups of children demonstrated similar responses to the underspecified /dɑ/, their neural responses to the more specified /bɑ/ varied. These findings are interpreted within a proposed developmental model of phonological underspecification, wherein children with PD are functioning at a developmentally less mature stage of phonological acquisition than their same-aged TD peers. Thus, phonological underspecification is a phenomenon that likely develops over time with experience and exposure to language.},
  note = {PubMed query source: Ying Wu}
}

@article{Chang202031329105,
  title = {Evaluation of Artifact Subspace Reconstruction for Automatic Artifact Components Removal in Multi-Channel EEG Recordings.},
  author = {Chang, CY and Hsu, SH and Pion-Tonachini, L and Jung, TP},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2020},
  doi = {10.1109/TBME.2019.2930186},
  pmid = {31329105},
  url = {https://pubmed.ncbi.nlm.nih.gov/31329105/},
  abstract = {Artifact subspace reconstruction (ASR) is an automatic, online-capable, component-based method that can effectively remove transient or large-amplitude artifacts contaminating electroencephalographic (EEG) data. However, the effectiveness of ASR and the optimal choice of its parameter have not been systematically evaluated and reported, especially on actual EEG data. This paper systematically evaluates ASR on 20 EEG recordings taken during simulated driving experiments. Independent component analysis (ICA) and an independent component classifier are applied to separate artifacts from brain signals to quantitatively assess the effectiveness of the ASR. ASR removes more eye and muscle components than brain components. Even though some eye and muscle components retain after ASR cleaning, the power of their temporal activities is reduced. Study results also showed that ASR cleaning improved the quality of a subsequent ICA decomposition. Empirical results show that the optimal ASR parameter is between 20 and 30, balancing between removing non-brain signals and retaining brain activities. With an appropriate choice of parameter, ASR can be a powerful and automatic artifact removal approach for offline data analysis or online real-time EEG applications such as clinical monitoring and brain-computer interfaces.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lewczuk202031818724,
  title = {Evaluating Pornography Problems Due to Moral Incongruence Model.},
  author = {Lewczuk, K and Glica, A and Nowakowska, I and Gola, M and Grubbs, JB},
  journal = {The journal of sexual medicine},
  year = {2020},
  doi = {10.1016/j.jsxm.2019.11.259},
  pmid = {31818724},
  url = {https://pubmed.ncbi.nlm.nih.gov/31818724/},
  abstract = {To date, multiple models of problematic pornography use have been proposed, but attempts to validate them have been scarce. In our study, we aimed to evaluate the Pornography Problems due to Moral Incongruence model proposing that self-appraisals of pornography addiction stem from (i) general dysregulation, (ii) habits of use, and (iii) moral incongruence between internalized norms and behavior. We investigated whether the model can be used to adequately explain the self-perceptions of addiction to pornography (model 1) and a broader phenomenon of problematic pornography use (model 2). An online, nationally representative study was conducted on a sample of 1036 Polish adult participants, of whom, 880 declared a lifetime history of viewing pornography. The outcomes were self-perceived pornography addiction, problematic pornography use, avoidant coping, frequency of pornography use, religiosity, moral disapproval of pornography, and related variables. Our results indicated that avoidant coping (an indicator of general dysregulation), frequency of pornography use (indicator of habits of use), and the distress connected with incongruence between own sexual behavior and internalized norms, attitudes and beliefs positively contributed to self-perceived addiction (model 1) as well as problematic pornography use (model 2). This broadly confirms the basic shape of the PPMI model. There were, however, notable differences between the models. Moral incongruence related distress was only weakly related to self-perceived addiction (β = 0.15, P < .001), with a stronger relation for problematic pornography use (β = 0.31, P < .001). When controlling for other factors, religiosity weakly predicted problematic pornography use (β = 0.13, P < .001), but not self-perceived addiction to pornography (β = 0.03, P = .368). Frequency of pornography use was the strongest predictor of both self-perceived addiction (β = 0.52, P < .001) and problematic pornography use (β = 0.43, P < .001). Factors proposed within the PPMI model are distinctly relevant intervention targets, and they should be considered in the process of diagnosis and treatment. The presented study is the first to evaluate PPMI model. Its main limitation is that it has a cross-sectional design. The PPMI model is a promising framework for investigating the factors related to self-perceived addiction and problematic pornography use. Despite the differences between the models and in the strength of specific predictors, (i) dysregulation, (ii) habits of use, and (iii) moral incongruence all uniquely contribute to self-perceived addiction and problematic pornography use. Lewczuk, K., Glica, A., Nowakowska, I., et al. Evaluating Pornography Problems Due to Moral Incongruence Model. J Sex Med 2020;17:300-311.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wang202033018724,
  title = {Enhancing performance of SSVEP-based BCI by unsupervised learning information from test trials.},
  author = {Wang, L and Xu, M and Mei, J and Han, J and Wang, Y and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9176851},
  pmid = {33018724},
  url = {https://pubmed.ncbi.nlm.nih.gov/33018724/},
  abstract = {Steady-State Visual Evoked Potentials (SSVEPs) have become one of the most used neural signals for brain- computer interfaces (BCIs) due to their stability and high signal- to-noise rate. However, the performance of SSVEP-based BCIs would degrade with a few training samples. This study was proposed to enhance the detection of SSVEP by combining the supervised learning information from training samples and the unsupervised learning information from the trial to be tested. A new method, i.e. cyclic shift trials (CST), was proposed to generate new calibration samples from the test data, which were furtherly used to create the templates and spatial filters of task- related component analysis (TRCA). The test-trial templates and spatial filters were combined with training-sample templates and spatial filters to recognize SSVEP. The proposed algorithm was tested on a benchmark dataset. As a result, it reached significantly higher classification accuracy than traditional TRCA when only two training samples were used. Speciflcally, the accuracy was improved by 9.5% for 0.7s data. Therefore, this study demonstrates CST is effective to improve the performance of SSVEP-BCI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Piazza202032226371,
  title = {EEG Effective Source Projections Are More Bilaterally Symmetric in Infants Than in Adults.},
  author = {Piazza, C and Cantiani, C and Miyakoshi, M and Riva, V and Molteni, M and Reni, G and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2020},
  doi = {10.3389/fnhum.2020.00082},
  pmid = {32226371},
  url = {https://pubmed.ncbi.nlm.nih.gov/32226371/},
  abstract = {Although anatomical brain hemispheric asymmetries have been clearly documented in the infant brain, findings concerning functional hemispheric specialization have been inconsistent. The present report aims to assess whether bilaterally symmetric synchronous activity between the two hemispheres is a characteristic of the infant brain. To asses cortical bilateral synchronicity, we used decomposition by independent component analysis (ICA) of high-density electroencephalographic (EEG) data collected in an auditory passive oddball paradigm. Decompositions of concatenated  64-channel  EEG data epochs from each of 34 typically developing 6-month-old infants and from 18 healthy young adults participating in the same passive auditory oddball protocol were compared to characterize differences in functional brain organization between early life and adulthood. Our results show that infant EEG decompositions comprised a larger number of independent component (IC) effective source processes compatible with a cortical origin and having bilaterally near-symmetric scalp projections (13.8% of the infant data ICs presented a bilateral pattern vs. 4.3% of the adult data ICs). These IC projections could be modeled as the sum of potentials volume-conducted to the scalp from synchronous locally coherent field activities in corresponding left and right cortical source areas. To conclude, in this paradigm, source-resolved infant brain EEG exhibited more bilateral synchronicity than EEG produced by the adult brain, supporting the hypothesis that more strongly unilateral and likely more functionally specialized unihemispheric cortical field activities are concomitants of brain maturation.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wang202032746289,
  title = {Dynamic Reorganization of Functional Connectivity Unmasks Fatigue Related Performance Declines in Simulated Driving.},
  author = {Wang, H and Liu, X and Hu, H and Wan, F and Li, T and Gao, L and Bezerianos, A and Sun, Y and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.2999599},
  pmid = {32746289},
  url = {https://pubmed.ncbi.nlm.nih.gov/32746289/},
  abstract = {Although driving fatigue has long been recognized as one of the leading causes of fatal accidents worldwide, the underlying neural mechanisms remain largely unknown that impedes the developments of automatic detection techniques. This study investigated the effects of driving fatigue on the reorganization of dynamic functional connectivity (FC) through our newly developed temporal brain network analysis framework. EEG data were recorded from 20 healthy subjects (male/female = 15/5, age = 22.2 ± 3.2 years) using a remote wireless cap with 24 channels. Temporal brain networks in the theta, alpha and beta were estimated using a sliding window approach and quantitatively compared between the most vigilant and fatigue states during a 90-min simulated driving experiment. Behaviorally, subjects demonstrated a salient driving fatigue effect as reflected by a monotonic increase of reaction time and speed variation. Furthermore, we found a significantly disintegrated spatiotemporal topology of dynamic FC as shown in reduced temporal global efficiency and increased temporal local efficiency at fatigue state. Specifically, we found localized changes of temporal closeness centrality mainly resided in the frontal and parietal areas. Finally, the changes of temporal network measures were associated with those of behavioral metrics. Our findings provide new insights into dynamic characteristics of functional connectivity during driving fatigue and demonstrate the potential for using temporal network metrics as reliable biomarkers for driving fatigue detection.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xiao202031831401,
  title = {Discriminative Canonical Pattern Matching for Single-Trial Classification of ERP Components.},
  author = {Xiao, X and Xu, M and Jin, J and Wang, Y and Jung, TP and Ming, D},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2020},
  doi = {10.1109/TBME.2019.2958641},
  pmid = {31831401},
  url = {https://pubmed.ncbi.nlm.nih.gov/31831401/},
  abstract = {Event-related potentials (ERPs) are one of the most popular control signals for brain-computer interfaces (BCIs). However, they are very weak and sensitive to the experimental settings including paradigms, stimulation parameters and even surrounding environments, resulting in a diversity of ERP patterns across different BCI experiments. It's still a challenge to develop a general decoding algorithm that can adapt to the ERP diversities of different BCI datasets with small training sets. This study compared a recently developed algorithm, i.e., discriminative canonical pattern matching (DCPM), with seven ERP-BCI classification methods, i.e., linear discriminant analysis (LDA), stepwise LDA, bayesian LDA, shrinkage LDA, spatial-temporal discriminant analysis (STDA), xDAWN and EEGNet for the single-trial classification of two private EEG datasets and three public EEG datasets with small training sets. The feature ERPs of the five datasets included P300, motion visual evoked potential (mVEP), and miniature asymmetric visual evoked potential (aVEP). Study results showed that the DCPM outperformed other classifiers for all of the tested datasets, suggesting the DCPM is a robust classification algorithm for assessing a wide range of ERP components.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Qiu202032412932,
  title = {Dexmedetomidine Activation of Dopamine Neurons in the Ventral Tegmental Area Attenuates the Depth of Sedation in Mice.},
  author = {Qiu, G and Wu, Y and Yang, Z and Li, L and Zhu, X and Wang, Y and Sun, W and Dong, H and Li, Y and Hu, J},
  journal = {Anesthesiology},
  year = {2020},
  doi = {10.1097/ALN.0000000000003347},
  pmid = {32412932},
  url = {https://pubmed.ncbi.nlm.nih.gov/32412932/},
  abstract = {Dexmedetomidine induces a sedative response that is associated with rapid arousal. To elucidate the underlying mechanisms, the authors hypothesized that dexmedetomidine increases the activity of dopaminergic neurons in the ventral tegmental area, and that this action contributes to the unique sedative properties of dexmedetomidine. Only male mice were used. The activity of ventral tegmental area dopamine neurons was measured by a genetically encoded Ca indicator and patch-clamp recording. Dopamine neurotransmitter dynamics in the medial prefrontal cortex and nucleus accumbens were measured by a genetically encoded dopamine sensor. Ventral tegmental area dopamine neurons were inhibited or activated by a chemogenetic approach, and the depth of sedation was estimated by electroencephalography. Ca signals in dopamine neurons in the ventral tegmental area increased after intraperitoneal injection of dexmedetomidine (40 μg/kg; dexmedetomidine, 16.917 [14.882; 21.748], median [25%; 75%], vs. saline, -0.745 [-1.547; 0.359], normalized data, P = 0.001; n = 6 mice). Dopamine transmission increased in the medial prefrontal cortex after intraperitoneal injection of dexmedetomidine (40 μg/kg; dexmedetomidine, 10.812 [9.713; 15.104], median [25%; 75%], vs. saline, -0.498 [-0.664; -0.355], normalized data, P = 0.001; n = 6 mice) and in the nucleus accumbens (dexmedetomidine, 8.543 [7.135; 11.828], median [25%; 75%], vs. saline, -0.329 [-1.220; -0.047], normalized data, P = 0.001; n = 6 mice). Chemogenetic inhibition or activation of ventral tegmental area dopamine neurons increased or decreased slow waves, respectively, after intraperitoneal injection of dexmedetomidine (40 μg/kg; delta wave: two-way repeated measures ANOVA, F[2, 33] = 8.016, P = 0.002; n = 12 mice; theta wave: two-way repeated measures ANOVA, F[2, 33] = 22.800, P < 0.0001; n = 12 mice). Dexmedetomidine activates dopamine neurons in the ventral tegmental area and increases dopamine concentrations in the related forebrain projection areas. This mechanism may explain rapid arousability upon dexmedetomidine sedation.},
  note = {PubMed query source: Ying Wu}
}

@article{Jin202031940515,
  title = {Developing a Novel Tactile P300 Brain-Computer Interface With a Cheeks-Stim Paradigm.},
  author = {Jin, J and Chen, Z and Xu, R and Miao, Y and Wang, X and Jung, TP},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2020},
  doi = {10.1109/TBME.2020.2965178},
  pmid = {31940515},
  url = {https://pubmed.ncbi.nlm.nih.gov/31940515/},
  abstract = {Tactile brain-computer interface (BCI) systems can provide new communication and control options for patients with impairments of eye movements or vision. One of the most common modalities used in these BCIs is the P300 potential. Until now, tactile P300 BCIs have been successfully constructed by situating tactile stimuli at various parts of the human body. This article proposed a novel tactile P300 BCI paradigm for further expanding the tactile stimulation methods. In our proposed paradigm, the spatial target vibrotactile stimuli were delivered to subject's left and right cheeks. To validate the feasibility of our proposed paradigm, a traditional tactile P300 BCI paradigm employing spatial target vibrotactile stimuli to subject's left and right wrists was used for comparison. The experimental results of nine healthy subjects demonstrated that the proposed paradigm could obtain significantly higher classification accuracy and information transfer rate than the traditional paradigm (both for p < 0.05). Furthermore, the subjective feedback showed that our proposed paradigm was more favored by the subjects compared to the traditional paradigm, and most subjects reported that the new paradigm helped them easily distinguish between targets and non-targets. The proposed tactile P300 BCI paradigm is feasible, and can bring about superior performance and use-evaluation. The new paradigm might lead to many promising applications of such BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{LewStarowicz202031813820,
  title = {Compulsive Sexual Behavior and Dysregulation of Emotion.},
  author = {Lew-Starowicz, M and Lewczuk, K and Nowakowska, I and Kraus, S and Gola, M},
  journal = {Sexual medicine reviews},
  year = {2020},
  doi = {10.1016/j.sxmr.2019.10.003},
  pmid = {31813820},
  url = {https://pubmed.ncbi.nlm.nih.gov/31813820/},
  abstract = {Dysregulation of emotion (DE) is commonly seen in individuals suffering from compulsive sexual behavior (CSB), as well as represents a crucial element of its common comorbidities like mood, anxiety, and substance use disorders. To investigate the links between CSB and DE. A review of pertinent literature on CSB and DE was performed using EBSCO, PubMed, and Google Scholar databases. Patterns of DE were evaluated as a common clinical feature, underlying mechanisms, as well as a target for psychological and pharmacological interventions in CSB. Across different conceptualizations of CSB, DE represents the core element of a failure to cope with sexual impulses, thoughts, urges, or resulting uncontrolled sexual behaviors. DE may contribute to the occurrence of CSB while for individuals affected by this condition, sexual arousal and release act as an easier/learned (yet uncontrolled and leading to negative consequences) way of coping with negative mood states. CSB may represent a delusive form of self-regulation. Experience of child sexual abuse and insecure attachment patterns are considered risk factors for CSB (likely to be mediated by DE) but require further investigation. DE is also positively associated with CSB symptom severity. Pharmacological treatments affecting mood regulation, anxiety, impulsivity, and regulation within the brain reward system have been reported to help people with CSB achieve better control over their sexual urges and behavior. However, the available data are scarce and well-powered randomized controlled trials are needed to support these observations. Although improvement in one's emotional self-regulation is considered as an important healing factor in treatment, its benefit in psychological therapies specific to CSB requires further investigation. DE represents a core symptom of compulsive sexual behavior disorder and related comorbidities as well as a predisposing factor to the development of compulsive sexual behavior disorder. Addressing DE may facilitate better treatment outcomes for patients with CSB. Lew-Starowicz M, Lewczuk K, Nowakowska I, et al. Compulsive Sexual Behavior and Dysregulation of Emotion. J Sex Med 2020;8:191-205.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Brandmeyer202032714171,
  title = {Closed-Loop Frontal Midlineθ Neurofeedback: A Novel Approach for Training Focused-Attention Meditation.},
  author = {Brandmeyer, T and Delorme, A},
  journal = {Frontiers in human neuroscience},
  year = {2020},
  doi = {10.3389/fnhum.2020.00246},
  pmid = {32714171},
  url = {https://pubmed.ncbi.nlm.nih.gov/32714171/},
  abstract = {Cortical oscillations serve as an index of both sensory and cognitive processes and represent one of the most promising candidates for training and targeting the top-down mechanisms underlying executive functions. Research findings suggest that theta (θ) oscillations (3-7 Hz) recorded over frontal-midline electrodes are broadly associated with a number of higher-order cognitive processes and may serve as the mechanistic backbone for cognitive control. Frontal-midline theta (FMθ) oscillations have also been shown to inversely correlate with activity in the default mode network (DMN), a network in the brain linked to spontaneous thought processes such as mind-wandering and rumination. In line with these findings, we previously observed increased FMθ oscillations in expert meditation practitioners during reported periods of focused-attention meditation practice when compared to periods of mind-wandering. In an effort to narrow the explanatory gap by directly connecting observed neurophysiological activity in the brain to the phenomenological nature of reported experience, we designed a methodologically novel and adaptive neurofeedback protocol with the aim of modulating FMθ while having meditation novice participants implement breath-focus strategies derived from focused-attention mediation practices. Participants who received eight sessions of the adaptive FMθ-meditation neurofeedback protocol were able to significantly modulate FMθ over frontal electrodes using focused-attention meditation strategies relative to their baseline by the end of the training and demonstrated significantly faster reaction times on correct trials during the n-back working memory task assessed before and after the FMθ-meditation neurofeedback protocol. No significant differences in frontal theta activity or behavior were observed in the active control participants who received age and gender matched sham neurofeedback. These findings help lay the groundwork for the development of brain training protocols and neurofeedback applications that aim to train features of the mental states and traits associated with focused-attention meditation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Miao202033414824,
  title = {BCI-Based Rehabilitation on the Stroke in Sequela Stage.},
  author = {Miao, Y and Chen, S and Zhang, X and Jin, J and Xu, R and Daly, I and Jia, J and Wang, X and Cichocki, A and Jung, TP},
  journal = {Neural plasticity},
  year = {2020},
  doi = {10.1155/2020/8882764},
  pmid = {33414824},
  url = {https://pubmed.ncbi.nlm.nih.gov/33414824/},
  abstract = {Stroke is the leading cause of serious and long-term disability worldwide. Survivors may recover some motor functions after rehabilitation therapy. However, many stroke patients missed the best time period for recovery and entered into the sequela stage of chronic stroke. Studies have shown that motor imagery- (MI-) based brain-computer interface (BCI) has a positive effect on poststroke rehabilitation. This study used both virtual limbs and functional electrical stimulation (FES) as feedback to provide patients with a closed-loop sensorimotor integration for motor rehabilitation. An MI-based BCI system acquired, analyzed, and classified motor attempts from electroencephalogram (EEG) signals. The FES system would be activated if the BCI detected that the user was imagining wrist dorsiflexion on the instructed side of the body. Sixteen stroke patients in the sequela stage were randomly assigned to a BCI group and a control group. All of them participated in rehabilitation training for four weeks and were assessed by the Fugl-Meyer Assessment (FMA) of motor function. The average improvement score of the BCI group was 3.5, which was higher than that of the control group (0.9). The active EEG patterns of the four patients in the BCI group whose FMA scores increased gradually became centralized and shifted to sensorimotor areas and premotor areas throughout the study. Study results showed evidence that patients in the BCI group achieved larger functional improvements than those in the control group and that the BCI-FES system is effective in restoring motor function to upper extremities in stroke patients. This study provides a more autonomous approach than traditional treatments used in stroke rehabilitation.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Komarov202032070988,
  title = {Associations Among Emotional State, Sleep Quality, and Resting-State EEG Spectra: A Longitudinal Study in Graduate Students.},
  author = {Komarov, O and Ko, LW and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2020},
  doi = {10.1109/TNSRE.2020.2972812},
  pmid = {32070988},
  url = {https://pubmed.ncbi.nlm.nih.gov/32070988/},
  abstract = {University students are routinely influenced by a variety of natural stressors and experience irregular sleep-wake cycles caused by the necessity to trade sleep for studying while dealing with academic assignments. Often these factors result in long-term issues with daytime sleepiness, emotional instability, and mental exhaustion, which may lead to difficulties in the educational process. This study introduces the Daily Sampling System (DSS) implemented as a smartphone application, which combines a set of self-assessment scales for evaluating variations in the emotional state and sleep quality throughout a full academic term. In addition to submitting the daily sampling scores, the participants regularly filled in the Depression, Anxiety, and Stress Scales (DASS) reports and took part in resting-state EEG data recording immediately after report completion. In total, this study collected 1835 daily samples and 94 combined DASS with EEG datasets from 18 university students (aged 23-27 years), with 79.3± 15.3% response ratio in submitting the daily reports during an academic semester. The results of pairwise testing and multiple regression analysis demonstrate that the daily level of self-perceived fatigue correlates positively with stress, daytime sleepiness, and negatively with alertness on awakening, self-evaluated sleep quality, and sleep duration. The spectral analysis of the EEG data reveals a significant increase in the resting-state spectral power density across the theta and low-alpha frequency bands associated with increased levels of anxiety and stress. Additionally, the state of depression was accompanied by an intensification of high-frequency EEG activity over the temporal regions. No significant differences in prefrontal alpha power asymmetry were observed under the described experimental conditions while comparing the states of calmness and emotional arousal of the participants for the three conditions of depression, anxiety, and stress.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Sklenarik202032325387,
  title = {Approach bias for erotic stimuli among heterosexual female college students who use pornography.},
  author = {Sklenarik, S and Potenza, MN and Gola, M and Astur, RS},
  journal = {Addictive behaviors},
  year = {2020},
  doi = {10.1016/j.addbeh.2020.106438},
  pmid = {32325387},
  url = {https://pubmed.ncbi.nlm.nih.gov/32325387/},
  abstract = {Repeated engagement in addictive behaviors may lead to relatively automatic action tendencies whereby individuals approach rather than avoid addictive stimuli. This study assessed whether an approach bias for erotic stimuli exists among heterosexual college-aged females who report using pornography. We tested 121 female undergraduates using an approach-avoidance task (AAT) employing both erotic and neutral stimuli, during which participants were instructed to push or pull a gaming joystick in response to image orientation. To simulate approach and avoidance movements, pulling the joystick enlarged the image and pushing shrunk the image. Severity of pornography use was assessed using the Brief Pornography Screener (BPS) and the Problematic Pornography Use Scale (PPUS). Participants demonstrated a significant approach bias of 24.81 ms for erotic stimuli as compared to neutral stimuli, and this approach bias significantly positively correlated with PPUS scores. Moreover, approach bias scores were significantly positively correlated with anhedonia (as assessed by the Snaith-Hamilton Pleasure Scale), indicating that the stronger the degree of approach for erotic stimuli, the more anhedonia that was observed. Anhedonia was not significantly associated with pornography use severity, however. Findings implicate both similarities and differences in problematic pornography use among female and male users. A limitation of the current study is that it assessed approach biases among only heterosexual females due to the erotic stimuli employed during the AAT. Future studies should examine approach biases among females of varying sexual orientations.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Kaminska202032166625,
  title = {Ambiguous at the second sight: Mixed facial expressions trigger late electrophysiological responses linked to lower social impressions.},
  author = {Kaminska, OK and Magnuski, M and Olszanowski, M and Gola, M and Brzezicka, A and Winkielman, P},
  journal = {Cognitive, affective & behavioral neuroscience},
  year = {2020},
  doi = {10.3758/s13415-020-00778-5},
  pmid = {32166625},
  url = {https://pubmed.ncbi.nlm.nih.gov/32166625/},
  abstract = {Social interactions require quick perception, interpretation, and categorization of faces, with facial features offering cues to emotions, intentions, and traits. Importantly, reactions to faces depend not only on their features but also on their processing fluency, with disfluent faces suffering social devaluation. The current research used electrophysiological (EEG) and behavioral measures to explore at what processing stage and under what conditions emotional ambiguity is detected in the brain and how it influences trustworthiness judgments. Participants viewed male and female faces ranging from pure anger, through mixed expressions, to pure happiness. They categorized each face along the experimental dimension (happy vs. angry) or a control dimension (gender). In the emotion-categorization condition, mixed (ambiguous) expressions were classified relatively slower, and their trustworthiness was rated relatively lower. EEG analyses revealed that early brain responses are independent of the categorization condition, with pure faces evoking larger P1/N1 responses than mixed expressions. Some late (728- 880 ms) brain responses from central-parietal sites also were independent of the categorization condition and presumably reflect familiarity of the emotion categories, with pure expressions evoking larger central-parietal LPP amplitude than mixed expressions. Interestingly, other late responses were sensitive to both expressive features and categorization task, with ambiguous faces evoking a larger LPP amplitude in frontal-medial sites around 560-660 ms but only in the emotion categorization task. Critically, these late responses from the frontal-medial cluster correlated with the reduction in trustworthiness judgments. Overall, the results suggest that ambiguity detection involves late, top-down processes and that it influences important social impressions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Delorme202033166828,
  title = {Accuracy and neural correlates of blinded mediumship compared to controls on an image classification task.},
  author = {Delorme, A and Cannard, C and Radin, D and Wahbeh, H},
  journal = {Brain and cognition},
  year = {2020},
  doi = {10.1016/j.bandc.2020.105638},
  pmid = {33166828},
  url = {https://pubmed.ncbi.nlm.nih.gov/33166828/},
  abstract = {In this study, a classification task asked participants to look at 180 facial photographs of deceased individuals (photographs were taken years prior to their deaths) and guess the cause of death from three equiprobable categories: heart attack; death by firearm; or car accident. Electroencephalogram (EEG) and electrocardiogram (ECG) data were simultaneously collected during the task. The participants included individuals who claimed "mediumistic" (psychic) abilities and controls who claimed no mediumistic ability. Pooled data showed accurate guesses for the cause of death (partial η 2  = 0.12; p = 0.004), and control subjects were primarily responsible for this effect (partial η 2  = 0.11; p = 0.005). EEG and ECG differences were found between the mediums and controls. Control participants had larger amplitude event-related potentials (ERP) following the presentation of the images than the mediums, between 80 and 110 ms, and between 200 and 350 ms. This could be interpreted as reflecting greater attention and less response inhibition by controls as compared to the mediums. Participants in the control group also had lower average heart rates than the mediums, possibly indicating less stress during the task. Speculations and limits regarding why controls performed better than mediums are discussed.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Holas202033216012,
  title = {A pilot study of mindfulness-based relapse prevention for compulsive sexual behaviour disorder.},
  author = {Holas, P and Draps, M and Kowalewska, E and Lewczuk, K and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2020},
  doi = {10.1556/2006.2020.00075},
  pmid = {33216012},
  url = {https://pubmed.ncbi.nlm.nih.gov/33216012/},
  abstract = {Compulsive sexual behaviour disorder (CSBD) is a medical condition that can impair social and occupational functioning and lead to severe distress. To date, treatment effectiveness studies of CSBD are under-developed; typically, treatment for CSBD is based on guidelines for substance or other behavioural addictions. Mindfulness-based relapse prevention (MBRP) is an evidence-based treatment for substance addiction aimed at, among other things, reducing craving and negative affect-i.e. processes that are implicated in the maintenance of problematic sexual behaviours. However, to our knowledge no prior research has been published evaluating mindfulness-based intervention (MBI) in the treatment of CSBD, except two clinical case reports. Therefore, the aim of the current pilot study was to examine whether MBRP can lead to clinical improvement in CSBD. Methods: Participants were 13 adult males with a diagnosis of CSBD. Before and after the eight-week MBRP intervention, participants completed a booklet of questionnaires including measurements of porn viewing, masturbation and emotional distress. Results: As expected, we found that after MBRP participants spent significantly less time engaging in problematic pornography use and exhibited a decrease in anxiety, depression and obsessive-compulsive (OC) symptoms. Discussion and Conclusions: The findings indicate that MBRP could be beneficial for CSBD individuals. Further clinical effectiveness studies with bigger sample sizes, delayed post-training measurements and randomised control trial design are warranted. In conclusion, MBRP leads to a decrease in time spent watching porn and a decrease in emotional distress in CSBD patients.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Yue202033018658,
  title = {A brain-computer interface based on high-frequency steady-state asymmetric visual evoked potentials.},
  author = {Yue, L and Xiao, X and Xu, M and Chen, L and Wang, Y and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9176855},
  pmid = {33018658},
  url = {https://pubmed.ncbi.nlm.nih.gov/33018658/},
  abstract = {Steady State Visual Evoked Potentials (SSVEPs) have been widely used in Brain-Computer Interfaces (BCIs). SSVEP-BCIs have advantages of high classification accuracy, high information transfer rate, and strong anti-interference ability. Traditional studies mostly used low/medium frequency SSVEPs as system control signals. However, visual flickers with low/medium frequencies are uncomfortable, and even cause visual fatigue and epilepsy seizure. High-frequency SSVEP is a promising approach to solve these problems, but its miniature amplitude and low signal-to-noise ratio (SNR) would pose great challenges for target recognition. This study developed an innovative BCI paradigm to enhance the SNR of high-frequency SSVEP, which is named Steady-State asymmetrically Visual Evoked Potential (SSaVEP). Ten characters were encoded by ten couples of asymmetric flickers whose durations only lasted one second and frequencies ranged from 31 to 40 Hz with a step of 1 Hz. Discriminative canonical pattern matching (DCPM) was used to decode the high-frequency SSaVEP signals. Four subjects participated in the offline experiment. As a result, the accuracy achieved an average of 87.5% with a peak of 97.1%. The simulated online information transfer rate reached 87.2 bits/min on average and 111.2 bits/min for maximum. The results of this study demonstrate the high-frequency SSaVEP paradigm is a promising approach to alleviate the discomfort caused by visual stimuli and thereby can broaden the applications of BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Han202033019050,
  title = {'Write' but not 'spell' Chinese characters with a BCI-controlled robot.},
  author = {Han, J and Xu, M and Wang, Y and Tang, J and Liu, M and An, X and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2020},
  doi = {10.1109/EMBC44109.2020.9175275},
  pmid = {33019050},
  url = {https://pubmed.ncbi.nlm.nih.gov/33019050/},
  abstract = {Visual brain-computer interface (BCI) systems have made tremendous process in recent years. It has been demonstrated to perform well in spelling words. However, different from spelling English words in one-dimension sequences, Chinese characters are often written in a two-dimensional structure. Previous studies had never investigated how to use BCI to 'write' but not 'spell' Chinese characters. This study developed an innovative BCI-controlled robot for writing Chinese characters. The BCI system contained 108 commands displayed in a 9*12 array. A pixel-based writing method was proposed to map the starting point and ending point of each stroke of Chinese characters to the array. Connecting the starting and ending points for each stroke can make up any Chinese character. The large command set was encoded by the hybrid P300 and SSVEP features efficiently, in which each output needed only 1s of EEG data. The task-related component analysis was used to decode the combined features. Five subjects participated in this study and achieved an average accuracy of 87.23% and a maximal accuracy of 100%. The corresponding information transfer rate was 56.85 bits/min and 71.10 bits/min, respectively. The BCI-controlled robotic arm could write a Chinese character '' with 16 strokes within 5.7 seconds for the best subject. The demo video can be found at https://www.youtube.com/watch?v=A1w-e2dBGl0. The study results demonstrated that the proposed BCI-controlled robot is efficient for writing ideogram (e.g. Chinese characters) and phonogram (e.g. English letter), leading to broad prospects for real-world applications of BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Kowalewska201931204265,
  title = {Which Dimensions of Human Sexuality Are Related to Compulsive Sexual Behavior Disorder (CSBD)? Study Using a Multidimensional Sexuality Questionnaire on a Sample of Polish Males.},
  author = {Kowalewska, E and Kraus, SW and Lew-Starowicz, M and Gustavsson, K and Gola, M},
  journal = {The journal of sexual medicine},
  year = {2019},
  doi = {10.1016/j.jsxm.2019.05.006},
  pmid = {31204265},
  url = {https://pubmed.ncbi.nlm.nih.gov/31204265/},
  abstract = {Human sexuality is a multidimensional phenomenon related to several factors, such as self-esteem, awareness of sexual needs, and ability to communicate them to others. To examine the sexual characteristics of patients seeking treatment for compulsive sexual behavior disorder (CSBD)-a clinical diagnosis recently included in the 11th edition of the International Classification of Diseases classification. We have investigated the sexual characteristics of 72 Polish men seeking treatment for CSBD compared with 208 men from the Polish general population. The Multidimensional Sexual Questionnaire-PL was used to examine 12 sexual aspects of human sexuality. The severity of CSBD symptoms was assessed using Sexual Addiction Screening Test-PL, and the severity of problematic pornography use was measured by Brief Pornography Screener. Results show that CSBD patients (when compared with the general population) exhibit higher sexual anxiety, sexual depression, external sexual control, and fear of sexual relationship. Furthermore, CSBD severity is negatively related to sexual esteem, internal sexual control, sexual consciousness, sexual assertiveness, and sexual satisfaction. Our findings suggest that the impairment of the abovementioned dimensions warrant attention during clinical work and future studies on CSBD. This study was limited to men, most of whom self-identified as heterosexual. Future research should include women and non-heterosexual identified individuals. Sexual esteem, consciousness, assertiveness, satisfaction and internal sexual control are commonly affected among CSBD individuals and should be properly addressed during the clinical interview and treatment intervention. Kowalewska E, Kraus SW, Lew-Starowicz M, et al. Which Dimensions of Human Sexuality Are Related to Compulsive Sexual Behavior Disorder (CSBD)? Study Using a Multidimensional Sexuality Questionnaire on a Sample of Polish Males. J Sex Med 2019;16:1264-1273.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Delorme201930654311,
  title = {When the meditating mind wanders.},
  author = {Delorme, A and Brandmeyer, T},
  journal = {Current opinion in psychology},
  year = {2019},
  doi = {10.1016/j.copsyc.2018.12.006},
  pmid = {30654311},
  url = {https://pubmed.ncbi.nlm.nih.gov/30654311/},
  abstract = {The capacity for thought and the ability to assemble and manipulate concepts are cognitive features unique to humans. Spontaneous thoughts often occur when we are engaged in attention-demanding tasks, with an increased frequency predicting negative affect. Meditation does not require thinking; however, thinking occurs naturally during meditation. We develop the hypothesis that chronic thinking associated with strong emotional arousal during meditation practice might be detrimental to meditation practice and well-being. One goal of meditation is to identify the arousal of emotions and thoughts, and remain equanimous with them. Over time, meditation may help dampen the attention-grabbing power of these thoughts both during practice and in daily life, which may consequently help deepen meditation practice. However, when meditators fail to remain equanimous, the effects of these thoughts may be deleterious. We discuss how this hypothesis may help guide future research on meditation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wagner201931181332,
  title = {Trial-by-trial source-resolved EEG responses to gait task challenges predict subsequent step adaptation.},
  author = {Wagner, J and Martínez-Cancino, R and Makeig, S},
  journal = {NeuroImage},
  year = {2019},
  doi = {10.1016/j.neuroimage.2019.06.018},
  pmid = {31181332},
  url = {https://pubmed.ncbi.nlm.nih.gov/31181332/},
  abstract = {A growing body of evidence indicates a pivotal role of cognition and in particular executive function in gait control and fall prevention. In a recent gait study using electroencephalographic (EEG) imaging, we provided direct proof for cortical top-down inhibitory control in step adaptation. A crucial part of motor inhibition is recognizing stimuli that signal the need to inhibit or adjust motor actions such as steps during walking. One of the EEG signatures of performance monitoring in response to events signaling the need to adjust motor responses, are error-related potential (error-ERP) features. To examine whether error-ERP features may index executive control during gait adaptation, we analyzed high-density (108-channel) EEG data from an auditory gait pacing study. Participants (N = 18) walking on a steadily moving treadmill were asked to step in time to an auditory cue tone sequence, and then to quickly adapt their step length and rate, to regain step-cue synchrony following occasional unexpected shifts in the pacing cue train to a faster or slower cue tempo. Decomposition of the continuous EEG data by independent component analysis revealed a negative deflection in the source-resolved event-related potential (ERP) time locked to 'late' cue tones marking a shift to a slower cue tempo. This vertex-negative ERP feature, localized primarily to posterior medial frontal cortex (pMFC) and peaking 250 ms after the onset of the tempo-shift cue, we here refer to as the step-cue delay negativity (SDN). SDN source, timing, and polarity resemble other error-related ERP features, e.g., the Error-Related Negativity (ERN) and Feedback-Related Negativity (FRN) in (seated) button press response tasks. In single trials, SDN amplitude varied with the magnitude of the cue latency deviation (the time interval between the expected and actual cue onsets). Regression analysis also identified linear coupling between SDN amplitude and the subsequent speed of gait tempo adaptation (as measured by the increase in length of the ensuing adaptation step). The SDN in this paradigm thus seems both to index the perceived need for and the subsequent magnitude of the immediate gait adjustment, consistent with performance-monitoring models. Future research might investigate relationships of these control processes to the impairment of gait adjustment in motor disorders and cognitive decline, for example to develop a biomarker for fall risk prediction in early-stage Parkinson's.},
  note = {PubMed query source: Scott Makeig}
}

@article{Brandmeyer201930732832,
  title = {The neuroscience of meditation: classification, phenomenology, correlates, and mechanisms.},
  author = {Brandmeyer, T and Delorme, A and Wahbeh, H},
  journal = {Progress in brain research},
  year = {2019},
  doi = {10.1016/bs.pbr.2018.10.020},
  pmid = {30732832},
  url = {https://pubmed.ncbi.nlm.nih.gov/30732832/},
  abstract = {Rising from its contemplative and spiritual traditions, the science of meditation has seen huge growth over the last 30 years. This chapter reviews the classifications, phenomenology, neural correlates, and mechanisms of meditation. Meditation classification types are still varied and largely subjective. Broader models to describe meditation practice along multidimensional parameters may improve classification in the future. Phenomenological studies are few but growing, highlighting the subjective experience and correlations to neurophysiology. Oscillatory EEG studies are not conclusive likely due to the heterogeneous nature of the meditation styles and practitioners being assessed. Neuroimaging studies find common patterns during meditation and in long-term meditators reflecting the basic similarities of meditation in general; however, mostly the patterns differ across unique meditation traditions. Research on the mechanisms of meditation, specifically attention and emotion regulation is also discussed. There is a growing body of evidence demonstrating positive benefits from meditation in some clinical populations especially for stress reduction, anxiety, depression, and pain improvement, although future research would benefit by addressing the remaining methodological and conceptual issues. Meditation research continues to grow allowing us to understand greater nuances of how meditation works and its effects.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{PionTonachini201931294058,
  title = {The ICLabel dataset of electroencephalographic (EEG) independent component (IC) features.},
  author = {Pion-Tonachini, L and Kreutz-Delgado, K and Makeig, S},
  journal = {Data in brief},
  year = {2019},
  doi = {10.1016/j.dib.2019.104101},
  pmid = {31294058},
  url = {https://pubmed.ncbi.nlm.nih.gov/31294058/},
  abstract = {The ICLabel dataset is comprised of training and test sets of a set of spatiotemporal features of electroencephalographic (EEG) independent components (IC). The  ICLabel training set  feature sets were computed for over 200,000 EEG ICs from more than 6,000 existing EEG recordings. More than 8,000 of these ICs have accompanying crowdsourced IC labels across seven IC categories:  Brain, Muscle, Eye, Heart, Line Nosie, Channel Noise,  and  Other . The feature-sets included in the ICLabel dataset are scalp topography images, channel-based scalp topography measures, power spectral densities (PSD) measures (median, variance and kurtosis) and autocorrelation functions, equivalent current dipole (ECD) model fits for single and bilaterally symmetric dipole models, plus features used in several published IC classifier approaches. The  ICLabel test set  is comprised of 130 ICs from 10 datasets not included in the training set. Each of the test set ICs has an associated IC label estimated based on labels provided by six ICA-EEG experts. Files necessary for adding to and amending the dataset are also included, plus a python class containing useful methods for interacting with the dataset, and IC classifications produced by several existing IC classifiers. These data are linked to the article, "ICLabel: An automated electroencephalographic independent component classifier, dataset, and website" [1]. An active tutorial and crowdsourcing website is available: i clabel.ucsd.edu/tutorial/overview.},
  note = {PubMed query source: Scott Makeig}
}

@article{Efrati201931080103,
  title = {The Effect of Early Life Trauma on Compulsive Sexual Behavior among Members of a 12-Step Group.},
  author = {Efrati, Y and Gola, M},
  journal = {The journal of sexual medicine},
  year = {2019},
  doi = {10.1016/j.jsxm.2019.03.272},
  pmid = {31080103},
  url = {https://pubmed.ncbi.nlm.nih.gov/31080103/},
  abstract = {Early life trauma is at the core of many psychopathologies, including compulsive sexual behavior (CSB). The intermediate processes linking early life trauma and CSB have been less well studied. To investigate whether impulsiveness, internalizing symptoms, sensation-seeking, and self-criticism mediate the links between early life trauma and CSB. The sample comprised 65 Sexaholics Anonymous members and 47 healthy volunteers who completed self-report measures assessing CSB, early life trauma, and the mediating variables. The main outcome measures were severity of CSB symptoms, impulsiveness, internalizing symptoms, sensation-seeking, self-criticism, and early life trauma. The analysis indicated that the total effect of early life trauma on CSB was significant, with more prevalent and severe trauma relating to higher CSB. The analysis also revealed that this effect was significantly mediated by 3 mediation paths-greater sensation-seeking, internalizing symptoms, and self-criticism-and that these measures in turn were associated with higher CSB. Our findings provide an opportunity for researchers to gain a better insight into the effect of early life trauma on CSB. Efrati Y, Gola M. The Effect of Early Life Trauma on Compulsive Sexual Behavior among Members of a 12-Step Group. J Sex Med 2019;16:803-811.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Burwell201931081153,
  title = {Reduced premovement positivity during the stimulus-response interval precedes errors: Using single-trial and regression ERPs to understand performance deficits in ADHD.},
  author = {Burwell, SJ and Makeig, S and Iacono, WG and Malone, SM},
  journal = {Psychophysiology},
  year = {2019},
  doi = {10.1111/psyp.13392},
  pmid = {31081153},
  url = {https://pubmed.ncbi.nlm.nih.gov/31081153/},
  abstract = {Brain mechanisms linked to incorrect response selections made under time pressure during cognitive task performance are poorly understood, particularly in adolescents with attention-deficit hyperactivity disorder (ADHD). Using subject-specific multimodal imaging (electroencephalogram, magnetic resonance imaging, behavior) during flanker task performance by a sample of 94 human adolescents (mean age = 15.5 years, 50% female) with varying degrees of ADHD symptomatology, we examined the degree to which amplitude features of source-resolved event-related potentials (ERPs) from brain-independent component processes within a critical (but often ignored) period in the action selection process, the stimulus-response interval, were associated with motor response errors (across trials) and error rates (across individuals). Response errors were typically preceded by two smaller peaks in both trial-level and trial-averaged ERP projections from posterior medial frontal cortex (pMFC): a frontocentral P3 peaking about 390 ms after stimulus onset, and a premovement positivity (PMP) peaking about 110 ms before the motor response. Separating overlapping stimulus-locked and response-locked ERP contributions using a "regression ERP" approach showed that trial errors and participant error rates were primarily associated with smaller PMP, and not with frontocentral P3. Moreover, smaller PMP mediated the association between larger numbers of errors and ADHD symptoms, suggesting the possible value of using PMP as an intervention target to remediate performance deficits in ADHD.},
  note = {PubMed query source: Scott Makeig}
}

@article{Loo201931382238,
  title = {Neural activation and connectivity during cued eye blinks in Chronic Tic Disorders.},
  author = {Loo, SK and Miyakoshi, M and Tung, K and Lloyd, E and Salgari, G and Dillon, A and Chang, S and Piacentini, J and Makeig, S},
  journal = {NeuroImage. Clinical},
  year = {2019},
  doi = {10.1016/j.nicl.2019.101956},
  pmid = {31382238},
  url = {https://pubmed.ncbi.nlm.nih.gov/31382238/},
  abstract = {The pathophysiology of Chronic Tic Disorders (CTDs), including Tourette Syndrome, remains poorly understood. The goal of this study was to compare neural activity and connectivity during a voluntary movement (VM) paradigm that involved cued eye blinks among children with and without CTDs. Using the precise temporal resolution of electroencephalography (EEG), we used the timing and location of cortical source resolved spectral power activation and connectivity to map component processes such as visual attention, cue detection, blink regulation and response monitoring. We hypothesized that neural activation and connectivity during the cued eye blink paradigm would be significantly different in regions typically associated with effortful control of eye blinks, such as frontal, premotor, parietal, and occipital cortices between children with and without CTD. Participants were 40 children (23 with CTD, 17 age-matched Healthy Control [HC]), between the ages of 8-12 (mean age = 9.5) years old. All participants underwent phenotypic assessment including diagnostic interviews, behavior rating scales and 128-channel EEG recording. Upon presentation of a cue every 3 s, children were instructed to make an exaggerated blink. Behaviorally, the groups did not differ in blink number, latency, or ERP amplitude. Within source resolved clusters located in left dorsolateral prefrontal cortex, posterior cingulate, and supplemental motor area, children with CTD exhibited higher gamma band spectral power relative to controls. In addition, significant diagnostic group differences in theta, alpha, and beta band power in inferior parietal cortex emerged. Spectral power differences were significantly associated with clinical characteristics such as tic severity and premonitory urge strength. After calculating dipole density for 76 anatomical regions, the CTD and HC groups had 70% overlap of top regions with the highest dipole density, suggesting that similar cortical networks were used across groups to carry out the VM. The CTD group exhibited significant information flow increase and dysregulation relative to the HC group, particularly from occipital to frontal regions. Children with CTD exhibit abnormally high levels of neural activation and dysregulated connectivity among networks used for regulation and effortful control of voluntary eye blinks.},
  note = {PubMed query source: Scott Makeig}
}

@article{Shirazi201931787866,
  title = {More Reliable EEG Electrode Digitizing Methods Can Reduce Source Estimation Uncertainty, but Current Methods Already Accurately Identify Brodmann Areas.},
  author = {Shirazi, SY and Huang, HJ},
  journal = {Frontiers in neuroscience},
  year = {2019},
  doi = {10.3389/fnins.2019.01159},
  pmid = {31787866},
  url = {https://pubmed.ncbi.nlm.nih.gov/31787866/},
  abstract = {Electroencephalography (EEG) and source estimation can be used to identify brain areas activated during a task, which could offer greater insight on cortical dynamics. Source estimation requires knowledge of the locations of the EEG electrodes. This could be provided with a template or obtained by digitizing the EEG electrode locations. Operator skill and inherent uncertainties of a digitizing system likely produce a range of digitization reliabilities, which could affect source estimation and the interpretation of the estimated source locations. Here, we compared the reliabilities of five digitizing methods (ultrasound, structured-light 3D scan, infrared 3D scan, motion capture probe, and motion capture) and determined the relationship between digitization reliability and source estimation uncertainty, assuming other contributors to source estimation uncertainty were constant. We digitized a mannequin head using each method five times and quantified the reliability and validity of each method. We created five hundred sets of electrode locations based on our reliability results and applied a dipole fitting algorithm (DIPFIT) to perform source estimation. The motion capture method, which recorded the locations of markers placed directly on the electrodes had the best reliability with an average electrode variability of 0.001 cm. Then, in order of decreasing reliability were the method using a digitizing probe in the motion capture system, an infrared 3D scanner, a structured-light 3D scanner, and an ultrasound digitization system. Unsurprisingly, uncertainty of the estimated source locations increased with greater variability of EEG electrode locations and less reliable digitizing systems. If EEG electrode location variability was ∽1 cm, a single source could shift by as much as 2 cm. To help translate these distances into practical terms, we quantified Brodmann area accuracy for each digitizing method and found that the average Brodmann area accuracy for all digitizing methods was >80%. Using a template of electrode locations reduced the Brodmann area accuracy to ∽50%. Overall, more reliable digitizing methods can reduce source estimation uncertainty, but the significance of the source estimation uncertainty depends on the desired spatial resolution. For accurate Brodmann area identification, any of the digitizing methods tested can be used confidently.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Perez201931176741,
  title = {Mismatch negativity reveals plasticity in cortical dynamics after 1-hour of auditory training exercises.},
  author = {Perez, VB and Miyakoshi, M and Makeig, SD and Light, GA},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2019},
  doi = {10.1016/j.ijpsycho.2019.06.003},
  pmid = {31176741},
  url = {https://pubmed.ncbi.nlm.nih.gov/31176741/},
  abstract = {Impaired sensory processing contributes to deficits in cognitive and psychosocial functioning in individuals with schizophrenia (SZ). Mismatch Negativity (MMN), an event-related potential (ERP) index of sensory discrimination associated with cognitive and psychosocial functioning, is a candidate biomarker of auditory discrimination and thus possibly of changes following auditory-based Targeted Cognitive Training (TCT). Here we evaluated the acute effect of TCT on cortical processes supporting auditory discrimination. MMN was assessed in 28 SZ outpatients before and after a single 1-hour (hr) session of "Sound Sweeps," a pitch discrimination task that is a component of the TCT suite of exercises. Independent component (IC) analysis was applied to decompose 64-channel scalp-recorded electroencephalogram (EEG) activity into spatiotemporally stationary sources and their activities. ICs from all patients were pooled to find commonalities in their cortical locations. IC cluster-mean ERPs were evaluated to determine the clusters contributing to the (140-200 ms) MMN difference between responses to deviant and standard tone stimuli respectively. Two frontal IC clusters centered in orbitofrontal cortex (OFC) and anterior cingulate cortex (ACC) accounted for >77% of MMN variance across all scalp channels. After 1-hr auditory training, significant suppression of ACC cluster contributions was detected, whereas the OFC cluster contribution was unchanged. Prior to TCT, the MMN response was dominated by EEG effective sources in or near OFC and ACC. However, after 1-hr of auditory-based TCT, a significant attenuation of ACC was observed, whereas OFC contribution to MMN persisted. The present findings support further trials designed to test whether training-related MMN plasticity in the ACC after 1-hr may predict individual patient response to a full course of TCT.},
  note = {PubMed query source: Scott Makeig}
}

@article{MartnezCancino201930342235,
  title = {Measuring transient phase-amplitude coupling using local mutual information.},
  author = {Martínez-Cancino, R and Heng, J and Delorme, A and Kreutz-Delgado, K and Sotero, RC and Makeig, S},
  journal = {NeuroImage},
  year = {2019},
  doi = {10.1016/j.neuroimage.2018.10.034},
  pmid = {30342235},
  url = {https://pubmed.ncbi.nlm.nih.gov/30342235/},
  abstract = {Here we demonstrate the suitability of a local mutual information measure for estimating the temporal dynamics of cross-frequency coupling (CFC) in brain electrophysiological signals. In CFC, concurrent activity streams in different frequency ranges interact and transiently couple. A particular form of CFC, phase-amplitude coupling (PAC), has raised interest given the growing amount of evidence of its possible role in healthy and pathological brain information processing. Although several methods have been proposed for PAC estimation, only a few have addressed the estimation of the temporal evolution of PAC, and these typically require a large number of experimental trials to return a reliable estimate. Here we explore the use of mutual information to estimate a PAC measure (MIPAC) in both continuous and event-related multi-trial data. To validate these two applications of the proposed method, we first apply it to a set of simulated phase-amplitude modulated signals and show that MIPAC can successfully recover the temporal dynamics of the simulated coupling in either continuous or multi-trial data. Finally, to explore the use of MIPAC to analyze data from human event-related paradigms, we apply it to an actual event-related human electrocorticographic (ECoG) data set that exhibits strong PAC, demonstrating that the MIPAC estimator can be used to successfully characterize amplitude-modulation dynamics in electrophysiological data.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wahbeh201932518623,
  title = {Measuring extraordinary experiences and beliefs: A validation and reliability study.},
  author = {Wahbeh, H and Yount, G and Vieten, C and Radin, D and Delorme, A},
  journal = {F1000Research},
  year = {2019},
  doi = {10.12688/f1000research.20409.3},
  pmid = {32518623},
  url = {https://pubmed.ncbi.nlm.nih.gov/32518623/},
  abstract = {Background:  Belief in the paranormal is widespread worldwide. Recent surveys suggest that subjective experiences of the paranormal are common. A concise instrument that adequately evaluates beliefs as distinct from experiences does not currently exist. To address this gap, we created the Noetic Experiences and Beliefs Scale (NEBS) which evaluates belief and experience as separate constructs.  Methods:  The NEBS is a 20-item survey with 10 belief and 10 experience items rated on a visual analog scale from 0-100. In an observational study, the survey was administered to 361 general population adults in the United States and a subsample of 96 one month later. Validity, reliability and internal consistency were evaluated. A confirmatory factor analysis was conducted to confirm the latent variables of belief and experience. The survey was then administered to a sample of 646 IONS Discovery Lab participants to evaluate divergent validity and confirm belief and experience as latent variables of the model in a different population.  Results:  The NEBS demonstrated convergent validity, reliability and internal consistency (Cronbach's alpha Belief 0.90; Experience 0.93) and test-retest reliability (Belief:  r =  0.83  ;  Experience:  r =  0.77). A confirmatory factor analysis model with belief and experience as latent variables demonstrated a good fit. The factor model was confirmed as having a good fit and divergent validity was established in the sample of 646 IONS Discovery Lab participants.  Conclusions:  The NEBS is a short, valid, and reliable instrument for evaluating paranormal belief and experience.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wu201931491423,
  title = {Meaning enhances discrimination of merged phonemes: A mismatch negativity study.},
  author = {Wu, Y and Guo, X and Gao, Y and Wang, Z and Wang, X},
  journal = {Brain research},
  year = {2019},
  doi = {10.1016/j.brainres.2019.146433},
  pmid = {31491423},
  url = {https://pubmed.ncbi.nlm.nih.gov/31491423/},
  abstract = {The phonemic merger phenomena is characterized by the inability of distinguishing two acoustically different phonemes, such as /n/ and /l/. Previous studies suggested that the process that drives the phonemic merger is the lack of separated memory traces of phonemes. However, it is still unknown whether higher-level linguistic functions have an influence on the perception of merged phonemes. We designed a mismatch negativity (MMN) study to explore the influence of semantic information in the perception of the phonemic merger. The results showed that no robust MMN was elicited in an oddball stream of the syllables /niu2/ and /liu2/ in the group of merged speakers. We interpreted that the brain of the /n/-/l/ merged speakers had almost lost the ability of early auditory discrimination of the phonemes /n/ and /l/. Interestingly, the same merged speakers regained the ability of discriminating /n/ and /l/ when the oddball contrast was placed in an idiom context. All in all, our results indicate that a context with a meaning, such as an idiom, facilitates the early acoustic processing of merged phonemes. This finding also gives additional evidence that not only the bottom-up analysis of the acoustic space, but also the top-down modulation of the functional significance of sounds could contribute to the early auditory discrimination of phonemes.},
  note = {PubMed query source: Ying Wu}
}

@article{Warrington201931043758,
  title = {Maternal and fetal genetic effects on birth weight and their relevance to cardio-metabolic risk factors.},
  author = {Warrington, NM and Beaumont, RN and Horikoshi, M and Day, FR and Helgeland, Ø and Laurin, C and Bacelis, J and Peng, S and Hao, K and Feenstra, B and Wood, AR and Mahajan, A and Tyrrell, J and Robertson, NR and Rayner, NW and Qiao, Z and Moen, GH and Vaudel, M and Marsit, CJ and Chen, J and Nodzenski, M and Schnurr, TM and Zafarmand, MH and Bradfield, JP and Grarup, N and Kooijman, MN and Li-Gao, R and Geller, F and Ahluwalia, TS and Paternoster, L and Rueedi, R and Huikari, V and Hottenga, JJ and Lyytikäinen, LP and Cavadino, A and Metrustry, S and Cousminer, DL and Wu, Y and Thiering, E and Wang, CA and Have, CT and Vilor-Tejedor, N and Joshi, PK and Painter, JN and Ntalla, I and Myhre, R and Pitkänen, N and van Leeuwen, EM and Joro, R and Lagou, V and Richmond, RC and Espinosa, A and Barton, SJ and Inskip, HM and Holloway, JW and Santa-Marina, L and Estivill, X and Ang, W and Marsh, JA and Reichetzeder, C and Marullo, L and Hocher, B and Lunetta, KL and Murabito, JM and Relton, CL and Kogevinas, M and Chatzi, L and Allard, C and Bouchard, L and Hivert, MF and Zhang, G and Muglia, LJ and Heikkinen, J and EGG Consortium and Morgen, CS and van Kampen, AHC and van Schaik, BDC and Mentch, FD and Langenberg, C and Luan, J and Scott, RA and Zhao, JH and Hemani, G and Ring, SM and Bennett, AJ and Gaulton, KJ and Fernandez-Tajes, J and van Zuydam, NR and Medina-Gomez, C and de Haan, HG and Rosendaal, FR and Kutalik, Z and Marques-Vidal, P and Das, S and Willemsen, G and Mbarek, H and Müller-Nurasyid, M and Standl, M and Appel, EVR and Fonvig, CE and Trier, C and van Beijsterveldt, CEM and Murcia, M and Bustamante, M and Bonas-Guarch, S and Hougaard, DM and Mercader, JM and Linneberg, A and Schraut, KE and Lind, PA and Medland, SE and Shields, BM and Knight, BA and Chai, JF and Panoutsopoulou, K and Bartels, M and Sánchez, F and Stokholm, J and Torrents, D and Vinding, RK and Willems, SM and Atalay, M and Chawes, BL and Kovacs, P and Prokopenko, I and Tuke, MA and Yaghootkar, H and Ruth, KS and Jones, SE and Loh, PR and Murray, A and Weedon, MN and Tönjes, A and Stumvoll, M and Michaelsen, KF and Eloranta, AM and Lakka, TA and van Duijn, CM and Kiess, W and Körner, A and Niinikoski, H and Pahkala, K and Raitakari, OT and Jacobsson, B and Zeggini, E and Dedoussis, GV and Teo, YY and Saw, SM and Montgomery, GW and Campbell, H and Wilson, JF and Vrijkotte, TGM and Vrijheid, M and de Geus, EJCN and Hayes, MG and Kadarmideen, HN and Holm, JC and Beilin, LJ and Pennell, CE and Heinrich, J and Adair, LS and Borja, JB and Mohlke, KL and Eriksson, JG and Widén, EE and Hattersley, AT and Spector, TD and Kähönen, M and Viikari, JS and Lehtimäki, T and Boomsma, DI and Sebert, S and Vollenweider, P and Sørensen, TIA and Bisgaard, H and Bønnelykke, K and Murray, JC and Melbye, M and Nohr, EA and Mook-Kanamori, DO and Rivadeneira, F and Hofman, A and Felix, JF and Jaddoe, VWV and Hansen, T and Pisinger, C and Vaag, AA and Pedersen, O and Uitterlinden, AG and Järvelin, MR and Power, C and Hyppönen, E and Scholtens, DM and Lowe, WL and Davey Smith, G and Timpson, NJ and Morris, AP and Wareham, NJ and Hakonarson, H and Grant, SFA and Frayling, TM and Lawlor, DA and Njølstad, PR and Johansson, S and Ong, KK and McCarthy, MI and Perry, JRB and Evans, DM and Freathy, RM},
  journal = {Nature genetics},
  year = {2019},
  doi = {10.1038/s41588-019-0403-1},
  pmid = {31043758},
  url = {https://pubmed.ncbi.nlm.nih.gov/31043758/},
  abstract = {Birth weight variation is influenced by fetal and maternal genetic and non-genetic factors, and has been reproducibly associated with future cardio-metabolic health outcomes. In expanded genome-wide association analyses of own birth weight (n = 321,223) and offspring birth weight (n = 230,069 mothers), we identified 190 independent association signals (129 of which are novel). We used structural equation modeling to decompose the contributions of direct fetal and indirect maternal genetic effects, then applied Mendelian randomization to illuminate causal pathways. For example, both indirect maternal and direct fetal genetic effects drive the observational relationship between lower birth weight and higher later blood pressure: maternal blood pressure-raising alleles reduce offspring birth weight, but only direct fetal effects of these alleles, once inherited, increase later offspring blood pressure. Using maternal birth weight-lowering genotypes to proxy for an adverse intrauterine environment provided no evidence that it causally raises offspring blood pressure, indicating that the inverse birth weight-blood pressure association is attributable to genetic effects, and not to intrauterine programming.},
  note = {PubMed query source: Ying Wu}
}

@article{Grubbs201930621919,
  title = {Is Pornography Use Related to Erectile Functioning? Results From Cross-Sectional and Latent Growth Curve Analyses.},
  author = {Grubbs, JB and Gola, M},
  journal = {The journal of sexual medicine},
  year = {2019},
  doi = {10.1016/j.jsxm.2018.11.004},
  pmid = {30621919},
  url = {https://pubmed.ncbi.nlm.nih.gov/30621919/},
  abstract = {Despite evidence to the contrary, a number of advocacy and self-help groups persist in claiming that internet pornography use is driving an epidemic of erectile dysfunction (ED). The present work sought to explore whether mere pornography use itself and self-reported problematic use of pornography are related to ED, both cross-sectionally and longitudinally. A series of 3 samples of sexually active men who also used pornography were collected: a cross-sectional sample of undergraduate men in the United States (n = 147), an online sample of men derived from a larger sample that was matched to U.S. nationally representative norms (n = 297), and a 1-year, 4-wave longitudinal sample of adult men derived from an online convenience sample (Mechanical Turk: time 1, n = 433; time 2, n = 223; time 3, n = 202; time 4, n = 196). Pearson correlations and cross-sectional structural equation models were conducted in each sample. Latent growth curve analyses were conducted in the longitudinal sample. The primary outcomes of interest were cross-sectional and longitudinal reports of erectile functioning as measured by the International Index of Erectile Functioning 5. Across all 3 samples, there was evidence of a positive, cross-sectional association between self-reported problematic use and ED, but no consistent association between mere use itself and ED. In our longitudinal sample, there were correlations among baseline pornography use, baseline self-reported problematic use, and prospective ED at times 2-4; however, latent growth curve analyses demonstrated no significant relationships between any pornography-related variables and trajectories of ED. These results suggest that among non-treatment-seeking pornography users, self-reported problematic use likely is associated with concurrent reports of ED, but that the links between these variables are not directional or causal in nature. This work is the first work to systematically examine the links between self-reported problematic use of pornography and ED, and it did so in a variety of samples, using both cross-sectional and longitudinal methods. Even so, the work relied exclusively on self-report methods, and did not control for medical covariates that may be related to the experience of ED. In conjunction with prior literature, we conclude that there is little or no evidence of an association between mere pornography use and ED, consistent evidence of an association between self-reported problematic use and ED cross-sectionally, and no evidence of causal links between any pornography variables and ED. Grubbs JB, Gola M. Is Pornography Use Related to Erectile Functioning? Results From Cross-Sectional and Latent Growth Curve Analyses. J Sex Med 2019;16:111-125.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Siddharth201931705031,
  title = {Impact of Affective Multimedia Content on the Electroencephalogram and Facial Expressions.},
  author = {Siddharth, S and Jung, TP and Sejnowski, TJ},
  journal = {Scientific reports},
  year = {2019},
  doi = {10.1038/s41598-019-52891-2},
  pmid = {31705031},
  url = {https://pubmed.ncbi.nlm.nih.gov/31705031/},
  abstract = {Most of the research in the field of affective computing has focused on detecting and classifying human emotions through electroencephalogram (EEG) or facial expressions. Designing multimedia content to evoke certain emotions has been largely motivated by manual rating provided by users. Here we present insights from the correlation of affective features between three modalities namely, affective multimedia content, EEG, and facial expressions. Interestingly, low-level Audio-visual features such as contrast and homogeneity of the video and tone of the audio in the movie clips are most correlated with changes in facial expressions and EEG. We also detect the regions associated with the human face and the brain (in addition to the EEG frequency bands) that are most representative of affective responses. The computational modeling between the three modalities showed a high correlation between features from these regions and user-reported affective labels. Finally, the correlation between different layers of convolutional neural networks with EEG and Face images as input provides insights into human affection. Together, these findings will assist in (1) designing more effective multimedia contents to engage or influence the viewers, (2) understanding the brain/body bio-markers of affection, and (3) developing newer brain-computer interfaces as well as facial-expression-based algorithms to read emotional responses of the viewers.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{PionTonachini201931103785,
  title = {ICLabel: An automated electroencephalographic independent component classifier, dataset, and website.},
  author = {Pion-Tonachini, L and Kreutz-Delgado, K and Makeig, S},
  journal = {NeuroImage},
  year = {2019},
  doi = {10.1016/j.neuroimage.2019.05.026},
  pmid = {31103785},
  url = {https://pubmed.ncbi.nlm.nih.gov/31103785/},
  abstract = {The electroencephalogram (EEG) provides a non-invasive, minimally restrictive, and relatively low-cost measure of mesoscale brain dynamics with high temporal resolution. Although signals recorded in parallel by multiple, near-adjacent EEG scalp electrode channels are highly-correlated and combine signals from many different sources, biological and non-biological, independent component analysis (ICA) has been shown to isolate the various source generator processes underlying those recordings. Independent components (IC) found by ICA decomposition can be manually inspected, selected, and interpreted, but doing so requires both time and practice as ICs have no order or intrinsic interpretations and therefore require further study of their properties. Alternatively, sufficiently-accurate automated IC classifiers can be used to classify ICs into broad source categories, speeding the analysis of EEG studies with many subjects and enabling the use of ICA decomposition in near-real-time applications. While many such classifiers have been proposed recently, this work presents the ICLabel project comprised of (1) the ICLabel dataset containing spatiotemporal measures for over 200,000 ICs from more than 6000 EEG recordings and matching component labels for over 6000 of those ICs, all using common average reference, (2) the ICLabel website for collecting crowdsourced IC labels and educating EEG researchers and practitioners about IC interpretation, and (3) the automated ICLabel classifier, freely available for MATLAB. The ICLabel classifier improves upon existing methods in two ways: by improving the accuracy of the computed label estimates and by enhancing its computational efficiency. The classifier outperforms or performs comparably to the previous best publicly available automated IC component classification method for all measured IC categories while computing those labels ten times faster than that classifier as shown by a systematic comparison against other publicly available EEG IC classifiers.},
  note = {PubMed query source: Scott Makeig}
}

@article{Somon201930423428,
  title = {Human or not human? Performance monitoring ERPs during human agent and machine supervision.},
  author = {Somon, B and Campagne, A and Delorme, A and Berberian, B},
  journal = {NeuroImage},
  year = {2019},
  doi = {10.1016/j.neuroimage.2018.11.013},
  pmid = {30423428},
  url = {https://pubmed.ncbi.nlm.nih.gov/30423428/},
  abstract = {Performance monitoring is a critical process which allows us to both learn from our own errors, and also interact with other human beings. However, our increasingly automated world requires us to interact more and more with automated systems, especially in risky environments. The present EEG study aimed at investigating and comparing the neuro-functional correlates associated with performance monitoring of an automated system and a human agent using a vertically-oriented arrowhead version of the flanker task. Given the influence of task difficulty on performance monitoring, two levels of difficulty were considered in order to assess their impact on supervision activity. A large N2-P3 complex in fronto-central regions was observed for both human agent error detection and system error detection during supervision. Using a cluster-based permutation analysis, a significantly decreased P3-like component was found for system compared to human agent error detection. This variation is in line with various psychosocial behavioral studies showing a difference between human-human and human-machine interactions, even though it was not clearly anticipated. Finally, the activity observed during error detection was significantly reduced in the difficult condition compared to the easy one, for both system and human agent supervision. Overall, this study is a first step towards the characterization of the neurophysiological correlates underlying system supervision, and a better understanding of their evolution in more complex environments. To go further, these results need to be replicated in other experiments with various paradigms to assess the robustness of the pattern and decrease during system supervision.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wagner201931624252,
  title = {High-density EEG mobile brain/body imaging data recorded during a challenging auditory gait pacing task.},
  author = {Wagner, J and Martinez-Cancino, R and Delorme, A and Makeig, S and Solis-Escalante, T and Neuper, C and Mueller-Putz, G},
  journal = {Scientific data},
  year = {2019},
  doi = {10.1038/s41597-019-0223-2},
  pmid = {31624252},
  url = {https://pubmed.ncbi.nlm.nih.gov/31624252/},
  abstract = {In this report we present a mobile brain/body imaging (MoBI) dataset that allows study of source-resolved cortical dynamics supporting coordinated gait movements in a rhythmic auditory cueing paradigm. Use of an auditory pacing stimulus stream has been recommended to identify deficits and treat gait impairments in neurologic populations. Here, the rhythmic cueing paradigm required healthy young participants to walk on a treadmill (constant speed) while attempting to maintain step synchrony with an auditory pacing stream and to adapt their step length and rate to unanticipated shifts in tempo of the pacing stimuli (e.g., sudden shifts to a faster or slower tempo). High-density electroencephalography (EEG, 108 channels), surface electromyography (EMG, bilateral tibialis anterior), pressure sensors on the heel (to register timing of heel strikes), and goniometers (knee, hip, and ankle joint angles) were concurrently recorded in 20 participants. The data is provided in the Brain Imaging Data Structure (BIDS) format to promote data sharing and reuse, and allow the inclusion of the data into fully automated data analysis workflows.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Tsai201930817980,
  title = {Eye fixation-related fronto-parietal neural network correlates of memory retrieval.},
  author = {Tsai, PY and She, HC and Chen, SC and Huang, LY and Chou, WC and Duann, JR and Jung, TP},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2019},
  doi = {10.1016/j.ijpsycho.2019.02.008},
  pmid = {30817980},
  url = {https://pubmed.ncbi.nlm.nih.gov/30817980/},
  abstract = {Eye movements are considered to be informative with regard to the underlying cognitive processes of human beings. Previous studies have reported that eye movements are associated with which scientific concepts are retrieved correctly. Moreover, other studies have also suggested that eye movements involve the cooperative activity of the human brain's fronto-parietal circuits. Less research has been conducted to investigate whether fronto-parietal EEG oscillations are associated with the retrieval processing of scientific concepts. Our findings in this study demonstrated that the fronto-parietal network is indeed crucial for successful memory retrieval. In short, significantly lower theta augmentation in the frontal midline and lower alpha suppression in the right parietal region were observed at the 5th eye fixation for physics concepts that were correctly retrieved than for those that were incorrectly retrieved. Moreover, the visual cortex in the occipital lobe exhibits a significantly greater theta augmentation followed by an alpha suppression following each eye fixation, while a right fronto-parietal asymmetry was also found for the successful retrieval of presentations of physics concepts. In particular, the study results showed that eye fixation-related frontal midline theta power and right parietal alpha power at the 5th eye fixation have the greatest predictive power regarding the correctness of the retrieval of physics concepts.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Somon201930300637,
  title = {Evaluation of performance monitoring ERPs through difficulty manipulation in a response-feedback paradigm.},
  author = {Somon, B and Campagne, A and Delorme, A and Berberian, B},
  journal = {Brain research},
  year = {2019},
  doi = {10.1016/j.brainres.2018.10.007},
  pmid = {30300637},
  url = {https://pubmed.ncbi.nlm.nih.gov/30300637/},
  abstract = {Performance monitoring is an amply studied function, since it is of major importance in carrying out actions in our everyday life. No consensus has been reached on the functional role and the relationship between each event-related potential (ERP) characterizing this function. In this study, we used a modified version of the flanker task, measuring the impact of task difficulty on the amplitudes of response-locked and feedback-locked performance monitoring ERPs in a single trial. We observed a functional differentiation between fronto-central (ERN/CRN and FRN) and centro-parietal (Pe/Pc and P300) components: the former seem to be only sensitive to accuracy, whereas the latter seem to be mainly modulated by task difficulty. The use of a surface Laplacian transformation, estimating current source density, on our data also supported an effect of difficulty on centro-parietal response-locked and feedback-locked ERPs. This technique allowed the spatial resolution to be improved and provided clarity, associated with the difficulty manipulation, on the activity of response-locked and feedback-locked performance monitoring ERPs.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lu201930770443,
  title = {Emergence of analogy from relation learning.},
  author = {Lu, H and Wu, YN and Holyoak, KJ},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  year = {2019},
  doi = {10.1073/pnas.1814779116},
  pmid = {30770443},
  url = {https://pubmed.ncbi.nlm.nih.gov/30770443/},
  abstract = {By middle childhood, humans are able to learn abstract semantic relations (e.g., antonym, synonym, category membership) and use them to reason by analogy. A deep theoretical challenge is to show how such abstract relations can arise from nonrelational inputs, thereby providing key elements of a protosymbolic representation system. We have developed a computational model that exploits the potential synergy between deep learning from "big data" (to create semantic features for individual words) and supervised learning from "small data" (to create representations of semantic relations between words). Given as inputs labeled pairs of lexical representations extracted by deep learning, the model creates augmented representations by remapping features according to the rank of differences between values for the two words in each pair. These augmented representations aid in coping with the feature alignment problem (e.g., matching those features that make "love-hate" an antonym with the different features that make "rich-poor" an antonym). The model extracts weight distributions that are used to estimate the probabilities that new word pairs instantiate each relation, capturing the pattern of human typicality judgments for a broad range of abstract semantic relations. A measure of relational similarity can be derived and used to solve simple verbal analogies with human-level accuracy. Because each acquired relation has a modular representation, basic symbolic operations are enabled (notably, the converse of any learned relation can be formed without additional training). Abstract semantic relations can be induced by bootstrapping from nonrelational inputs, thereby enabling relational generalization and analogical reasoning.},
  note = {PubMed query source: Ying Wu}
}

@article{Molina201929061281,
  title = {Electroencephalographic and peripheral temperature dynamics during a prolonged psychomotor vigilance task.},
  author = {Molina, E and Sanabria, D and Jung, TP and Correa, Á},
  journal = {Accident; analysis and prevention},
  year = {2019},
  doi = {10.1016/j.aap.2017.10.014},
  pmid = {29061281},
  url = {https://pubmed.ncbi.nlm.nih.gov/29061281/},
  abstract = {Attention lapses and fatigue are a main source of impaired performance that can lead to accidents. This study analyzed electroencephalographic (EEG) dynamics and body skin temperature as markers of attentional fluctuations in non-sleep deprived subjects during a 45min Psychomotor Vigilance Task (PVT). Independent Component Analysis and time-frequency analysis were used to evaluate the EEG data. Results showed a positive association between distal and distal-to-proximal gradient (DPG) temperatures and reaction time (RT); increments in EEG power in alpha-, theta- and beta-band frequencies in parieto-occipital, central-medial and frontal components, were associated with poor performance (slower RT) in the task. This generalized power increment fits with an increased activity in the default mode network, associated with attention lapses. This study highlights the potential use of the PVT as a tool to obtain individual physiological indices of vigilance and fatigue that could be applied to other vigilance tasks typically performed in occupational settings.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu201931947204,
  title = {Effects of stimulus position on the classification of miniature asymmetric VEPs for brain-computer interfaces.},
  author = {Xu, M and Zhou, X and Xiao, X and Wang, Y and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2019},
  doi = {10.1109/EMBC.2019.8857789},
  pmid = {31947204},
  url = {https://pubmed.ncbi.nlm.nih.gov/31947204/},
  abstract = {The speed of visual brain-computer interfaces (BCIs) has been greatly improved in recent years. However, traditional visual BCI paradigm requires users to directly gaze at the intensive flickering items, which would cause severe problems in practical applications, such as visual fatigue and excessive visual resources consumption. A promising solution is to use small visual stimuli outside the central visual area to encode instructions, which had been demonstrated to be effective in our previous study. This study aims to further investigate the effects of stimulus position on the classification of miniature asymmetric visual evoked potentials (aVEPs). Small peripheral visual stimuli were designed with different eccentricities (1° and 2°) and directions (0°, 45°, 90°, 135°, 180°, -135°, -90°, and -45°) to induce different kinds of miniature aVEPs. Five subjects participated in this experiment. Discriminative canonical pattern matching (DCPM) was used to classify all possible pairs of miniature aVEPs. Study results showed that visual stimuli with less eccentricity could induce more distinct miniature aVEPs. The highest single-trial accuracy achieved was about 83% for the binary classifications of miniature aVEPs pairs corresponding to (1°, -135°) Vs (1°, 0°), (1°, -45°) Vs (1°, -135°) and (1°, -45°) Vs (1°, 180°). This finding is very important for the design and development of the miniature aVEPs-based BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Kappel201931551697,
  title = {Ear-EEG Forward Models: Improved Head-Models for Ear-EEG.},
  author = {Kappel, SL and Makeig, S and Kidmose, P},
  journal = {Frontiers in neuroscience},
  year = {2019},
  doi = {10.3389/fnins.2019.00943},
  pmid = {31551697},
  url = {https://pubmed.ncbi.nlm.nih.gov/31551697/},
  abstract = {Computational models for mapping electrical sources in the brain to potentials on the scalp have been widely explored. However, current models do not describe the external ear anatomy well, and is therefore not suitable for ear-EEG recordings. Here we present an extension to existing computational models, by incorporating an improved description of the external ear anatomy based on 3D scanned impressions of the ears. The result is a method to compute an ear-EEG forward model, which enables mapping of sources in the brain to potentials in the ear. To validate the method, individualized ear-EEG forward models were computed for four subjects, and ear-EEG and scalp EEG were recorded concurrently from the subjects in a study comprising both auditory and visual stimuli. The EEG recordings were analyzed with independent component analysis (ICA) and using the individualized ear-EEG forward models, single dipole fitting was performed for each independent component (IC). A subset of ICs were selected, based on how well they were modeled by a single dipole in the brain volume. The correlation between the topographic IC map and the topographic map predicted by the forward model, was computed for each IC. Generally, the correlation was high in the ear closest to the dipole location, showing that the ear-EEG forward models provided a good model to predict ear potentials. In addition, we demonstrated that the developed forward models can be used to explore the sensitivity to brain sources for different ear-EEG electrode configurations. We consider the proposed method to be an important step forward in the characterization and utilization of ear-EEG.},
  note = {PubMed query source: Scott Makeig}
}

@article{Pernet201931239435,
  title = {EEG-BIDS, an extension to the brain imaging data structure for electroencephalography.},
  author = {Pernet, CR and Appelhoff, S and Gorgolewski, KJ and Flandin, G and Phillips, C and Delorme, A and Oostenveld, R},
  journal = {Scientific data},
  year = {2019},
  doi = {10.1038/s41597-019-0104-8},
  pmid = {31239435},
  url = {https://pubmed.ncbi.nlm.nih.gov/31239435/},
  abstract = {The Brain Imaging Data Structure (BIDS) project is a rapidly evolving effort in the human brain imaging research community to create standards allowing researchers to readily organize and share study data within and between laboratories. Here we present an extension to BIDS for electroencephalography (EEG) data, EEG-BIDS, along with tools and references to a series of public EEG datasets organized using this new standard.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Li201931295566,
  title = {Default mode and visual network activity in an attention task: Direct measurement with intracranial EEG.},
  author = {Li, J and Kronemer, SI and Herman, WX and Kwon, H and Ryu, JH and Micek, C and Wu, Y and Gerrard, J and Spencer, DD and Blumenfeld, H},
  journal = {NeuroImage},
  year = {2019},
  doi = {10.1016/j.neuroimage.2019.07.016},
  pmid = {31295566},
  url = {https://pubmed.ncbi.nlm.nih.gov/31295566/},
  abstract = {Dynamic attention states are necessary to navigate the ever changing task demands of daily life. Previous investigations commonly utilize a block paradigm to study sustained and transient changes in attention networks. fMRI investigations have shown that sustained attention in visual block design attention tasks corresponds to decreased signal in the default mode and visual processing networks. While task negative networks are anticipated to decrease during active task engagement, it is unexpected that visual networks would also be suppressed during a visual task where event-related fMRI studies have found transient increases to visual stimuli. To resolve these competing results, the current investigations utilized intracranial EEG to directly interrogate visual and default mode network dynamics during a visual continuous performance task. We used the electrophysiological data to model expected fMRI signals and to maximize interpretation of current results with previous investigations. Results show broadband gamma power decreases in the default mode network, corresponding to previous EEG and fMRI findings. Meanwhile, visual processing regions including the primary visual cortex and fusiform gyrus demonstrate both sustained decreases during task engagement and stimuli-driven transient increases in gamma power. Modeled fMRI based on gamma power reproduces signal decreases reported in the fMRI literature, and emphasizes the insensitivity of fMRI to transient, regularly spaced signal changes embedded within sustained network dynamics. The signal processing functions of the dynamic visual and default mode network changes explored in this study are unknown but may be elucidated through further investigation.},
  note = {PubMed query source: Ying Wu}
}

@article{Wagner201931427937,
  title = {Can Oscillatory Alpha-Gamma Phase-Amplitude Coupling be Used to Understand and Enhance TMS Effects?},
  author = {Wagner, J and Makeig, S and Hoopes, D and Gola, M},
  journal = {Frontiers in human neuroscience},
  year = {2019},
  doi = {10.3389/fnhum.2019.00263},
  pmid = {31427937},
  url = {https://pubmed.ncbi.nlm.nih.gov/31427937/},
  abstract = {Recent applications of simultaneous scalp electroencephalography (EEG) and transcranial magnetic stimulation (TMS) suggest that adapting stimulation to underlying brain states may enhance neuroplastic effects of TMS. It is often assumed that longer-lasting effects of TMS on brain function may be mediated by phasic interactions between TMS pulses and endogenous cortical oscillatory dynamics. The mechanisms by which TMS exerts its neuromodulatory effects, however, remain unknown. Here, we discuss evidence concerning the functional effects on synaptic plasticity of oscillatory cross-frequency coupling in cortical networks as a potential framework for understanding the neuromodulatory effects of TMS. We first discuss evidence for interactions between endogenous oscillatory brain dynamics and externally induced electromagnetic field activity. Alpha band (8-12 Hz) activities are of special interest here because of the wide application and therapeutic effectiveness of rhythmic TMS (rTMS) using a stimulus repetition frequency at or near 10 Hz. We discuss the large body of literature on alpha oscillations suggesting that alpha oscillatory cycles produce periodic inhibition or excitation of neuronal processing through phase-amplitude coupling (PAC) of low-frequency oscillations with high-frequency broadband (or gamma) bursting. Such alpha-gamma coupling may reflect excitability of neuronal ensembles underlying neuroplasticity effects of TMS. We propose that TMS delivery with simultaneous EEG recording and near real-time estimation of source-resolved alpha-gamma PAC might be used to select the precise timing of TMS pulse deliveries so as to enhance the neuroplastic effects of TMS therapies.},
  note = {PubMed query source: Scott Makeig}
}

@article{Randau201930927608,
  title = {Attenuated mismatch negativity in patients with first-episode antipsychotic-naive schizophrenia using a source-resolved method.},
  author = {Randau, M and Oranje, B and Miyakoshi, M and Makeig, S and Fagerlund, B and Glenthøj, B and Bak, N},
  journal = {NeuroImage. Clinical},
  year = {2019},
  doi = {10.1016/j.nicl.2019.101760},
  pmid = {30927608},
  url = {https://pubmed.ncbi.nlm.nih.gov/30927608/},
  abstract = {Mismatch negativity (MMN) is a measure of pre-attentive auditory information processing related to change detection. Traditional scalp-level EEG methods consistently find attenuated MMN in patients with chronic but not first-episode schizophrenia. In the current paper, we use a source-resolved method to assess MMN and hypothesize that more subtle changes can be identified with this analysis method. Fifty-six first-episode antipsychotic-naïve schizophrenia (FEANS) patients (31 males, 25 females, mean age 24.6) and 64 matched controls (37 males, 27 females, mean age 24.8) were assessed for duration-, frequency- and combined-type MMN and P3a as well as 4 clinical, 3 cognitive and 3 psychopathological measures. To evaluate and correlate MMN at source-level, independent component analysis (ICA) was applied to the continuous EEG data to derive equivalent current dipoles which were clustered into 19 clusters based on cortical location. No scalp channel group MMN or P3a amplitude differences were found. Of the localized clusters, several were in or near brain areas previously suggested to be involved in the MMN response, including frontal and anterior cingulate cortices and superior temporal and inferior frontal gyri. For duration deviants, MMN was attenuated at the right superior temporal gyrus in patients compared to healthy controls (p = 0.01), as was P3a at the superior frontal cortex (p = 0.01). No individual patient correlations with clinical, cognitive, or psychopathological measures survived correction for multiple comparisons. Attenuated source-localized MMN and P3a peak contributions can be identified in FEANS patients using a method based on independent component analysis (ICA). This indicates that deficits in pre-attentive auditory information processing are present at this early stage of schizophrenia and are not the result of disease chronicity or medication. This is to our knowledge the first study on FEANS patients using this more detailed method.},
  note = {PubMed query source: Scott Makeig}
}

@article{Sklenarik201931257916,
  title = {Approach bias for erotic stimuli in heterosexual male college students who use pornography.},
  author = {Sklenarik, S and Potenza, MN and Gola, M and Kor, A and Kraus, SW and Astur, RS},
  journal = {Journal of behavioral addictions},
  year = {2019},
  doi = {10.1556/2006.8.2019.31},
  pmid = {31257916},
  url = {https://pubmed.ncbi.nlm.nih.gov/31257916/},
  abstract = {Addicted individuals often demonstrate relatively automatic action tendencies in response to addiction-related stimuli, whereby they approach rather than avoid addictive stimuli. This study assessed whether an approach bias for erotic stimuli exists among heterosexual college-aged males who report using pornography. We tested 72 male undergraduate students using an approach-avoidance task employing erotic stimuli, during which participants were instructed to push or pull a joystick in response to image orientation. To simulate approach and avoidance movements, pulling the joystick enlarged the image and pushing shrunk the image. Frequency and severity of pornography use was assessed using a Brief Pornography Screener and the Problematic Pornography Use Scale (PPUS). Participants demonstrated a significant approach bias for erotic stimuli as compared to neutral stimuli, and this approach bias significantly correlated with pornography-use measures. Moreover, individuals with problematic pornography use (as classified by the PPUS) showed more than double the approach bias than did non-problematic users. The observation of cognitive biases for erotic stimuli in individuals with problematic pornography use indicate similarities between behavioral and substance addictions.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Efrati201931328954,
  title = {Adolescents' compulsive sexual behavior: The role of parental competence, parents' psychopathology, and quality of parent-child communication about sex.},
  author = {Efrati, Y and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2019},
  doi = {10.1556/2006.8.2019.33},
  pmid = {31328954},
  url = {https://pubmed.ncbi.nlm.nih.gov/31328954/},
  abstract = {Compulsive sexual behavior (CSB) has implications for clinical and non-clinical adult populations. Disposition to CSB has been shown to influence adolescence sexual behaviors, but the development of adolescents' disposition toward CSB has yet to be examined in the family context. In this study, we investigated whether parent-adolescent communication mediates the links between parental characteristics and adolescents' CSB. The sample included 275 Israeli families [triad of mothers (age = 34-63 years,  M  = 45.48,  SD  = 5.46), fathers (age = 36-83 years,  M  = 48.33,  SD  = 6.63), and one adolescent (48.2% boys, 51.1% girls; age = 14-18 years,  M  = 16.23,  SD  = 1.18)]. Parents completed measures of psychopathology, parental self-esteem, and parental self-efficacy, and adolescents completed measures of quality of sex-related communication and CSB. The results indicate that, for girls, higher maternal self-esteem and lower psychopathology were linked with better sex-related communication and so with lower CSB. For boys, only parental religiosity was linked with the quality of sex-related communication and CSB, with religious parents having better communication than secular ones. The findings provide an opportunity for researchers to gain a better insight into the dynamics of familial factors in the development of CSB among adolescents.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Artoni201930705925,
  title = {A visual working memory dataset collection with bootstrap Independent Component Analysis for comparison of electroencephalographic preprocessing pipelines.},
  author = {Artoni, F and Delorme, A and Makeig, S},
  journal = {Data in brief},
  year = {2019},
  doi = {10.1016/j.dib.2018.12.022},
  pmid = {30705925},
  url = {https://pubmed.ncbi.nlm.nih.gov/30705925/},
  abstract = {Here we present an electroencephalographic (EEG) collection of 71-channel datasets recorded from 14 subjects (7 males, 7 females, aged 20-40 years) while performing a visual working memory task with a T set of 150 Independent Component Analysis (ICA) decompositions by Extended Infomax using RELICA, each on a bootstrap resampling of the data. These data are linked to the paper "Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition" [1]. Independent components (ICs) are clustered within subject and thereby associated with a quality index (QIc) measure of their stability to data resampling. Sets of single ICA decompositions obtained after applying Principal Component Analysis (PCA) to the data to perform dimension reduction retaining (85%, 95%, 99%) of data variance are also included, as are the positions of the best fitting equivalent dipoles for ICs whose scalp projections are compatible with a compact brain source. These bootstrap ICs may be used as benchmarks for different data preprocessing pipelines and/or ICA algorithms, allowing investigation of the effects that noise or insufficient data have on the quality of ICA decompositions.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wahbeh201930815253,
  title = {A physiological examination of perceived incorporation during trance.},
  author = {Wahbeh, H and Cannard, C and Okonsky, J and Delorme, A},
  journal = {F1000Research},
  year = {2019},
  doi = {10.12688/f1000research.17157.2},
  pmid = {30815253},
  url = {https://pubmed.ncbi.nlm.nih.gov/30815253/},
  abstract = {Background:  Numerous world cultures believe channeling provides genuine information, and channeling rituals in various forms are regularly conducted in both religious and non-religious contexts. Little is known about the physiological correlates of the subjective experience of channeling.  Methods:  We conducted a prospective within-subject design study with 13 healthy adult trance channels. Participants alternated between 5-minute blocks of channeling and no-channeling three times while electroencephalography (EEG), electrocardiography (ECG), galvanic skin response (GSR), and respiration were collected on two separate days. Voice recordings of the same story read in channeling and no-channeling states were also analyzed.    Results:  The pre-laboratory survey data about demographics, perception of the source, purpose and utility of channeled information reflected previous reports. Most participants were aware of their experience (rather than in a full trance) and had varying levels of perceived incorporation (i.e. control of their body). Voice analysis showed an increase in voice arousal and power (dB/Hz) differences in the 125 Hz bins between 0 and 625 Hz, and 3625 and 3875 Hz when reading during the channeling state versus control. Despite subjective perceptions of distinctly different states, no substantive differences were seen in EEG frequency power, ECG measures, GSR and respiration.  Conclusions:  Voice parameters were different between channeling and no-channeling states using rigorous controlled methods, but other physiology measure collected were not. Considering the subjective and phenomenological differences observed, future studies should include other measures such as EEG connectivity analyses, fMRI and biomarkers.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Xiao201931946527,
  title = {A comparison of classification methods for recognizing single-trial P300 in brain-computer interfaces.},
  author = {Xiao, X and Xu, M and Wang, Y and Jung, TP and Ming, D},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2019},
  doi = {10.1109/EMBC.2019.8857521},
  pmid = {31946527},
  url = {https://pubmed.ncbi.nlm.nih.gov/31946527/},
  abstract = {P300s are one of the most popular and robust control signals for brain-computer interfaces (BCIs). Fast classifying P300s is vital for the good performance of P300-based BCIs. However, due to noisy background electroencephalography (EEG) environments, current P300-based BCI systems need to collect multiple trials for a reliable output, which is inefficient. This study compared a recently developed algorithm, i.e. discriminative canonical pattern matching (DCPM), with five traditional classification methods,i.e. linear discriminant analysis (LDA), stepwise LDA, Bayesian LDA, shrinkage LDA and spatial-temporal discriminant analysis (STDA), for the detection of single-trial P300s. Eight subjects participated in the classical P300-speller experiments. Study results showed that the DCPM significantly outperformed the other traditional methods in single-trial P300 classification even with small training samples, suggesting the DCPM is a promising classification algorithm for the P300-based BCI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Marini201931096191,
  title = {A comparative evaluation of signal quality between a research-grade and a wireless dry-electrode mobile EEG system.},
  author = {Marini, F and Lee, C and Wagner, J and Makeig, S and Gola, M},
  journal = {Journal of neural engineering},
  year = {2019},
  doi = {10.1088/1741-2552/ab21f2},
  pmid = {31096191},
  url = {https://pubmed.ncbi.nlm.nih.gov/31096191/},
  abstract = {Electroencephalography (EEG) is widely used by clinicians, scientists, engineers and other professionals worldwide, with an increasing number of low-cost, commercially-oriented EEG systems that have become available in recent years. One such system is the Cognionics Quick-20 (Cognionics Inc., San Diego, USA), which uses dry electrodes and offers the convenience of portability thanks to its built-in amplifier and wireless connection. Because of such characteristics, this system has been used in several applications for both clinical and basic research studies. However, an investigation of the quality of the signals that are recorded using this system has not yet been reported. To bridge this gap, here we conducted a systematic comparison of signal quality between the Cognionics Quick-20 system and the Brain Products actiCAP/actiCHamp (Brain Products GmbH, Munich, Germany), a state-of-the-art, wet-electrode, research-oriented EEG system. Resting-state EEG data were recorded from twelve human participants at rest in eyes open and eyes closed conditions. For both systems we evaluated the similarity of mean recorded power spectral density, and detection of alpha suppression associated with eyes open relative to eyes closed. Power spectral densities were highly correlated across systems, with only minor topographical variability across the scalp. Both systems recorded alpha suppression during eyes open relative to eyes closed conditions. These results attest to the robustness and reliability of the dry-electrode Cognionics system relatively to the widely used Brain Products laboratory EEG system, and thus validate its utility for clinical and basic research purposes, at least in studies in which participants do not move.},
  note = {PubMed query source: Scott Makeig}
}

@article{Siddharth201930188809,
  title = {A Wearable Multi-Modal Bio-Sensing System Towards Real-World Applications.},
  author = {Siddharth and Patel, AN and Jung, TP and Sejnowski, TJ},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2019},
  doi = {10.1109/TBME.2018.2868759},
  pmid = {30188809},
  url = {https://pubmed.ncbi.nlm.nih.gov/30188809/},
  abstract = {Multi-modal bio-sensing has recently been used as effective research tools in affective computing, autism, clinical disorders, and virtual reality among other areas. However, none of the existing bio-sensing systems support multi-modality in a wearable manner outside well-controlled laboratory environments with research-grade measurements. This paper attempts to bridge this gap by developing a wearable multi-modal bio-sensing system capable of collecting, synchronizing, recording, and transmitting data from multiple bio-sensors: PPG, EEG, eye-gaze headset, body motion capture, GSR, etc., while also providing task modulation features including visual-stimulus tagging. This study describes the development and integration of various components of our system. We evaluate the developed sensors by comparing their measurements to those obtained by a standard research-grade bio-sensors. We first evaluate different sensor modalities of our headset, namely, earlobe-based PPG module with motion-noise canceling for ECG during heart-beat calculation. We also compare the steady-state visually evoked potentials measured by our shielded dry EEG sensors with the potentials obtained by commercially available dry EEG sensors. We also investigate the effect of head movements on the accuracy and precision of our wearable eye-gaze system. Furthermore, we carry out two practical tasks to demonstrate the applications of using multiple sensor modalities for exploring previously unanswerable questions in bio-sensing. Specifically, utilizing bio-sensing, we show which strategy works best for playing "Where is Waldo?" visual-search game, changes in EEG corresponding to true vs. false target fixations in this game, and predicting the loss/draw/win states through bio-sensing modalities while learning their limitations in a "Rock-Paper-Scissors" game.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Burgos201829766612,
  title = {Visuomotor coordination and cortical connectivity of modular motor learning.},
  author = {Burgos, PI and Mariman, JJ and Makeig, S and Rivera-Lillo, G and Maldonado, PE},
  journal = {Human brain mapping},
  year = {2018},
  doi = {10.1002/hbm.24215},
  pmid = {29766612},
  url = {https://pubmed.ncbi.nlm.nih.gov/29766612/},
  abstract = {The ability to transfer sensorimotor skill components to new actions and the capacity to use skill components from whole actions are characteristic of the adaptability of the human sensorimotor system. However, behavioral evidence suggests complex limitations for transfer after combined or modular learning of motor adaptations. Also, to date, only behavioral analysis of the consequences of the modular learning has been reported, with little understanding of the sensorimotor mechanisms of control and the interaction between cortical areas. We programmed a video game with distorted kinematic and dynamic features to test the ability to combine sensorimotor skill components learned modularly (composition) and the capacity to use separate sensorimotor skill components learned in combination (decomposition). We examined motor performance, eye-hand coordination, and EEG connectivity. When tested for integrated learning, we found that combined practice initially performed better than separated practice, but differences disappeared after integrated practice. Separate learning promotes fewer anticipatory control mechanisms (depending more on feedback control), evidenced in a lower gaze leading behavior and in higher connectivity between visual and premotor domains, in comparison with the combined practice. The sensorimotor system can acquire motor modules in a separated or integrated manner. However, the system appears to require integrated practice to coordinate the adaptations with the skill learning and the networks involved in the integrated behavior. This integration seems to be related to the acquisition of anticipatory mechanism of control and with the decrement of feedback control.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gola201830487759,
  title = {Ventral Striatal Reactivity in Compulsive Sexual Behaviors.},
  author = {Gola, M and Draps, M},
  journal = {Frontiers in psychiatry},
  year = {2018},
  doi = {10.3389/fpsyt.2018.00546},
  pmid = {30487759},
  url = {https://pubmed.ncbi.nlm.nih.gov/30487759/},
  abstract = {Compulsive Sexual Behaviors (CSB) are a reason to seek treatment. Given this reality, the number of studies on CSB has increased substantially in the last decade and the World Health Organization (WHO) included CSB in its proposal for the upcoming ICD-11. Sixty percent of the neuroimaging studies on CSB published since 2014 aimed to examine similarities and differences between brain mechanisms underlying CSB, gambling disorder, and substance use disorders. One of the crucial brain circuits involved in addiction is the reward system involving the ventral striatum (including nucleus accumbens). There are two distinct theories describing ventral striatal activity in addictions: Incentive Salience Theory (IST) and Reward Deficiency Syndrome (RDS). IST describes increased ventral striatal activations during the anticipation of addiction-related reward, while RDS describes decreased ventral striatal reactivity both during the anticipation of the reward and during the reward processing. Here, we aim to investigate how the findings on ventral striatal reactivity in CSB support each of these two addiction frameworks. For this purpose, we conducted a systematic review of neuroimaging studies on CSB available in Pubmed, EBSCO, and Google Scholar between 2005 and 2018. We found nine relevant research papers. Only four of these studies directly investigated processing of erotic cues and/or rewards and reported findings related to ventral striatum activations. Three of these studies indicate increased ventral striatal reactivity for erotic stimuli, which is consistent with IST and does not support predictions based on RDS. Therefore, the current state of this data suggest that CSB is related to increased ventral striatal reactivity during the anticipation of erotic stimuli.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Efrati201830378458,
  title = {Understanding and predicting profiles of compulsive sexual behavior among adolescents.},
  author = {Efrati, Y and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2018},
  doi = {10.1556/2006.7.2018.100},
  pmid = {30378458},
  url = {https://pubmed.ncbi.nlm.nih.gov/30378458/},
  abstract = {This two-study research was designed to define and predict profiles of compulsive sexual behavior (CSB) among non-clinical population of adolescents, and aimed to fill gaps in the current research. In Study 1 (N = 1,182), we examined the profiles of CSB among adolescents using latent profile analysis. Results revealed the following three clusters: abstainers, sexual fantasizers, and individuals with CSB. In Study 2 (N = 618), we replicated this classification and examined differences between the clusters in Big Five personality traits, locus of control, attachment orientations, loneliness, age, gender, socioeconomic status (SES), residence quality, use of pornography, and sex-related online activities. Adolescents classified into different clusters significantly differed in personality traits, loneliness, age, SES, use of pornography, and sex-related online activities. Specifically, individuals with CSB had external locus of control, anxious attachment, greater loneliness, higher frequency of pornography use, and more sex-related online activities than the other groups. The current research expands the knowledge about CSB by providing a more individualized approach to understanding CSB among adolescence.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Nakanishi201830440348,
  title = {Transferring Shared Responses Across Electrode Montages for Facilitating Calibration in High-Speed Brain Spellers.},
  author = {Nakanishi, M and Wang, YT and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512269},
  pmid = {30440348},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440348/},
  abstract = {Recent studies have shown that using the user's average steady-state visual evoked responses (SSVEPs) as the template to template-matching methods could significantly improve the accuracy and speed of the SSVEP-based brain- computer interface (BCI). However, collecting the pilot data for each individual can be time-consuming. To resolve this practical issue, this study aims to explore the feasibility of leveraging pre- recorded datasets from the same users by transferring common electroencephalogram (EEG) responses across different sessions with the same or different electrode montages. The proposed method employs spatial filtering techniques including response averaging, canonical correlation analysis (CCA), and task- related component analysis (TRCA) to project scalp EEG recordings onto a shared response domain. The transferability was evaluated by using 40-class SSVEPs recorded from eight subjects with nine electrodes on two different days. Three subsets of electrode montages were selected to simulate different scenarios such as identical, partly overlapped, and non-overlapped electrode placements across two sessions. The target identification accuracy of the proposed methods with transferred training data significantly outperformed a conventional training-free algorithm. The result suggests training data required in the BCI speller could be transferred from different EEG montages and/or headsets.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wei201829432111,
  title = {Toward Drowsiness Detection Using Non-hair-Bearing EEG-Based Brain-Computer Interfaces.},
  author = {Wei, CS and Wang, YT and Lin, CT and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2018},
  doi = {10.1109/TNSRE.2018.2790359},
  pmid = {29432111},
  url = {https://pubmed.ncbi.nlm.nih.gov/29432111/},
  abstract = {Drowsy driving is one of the major causes that lead to fatal accidents worldwide. For the past two decades, many studies have explored the feasibility and practicality of drowsiness detection using electroencephalogram (EEG)-based brain-computer interface (BCI) systems. However, on the pathway of transitioning laboratory-oriented BCI into real-world environments, one chief challenge is to obtain high-quality EEG with convenience and long-term wearing comfort. Recently, acquiring EEG from non-hair-bearing (NHB) scalp areas has been proposed as an alternative solution to avoid many of the technical limitations resulted from the interference of hair between electrodes and the skin. Furthermore, our pilot study has shown that informative drowsiness-related EEG features are accessible from the NHB areas. This study extends the previous work to quantitatively evaluate the performance of drowsiness detection using cross-session validation with widely studied machine-learning classifiers. The offline results showed no significant difference between the accuracy of drowsiness detection using the NHB EEG and the whole-scalp EEG across all subjects ( ). The findings of this study demonstrate the efficacy and practicality of the NHB EEG for drowsiness detection and could catalyze explorations and developments of many other real-world BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wang201829479310,
  title = {Theta and Alpha Oscillations in Attentional Interaction during Distracted Driving.},
  author = {Wang, YK and Jung, TP and Lin, CT},
  journal = {Frontiers in behavioral neuroscience},
  year = {2018},
  doi = {10.3389/fnbeh.2018.00003},
  pmid = {29479310},
  url = {https://pubmed.ncbi.nlm.nih.gov/29479310/},
  abstract = {Performing multiple tasks simultaneously usually affects the behavioral performance as compared with executing the single task. Moreover, processing multiple tasks simultaneously often involve more cognitive demands. Two visual tasks, lane-keeping task and mental calculation, were utilized to assess the brain dynamics through 32-channel electroencephalogram (EEG) recorded from 14 participants. A 400-ms stimulus onset asynchrony (SOA) factor was used to induce distinct levels of attentional requirements. In the dual-task conditions, the deteriorated behavior reflected the divided attention and the overlapping brain resources used. The frontal, parietal and occipital components were decomposed by independent component analysis (ICA) algorithm. The event- and response-related theta and alpha oscillations in selected brain regions were investigated first. The increased theta oscillation in frontal component and decreased alpha oscillations in parietal and occipital components reflect the cognitive demands and attentional requirements as executing the designed tasks. Furthermore, time-varying interactive over-additive (O-Add), additive (Add) and under-additive (U-Add) activations were explored and summarized through the comparison between the summation of the elicited spectral perturbations in two single-task conditions and the spectral perturbations in the dual task. Add and U-Add activations were observed while executing the dual tasks. U-Add theta and alpha activations dominated the posterior region in dual-task situations. Our results show that both deteriorated behaviors and interactive brain activations should be comprehensively considered for evaluating workload or attentional interaction precisely.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wen201829666577,
  title = {The Study of Evaluation and Rehabilitation of Patients With Different Cognitive Impairment Phases Based on Virtual Reality and EEG.},
  author = {Wen, D and Lan, X and Zhou, Y and Li, G and Hsu, SH and Jung, TP},
  journal = {Frontiers in aging neuroscience},
  year = {2018},
  doi = {10.3389/fnagi.2018.00088},
  pmid = {29666577},
  url = {https://pubmed.ncbi.nlm.nih.gov/29666577/},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gola201829464450,
  title = {The Proof of the Pudding Is in the Tasting: Data Are Needed to Test Models and Hypotheses Related to Compulsive Sexual Behaviors.},
  author = {Gola, M and Potenza, MN},
  journal = {Archives of sexual behavior},
  year = {2018},
  doi = {10.1007/s10508-018-1167-x},
  pmid = {29464450},
  url = {https://pubmed.ncbi.nlm.nih.gov/29464450/},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wu201826994213,
  title = {Study duration for three-arm non-inferiority survival trials designed for accrual by cohorts.},
  author = {Wu, Y and Li, Y and Hou, Y and Li, K and Zhou, X},
  journal = {Statistical methods in medical research},
  year = {2018},
  doi = {10.1177/0962280216633908},
  pmid = {26994213},
  url = {https://pubmed.ncbi.nlm.nih.gov/26994213/},
  abstract = {Study planning is particularly complex for survival trials because it usually involves an accrual period and a continued observation period after accrual closure. The three-arm clinical trial design, which includes a test treatment, an active reference, and a placebo control, is the gold standard design for the assessment of non-inferiority. The existing statistical methods of calculating minimal sample size for non-inferiority trials with three-arm design and survival-type endpoints cannot take into consideration the accrual rate of patients to the trial, the length of accrual period, the length of continued observation period after accrual closure, and unbalanced allocation of the total sample size. The purpose of this paper is to develop a statistical method, which allows for all these sources of variability for planning non-inferiority trials with the gold standard design for censored, exponentially distributed time-to-event data. The proposed method is based on the assumption of exponentially distributed failure times and a non-inferiority test formulated in terms of the retention of effect hypotheses. It can be used to calculate the duration of accrual required to assure a desired power for non-inferiority trials with active and placebo control. We illustrate the use of the method by considering a randomized, active- and placebo-controlled trial in depression associated with Parkinson's disease. We then explore the validity of the proposed method by simulation studies. An R-language program for the implementation of the proposed algorithm is provided as supplementary material.},
  note = {PubMed query source: Ying Wu}
}

@article{Brandmeyer201827815577,
  title = {Reduced mind wandering in experienced meditators and associated EEG correlates.},
  author = {Brandmeyer, T and Delorme, A},
  journal = {Experimental brain research},
  year = {2018},
  doi = {10.1007/s00221-016-4811-5},
  pmid = {27815577},
  url = {https://pubmed.ncbi.nlm.nih.gov/27815577/},
  abstract = {One outstanding question in the contemplative science literature relates to the direct impact of meditation experience on the monitoring of internal states and its respective correspondence with neural activity. In particular, to what extent does meditation influence the awareness, duration and frequency of the tendency of the mind to wander. To assess the relation between mind wandering and meditation, we tested 2 groups of meditators, one with a moderate level of experience (non-expert) and those who are well advanced in their practice (expert). We designed a novel paradigm using self-reports of internal mental states based on an experiential sampling probe paradigm presented during ~1 h of seated concentration meditation to gain insight into the dynamic measures of electroencephalography (EEG) during absorption in meditation as compared to reported mind wandering episodes. Our results show that expert meditation practitioners report a greater depth and frequency of sustained meditation, whereas non-expert practitioners report a greater depth and frequency of mind wandering episodes. This is one of the first direct behavioral indices of meditation expertise and its associated impact on the reduced frequency of mind wandering, with corresponding EEG activations showing increased frontal midline theta and somatosensory alpha rhythms during meditation as compared to mind wandering in expert practitioners. Frontal midline theta and somatosensory alpha rhythms are often observed during executive functioning, cognitive control and the active monitoring of sensory information. Our study thus provides additional new evidence to support the hypothesis that the maintenance of both internal and external orientations of attention may be maintained by similar neural mechanisms and that these mechanisms may be modulated by meditation training.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Gola201829895182,
  title = {Promoting educational, classification, treatment, and policy initiatives.},
  author = {Gola, M and Potenza, MN},
  journal = {Journal of behavioral addictions},
  year = {2018},
  doi = {10.1556/2006.7.2018.51},
  pmid = {29895182},
  url = {https://pubmed.ncbi.nlm.nih.gov/29895182/},
  abstract = {The letter by Kraus et al. (2018) published recently in World Psychiatry presents diagnostic criteria for compulsive sexual behaviors (CSBs). Here, we discuss the potential impact of including CSB disorder in ICD-11 for four areas: educational efforts related to CSB (for both clinicians and patients), investigation of underlying mechanisms and subtypes, development of personalized treatment frameworks, and answering socially important questions and advancing important prevention efforts and effective policies. Each of these four areas has their own challenges that should be addressed, and we briefly describe and discuss them. We hope that this information will help continue a dialog and provide a framework for moving forward in this area.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Sarafpour201830440817,
  title = {Postural Balance Performance of Children with ADHD, with and without Medication: A Quantitative Approach.},
  author = {Sarafpour, M and Shirazi, SY and Shirazi, E and Ghazaei, F and Parnianpour, Z},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512636},
  pmid = {30440817},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440817/},
  abstract = {tAtention Deficit Hyperactivity Disorder (ADHD) significantly impairs the performance of students during their early school years. However, the extent of the difference in postural stability between children with ADHD and Typically Developed (TD) children, are still not fully understood. Also, it is clinically important to investigate possible effects of medication on their performances. We recruited 38 children between the ages 6 to 12 with ADHD (15 medically naïve, 23 with current treatment history) and 25 age-matched as TD. Postural stability performance was assessed in four conditions: 1-eyes open, 2-eyes closed, 3-eyes open on foam and 4-eyes closed on foam. A cost-effective mobile force platform was used to evaluate postural performance quantitatively. Results revealed a lower stability performance in the medically-naïve participants especially in trials with eyes open on foam. No significant difference in performance was seen between children with medical treatment history and the TD group. Results suggest that using medication can effectively enhance postural stability for children with ADHD. We found portable balance assessment tools helpful in identifying changes in motor performances among children with ADHD. Our results indicate that further research is needed to understand the exact implications of ADHD on postural stability under different sensory stimuli.},
  note = {PubMed query source: Seyed Yahya Shirazi}
}

@article{Gouraud201830294267,
  title = {Out of the Loop, in Your Bubble: Mind Wandering Is Independent From Automation Reliability, but Influences Task Engagement.},
  author = {Gouraud, J and Delorme, A and Berberian, B},
  journal = {Frontiers in human neuroscience},
  year = {2018},
  doi = {10.3389/fnhum.2018.00383},
  pmid = {30294267},
  url = {https://pubmed.ncbi.nlm.nih.gov/30294267/},
  abstract = {This study examined the influence of automation reliability on task-unrelated mind wandering (MW) frequency and the impact of MW on task engagement. Automated environment features make it particularly prone to increase MW frequency. Through mechanisms like complacency or agency, automating a task could increase MW frequency for the operator. For safety-critical industries, the lower perception and degraded stimuli processing associated with MW, summarized by the term "decoupling hypothesis," are particularly concerning. Sixteen participants supervised an autopilot avoiding obstacles with two levels of reliability. Each condition lasted 45 min. We recorded thoughts as either pertaining to being focused, task-related MW or task-unrelated MW. We also recorded perceived mental demand, trust regarding the autopilot and oculometric measures. Based on questionnaire results, our protocol succeeded in inducing more mental demand and lower trust when the automation was unreliable. Attentional states were not correlated, nor did it influence trust in the system reliability. On the contrary, mental demand ratings and pupil diameter were lower during both task-related and task-unrelated MW, compared to those during the focus attentional state. This shows that perceptual decoupling also affects the engagement of operators in automated environments, which may dramatically lower their ability to supervise automation efficiently. This research informs human-automation designers to consider operator engagement when creating automated systems.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{PionTonachini201830440352,
  title = {Online Automatic Artifact Rejection using the Real-time EEG Source-mapping Toolbox (REST).},
  author = {Pion-Tonachini, L and Hsu, SH and Chang, CY and Jung, TP and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512191},
  pmid = {30440352},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440352/},
  abstract = {Non-brain contributions to electroencephalographic (EEG) signals, often referred to as artifacts, can hamper the analysis of scalp EEG recordings. This is especially true when artifacts have large amplitudes (e.g., movement artifacts), or occur continuously (like eye-movement artifacts). Offline automated pipelines can detect and reduce artifact in EEG data, but no good solution exists for online processing of EEG data in near real time. Here, we propose the combined use of online artifact subspace reconstruction (ASR) to remove large amplitude transients, and online recursive independent component analysis (ORICA) combined with an independent component (IC) classifier to compute, classify, and remove artifact ICs. We demonstrate the efficacy of the proposed pipeline using 2 EEG recordings containing series of (1) movement and muscle artifacts, and (2) cued blinks and saccades. This pipeline is freely available in the Real-time EEG Sourcemapping Toolbox (REST) for MATLAB (The Mathworks, Inc.).},
  note = {PubMed query source: Scott Makeig}
}

@article{Huang201828768447,
  title = {Neural Oscillation Correlates Chemistry Decision-Making.},
  author = {Huang, LY and She, HC and Jung, TP},
  journal = {International journal of neural systems},
  year = {2018},
  doi = {10.1142/S0129065717500319},
  pmid = {28768447},
  url = {https://pubmed.ncbi.nlm.nih.gov/28768447/},
  abstract = {This study explored the electroencephalography (EEG) dynamics during a chemistry-related decision-making task and further examined whether the correctness of the decision-making performance could be reflected by EEG activity. A total of 66 undergraduate students' EEG were collected while they participated in a chemistry-related decision-making task in which they had to retrieve the relevant chemistry concepts in order to make correct decisions for each task item. The results showed that it was only in the anterior cingulate cortex (ACC) cluster that distinct patterns in EEG dynamics were displayed for the correct and incorrect responses. The logistic regression results indicated that ACC theta power from 300[Formula: see text]ms to 250[Formula: see text]ms before stimulus onset was the most informative factor for estimating the likelihood of making correct decisions in the chemistry-related decision-making task, while it was the ACC low beta power from 150[Formula: see text]ms to 250[Formula: see text]ms after stimulus onset. The results suggested that the ACC theta augmentation before the stimulus onset serves to actively maintain the relevant information for retrieval from long-term memory, while the ACC low beta augmentation after the stimulus onset may serve the function of mapping the encoded stimulus onto the relevant criteria that the given participant has held within his or her mind to guide the decision-making responses.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Siddharth201830440395,
  title = {Multi-modal Approach for Affective Computing.},
  author = {Siddharth and Jung, TP and Sejnowski, TJ},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512320},
  pmid = {30440395},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440395/},
  abstract = {Throughout the past decade, many studies have classified human emotions using only a single sensing modality such as face video, electroencephalogram (EEG), electrocardiogram (ECG), galvanic skin response (GSR), etc. The results of these studies are constrained by the limitations of these modalities such as the absence of physiological biomarkers in the face-video analysis, poor spatial resolution in EEG, poor temporal resolution of the GSR etc. Scant research has been conducted to compare the merits of these modalities and understand how to best use them individually and jointly. Using multi-modal AMIGOS dataset, this study compares the performance of human emotion classification using multiple computational approaches applied to face videos and various bio-sensing modalities. Using a novel method for compensating physiological baseline we show an increase in the classification accuracy of various approaches that we use. Finally, we present a multi-modal emotion-classification approach in the domain of affective computing research.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hsu201830086409,
  title = {Modeling brain dynamic state changes with adaptive mixture independent component analysis.},
  author = {Hsu, SH and Pion-Tonachini, L and Palmer, J and Miyakoshi, M and Makeig, S and Jung, TP},
  journal = {NeuroImage},
  year = {2018},
  doi = {10.1016/j.neuroimage.2018.08.001},
  pmid = {30086409},
  url = {https://pubmed.ncbi.nlm.nih.gov/30086409/},
  abstract = {There is a growing interest in neuroscience in assessing the continuous, endogenous, and nonstationary dynamics of brain network activity supporting the fluidity of human cognition and behavior. This non-stationarity may involve ever-changing formation and dissolution of active cortical sources and brain networks. However, unsupervised approaches to identify and model these changes in brain dynamics as continuous transitions between quasi-stable brain states using unlabeled, noninvasive recordings of brain activity have been limited. This study explores the use of adaptive mixture independent component analysis (AMICA) to model multichannel electroencephalographic (EEG) data with a set of ICA models, each of which decomposes an adaptively learned portion of the data into statistically independent sources. We first show that AMICA can segment simulated quasi-stationary EEG data and accurately identify ground-truth sources and source model transitions. Next, we demonstrate that AMICA decomposition, applied to 6-13 channel scalp recordings from the CAP Sleep Database, can characterize sleep stage dynamics, allowing 75% accuracy in identifying transitions between six sleep stages without use of EEG power spectra. Finally, applied to 30-channel data from subjects in a driving simulator, AMICA identifies models that account for EEG during faster and slower response to driving challenges, respectively. We show changes in relative probabilities of these models allow effective prediction of subject response speed and moment-by-moment characterization of state changes within single trials. AMICA thus provides a generic unsupervised approach to identifying and modeling changes in EEG dynamics. Applied to continuous, unlabeled multichannel data, AMICA may likely be used to detect and study any changes in cognitive states.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme201829937148,
  title = {Intuitive Assessment of Mortality Based on Facial Characteristics: Behavioral, Electrocortical, and Machine Learning Analyses.},
  author = {Delorme, A and Pierce, A and Michel, L and Radin, D},
  journal = {Explore (New York, N.Y.)},
  year = {2018},
  doi = {10.1016/j.explore.2017.10.011},
  pmid = {29937148},
  url = {https://pubmed.ncbi.nlm.nih.gov/29937148/},
  abstract = {Studies of various characteristics of the human face indicate that it contains a wealth of information about health status. Most studies involve objective measurement of facial features as correlated with historical health information. But some individuals also claim to be adept at intuitively gauging mortality based solely upon a quick glance at a person's photograph. To test this claim, we invited 12 such individuals to see if they could tell if a person was alive or dead based solely on a brief examination of his or her photograph. All photos used in the experiment were transformed into a uniform gray scale and counterbalanced across eight categories as follows: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8seconds. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to indicate if they thought the person in a photo was living or deceased by pressing an appropriate button. Overall, mean accuracy on this task was 53.6%, where 50% was expected by chance (P = .005, two tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrocortical recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential at 100ms post-stimulus onset. We then applied machine learning techniques to classify the photographs based on 11 image characteristics; both random forest and logistic regression machine learning approaches were used, and both classifiers failed to achieve accuracy above chance level. Our results suggest that some individuals can intuitively assess mortality based on some as-yet unknown features of the face.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Gouraud201830396034,
  title = {Influence of automation on mind wandering frequency in sustained attention.},
  author = {Gouraud, J and Delorme, A and Berberian, B},
  journal = {Consciousness and cognition},
  year = {2018},
  doi = {10.1016/j.concog.2018.09.012},
  pmid = {30396034},
  url = {https://pubmed.ncbi.nlm.nih.gov/30396034/},
  abstract = {There is accumulating evidence which shows that mind wandering may be increased within automated environments. This is particularly concerning when considering the negative effect of mind wandering on short-term performance. Seventeen participants performed an obstacle avoidance task under two conditions, manual and automated, each lasting 40 min. Subjects perceived the manual condition as more demanding than the automated one. We noted a significant increase of mind wandering frequency after only approximately 20 min under the automated condition. While learning and workload alone cannot explain these results, more automation-related phenomena, such as complacency or loss of agency, could play a role. Pupil diameter decreased during mind wandering compared to focus periods, revealing a decoupling from the task. The decrease remained stable in amplitude across different times and conditions. Research on mind wandering could be used to characterize an operator's state of mind regarding issues related to system interactions.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Onton201829867419,
  title = {In-Home Sleep Recordings in Military Veterans With Posttraumatic Stress Disorder Reveal Less REM and Deep Sleep <1 Hz.},
  author = {Onton, JA and Matthews, SC and Kang, DY and Coleman, TP},
  journal = {Frontiers in human neuroscience},
  year = {2018},
  doi = {10.3389/fnhum.2018.00196},
  pmid = {29867419},
  url = {https://pubmed.ncbi.nlm.nih.gov/29867419/},
  abstract = {Veterans with posttraumatic stress disorder (PTSD) often report suboptimal sleep quality, often described as lack of restfulness for unknown reasons. These experiences are sometimes difficult to objectively quantify in sleep lab assessments. Here, we used a streamlined sleep assessment tool to record in-home 2-channel electroencephalogram (EEG) with concurrent collection of electrodermal activity (EDA) and acceleration. Data from a single forehead channel were transformed into a whole-night spectrogram, and sleep stages were classified using a fully automated algorithm. For this study, 71 control subjects and 60 military-related PTSD subjects were analyzed for percentage of time spent in Light, Hi Deep (1-3 Hz), Lo Deep (<1 Hz), and rapid eye movement (REM) sleep stages, as well as sleep efficiency and fragmentation. The results showed a significant tendency for PTSD sleepers to spend a smaller percentage of the night in REM ( p  < 0.0001) and Lo Deep ( p  = 0.001) sleep, while spending a larger percentage of the night in Hi Deep ( p  < 0.0001) sleep. The percentage of combined Hi+Lo Deep sleep did not differ between groups. All sleepers usually showed EDA peaks during Lo, but not Hi, Deep sleep; however, PTSD sleepers were more likely to lack EDA peaks altogether, which usually coincided with a lack of Lo Deep sleep. Linear regressions with all subjects showed that a decreased percentage of REM sleep in PTSD sleepers was accounted for by age, prazosin, SSRIs and SNRIs ( p  < 0.02), while decreased Lo Deep and increased Hi Deep in the PTSD group could not be accounted for by any factor in this study ( p  < 0.005). Linear regression models with only the PTSD group showed that decreased REM correlated with self-reported depression, as measured with the Depression, Anxiety, and Stress Scales (DASS;  p  < 0.00001). DASS anxiety was associated with increased REM time ( p  < 0.0001). This study shows altered sleep patterns in sleepers with PTSD that can be partially accounted for by age and medication use; however, differences in deep sleep related to PTSD could not be linked to any known factor. With several medications [prazosin, selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs);  p  < 0.03], as well as SSRIs were associated with less sleep efficiency (b = -3.3 ± 0.95;  p  = 0.0005) and more sleep fragmentation (b = -1.7 ± 0.51;  p  = 0.0009). Anti-psychotics were associated with less sleep efficiency (b = -4.9 ± 1.4;  p  = 0.0004). Sleep efficiency was negatively impacted by SSRIs, antipsychotic medications, and depression ( p  < 0.008). Increased sleep fragmentation was associated with SSRIs, SNRIs, and anxiety ( p  < 0.009), while prazosin and antipsychotic medications correlated with decreased sleep fragmentation ( p  < 0.05).},
  note = {PubMed query source: Julie Onton}
}

@article{Vieten201830403693,
  title = {Future directions in meditation research: Recommendations for expanding the field of contemplative science.},
  author = {Vieten, C and Wahbeh, H and Cahn, BR and MacLean, K and Estrada, M and Mills, P and Murphy, M and Shapiro, S and Radin, D and Josipovic, Z and Presti, DE and Sapiro, M and Chozen Bays, J and Russell, P and Vago, D and Travis, F and Walsh, R and Delorme, A},
  journal = {PloS one},
  year = {2018},
  doi = {10.1371/journal.pone.0205740},
  pmid = {30403693},
  url = {https://pubmed.ncbi.nlm.nih.gov/30403693/},
  abstract = {The science of meditation has grown tremendously in the last two decades. Most studies have focused on evaluating the clinical effectiveness of mindfulness-based interventions, neural and other physiological correlates of meditation, and individual cognitive and emotional aspects of meditation. Far less research has been conducted on more challenging domains to measure, such as group and relational, transpersonal and mystical, and difficult aspects of meditation; anomalous or extraordinary phenomena related to meditation; and post-conventional stages of development associated with meditation. However, these components of meditation may be crucial to people's psychological and spiritual development, could represent important mediators and/or mechanisms by which meditation confers benefits, and could themselves be important outcomes of meditation practices. In addition, since large numbers of novices are being introduced to meditation, it is helpful to investigate experiences they may encounter that are not well understood. Over the last four years, a task force of meditation researchers and teachers met regularly to develop recommendations for expanding the current meditation research field to include these important yet often neglected topics. These meetings led to a cross-sectional online survey to investigate the prevalence of a wide range of experiences in 1120 meditators. Results show that the majority of respondents report having had many of these anomalous and extraordinary experiences. While some of the topics are potentially controversial, they can be subjected to rigorous scientific investigation. These arenas represent largely uncharted scientific terrain and provide excellent opportunities for both new and experienced researchers. We provide suggestions for future directions, with accompanying online materials to encourage such research.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Chang201830440615,
  title = {Evaluation of Artifact Subspace Reconstruction for Automatic EEG Artifact Removal.},
  author = {Chang, CY and Hsu, SH and Pion-Tonachini, L and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512547},
  pmid = {30440615},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440615/},
  abstract = {One of the greatest challenges that hinder the decoding and application of electroencephalography (EEG) is that EEG recordings almost always contain artifacts - non-brain signals. Among existing automatic artifact-removal methods, artifact subspace reconstruction (ASR) is an online and realtime capable, component-based method that can effectively remove transient or large-amplitude artifacts. However, the effectiveness of ASR and the optimal choice of its parameter have not been evaluated and reported, especially on real EEG data. This study systematically validates ASR on ten EEG recordings in a simulated driving experiment. Independent component analysis (ICA) is applied to separate artifacts from brain signals to allow a quantitative assessment of ASR's effectiveness in removing various types of artifacts and preserving brain activities. Empirical results show that the optimal ASR parameter is between 10 and 100, which is small enough to remove activities from artifacts and eye-related components and large enough to retain signals from brain-related components. With the appropriate choice of the parameter, ASR can be a powerful and automatic artifact removal approach for offline data analysis or online real-time EEG applications such as clinical monitoring and brain-computer interfaces.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chan201830440785,
  title = {Evaluating the Performance of Non-Hair SSVEP-Based BCIs Featuring Template-Based Decoding Methods.},
  author = {Chan, WH and Chiang, KJ and Nakanishi, M and Wang, YT and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2018},
  doi = {10.1109/EMBC.2018.8512662},
  pmid = {30440785},
  url = {https://pubmed.ncbi.nlm.nih.gov/30440785/},
  abstract = {Our previous study has demonstrated the feasibility of employing non-hair-bearing electrodes to build a Steadystate Visual Evoked Potential (SSVEP)-based Brain-Computer Interface (BCI) system, relaxing technical barriers in preparation time and offering an ease-of-use apparatus. The signal quality of the SSVEPs and the resultant performance of the non-hair BCI, however, did not close upon those reported in the state-of-the-art BCI studies based on the electroencephalogram (EEG) measured from the occipital regions. Recently, advanced decoding algorithms such as task-related component analysis have made a breakthrough in enhancing the signal quality of the occipital SSVEPs and the performance of SSVEP-based BCIs in a well-controlled laboratory environment. However, it remains unclear if the advanced decoding algorithms can extract highfidelity SSVEPs from the non-hair EEG and enhance the practicality of non-hair BCIs in real-world environments. This study aims to quantitatively evaluate whether, and if so, to what extent the non-hair BCIs can leverage the state-of-art decoding algorithms. Eleven healthy individuals participated in a 5-target SSVEP BCI experiment. A high-density EEG cap recorded SSVEPs from both hair-covered and non-hair-bearing regions. By evaluating and demonstrating the accessibility of nonhair-bearing behind-ear signals, our assessment characterized constraints on data length, trial numbers, channels, and their relationships with the decoding algorithms, providing practical guidelines to optimize SSVEP-based BCI systems in real-life applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Nakanishi201828436836,
  title = {Enhancing Detection of SSVEPs for a High-Speed Brain Speller Using Task-Related Component Analysis.},
  author = {Nakanishi, M and Wang, Y and Chen, X and Wang, YT and Gao, X and Jung, TP},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2018},
  doi = {10.1109/TBME.2017.2694818},
  pmid = {28436836},
  url = {https://pubmed.ncbi.nlm.nih.gov/28436836/},
  abstract = {This study proposes and evaluates a novel data-driven spatial filtering approach for enhancing steady-state visual evoked potentials (SSVEPs) detection toward a high-speed brain-computer interface (BCI) speller. Task-related component analysis (TRCA), which can enhance reproducibility of SSVEPs across multiple trials, was employed to improve the signal-to-noise ratio (SNR) of SSVEP signals by removing background electroencephalographic (EEG) activities. An ensemble method was further developed to integrate TRCA filters corresponding to multiple stimulation frequencies. This study conducted a comparison of BCI performance between the proposed TRCA-based method and an extended canonical correlation analysis (CCA)-based method using a 40-class SSVEP dataset recorded from 12 subjects. An online BCI speller was further implemented using a cue-guided target selection task with 20 subjects and a free-spelling task with 10 of the subjects. The offline comparison results indicate that the proposed TRCA-based approach can significantly improve the classification accuracy compared with the extended CCA-based method. Furthermore, the online BCI speller achieved averaged information transfer rates (ITRs) of 325.33 ± 38.17 bits/min with the cue-guided task and 198.67 ± 50.48 bits/min with the free-spelling task. This study validated the efficiency of the proposed TRCA-based method in implementing a high-speed SSVEP-based BCI. The high-speed SSVEP-based BCIs using the TRCA method have great potential for various applications in communication and control.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{McLoughlin201829222686,
  title = {EEG Source Imaging Indices of Cognitive Control Show Associations with Dopamine System Genes.},
  author = {McLoughlin, G and Palmer, J and Makeig, S and Bigdely-Shamlo, N and Banaschewski, T and Laucht, M and Brandeis, D},
  journal = {Brain topography},
  year = {2018},
  doi = {10.1007/s10548-017-0601-z},
  pmid = {29222686},
  url = {https://pubmed.ncbi.nlm.nih.gov/29222686/},
  abstract = {Cognitive or executive control is a critical mental ability, an important marker of mental illness, and among the most heritable of neurocognitive traits. Two candidate genes, catechol-O-methyltransferase (COMT) and DRD4, which both have a roles in the regulation of cortical dopamine, have been consistently associated with cognitive control. Here, we predicted that individuals with the COMT Met/Met allele would show improved response execution and inhibition as indexed by event-related potentials in a Go/NoGo task, while individuals with the DRD4 7-repeat allele would show impaired brain activity. We used independent component analysis (ICA) to separate brain source processes contributing to high-density EEG scalp signals recorded during the task. As expected, individuals with the DRD4 7-repeat polymorphism had reduced parietal P3 source and scalp responses to response (Go) compared to those without the 7-repeat. Contrary to our expectation, the COMT homozygous Met allele was associated with a smaller frontal P3 source and scalp response to response-inhibition (NoGo) stimuli, suggesting that while more dopamine in frontal cortical areas has advantages in some tasks, it may also compromise response inhibition function. An interaction effect emerged for P3 source responses to Go stimuli. These were reduced in those with both the 7-repeat DRD4 allele and either the COMT Val/Val or the Met/Met homozygous polymorphisms but not in those with the heterozygous Val/Met polymorphism. This epistatic interaction between DRD4 and COMT replicates findings that too little or too much dopamine impairs cognitive control. The anatomic and functional separated maximally independent cortical EEG sources proved more informative than scalp channel measures for genetic studies of brain function and thus better elucidate the complex mechanisms in psychiatric illness.},
  note = {PubMed query source: Scott Makeig}
}

@article{Tanaka201829844584,
  title = {Dynamics of directional tuning and reference frames in humans: A high-density EEG study.},
  author = {Tanaka, H and Miyakoshi, M and Makeig, S},
  journal = {Scientific reports},
  year = {2018},
  doi = {10.1038/s41598-018-26609-9},
  pmid = {29844584},
  url = {https://pubmed.ncbi.nlm.nih.gov/29844584/},
  abstract = {Recent developments in EEG recording and signal processing have made it possible to record in an unconstrained, natural movement task, therefore EEG provides a promising approach to understanding the neural mechanisms of upper-limb reaching control. This study specifically addressed how EEG dynamics in the time domain encoded finger movement directions (directional tuning) and posture dependence (movement reference frames) by applying representational similarity analysis. High-density EEG covering the entire scalp was recorded while participants performed eight-directional, center-out reaching movements, thereby allowing us to explore directional selectivity of EEG sources over the brain beyond somatosensory areas. A majority of the source processes exhibited statistically significant directional tuning during peri-movement periods. In addition, directional tuning curves shifted systematically when the shoulder angle was rotated to perform the task within a more laterally positioned workspace, the degree of tuning curve rotation falling between that predicted by models assuming extrinsic and shoulder-based reference frames. We conclude that temporal dynamics of neural mechanisms for motor control can be studied noninvasively in humans using high-density EEG and that directional sensitivity of motor and non-motor processing is not limited within the sensorimotor areas but extends to the whole brain areas.},
  note = {PubMed query source: Scott Makeig}
}

@article{Szczypiski201829573379,
  title = {Dopamine dysregulation hypothesis: the common basis for motivational anhedonia in major depressive disorder and schizophrenia?},
  author = {Szczypiński, JJ and Gola, M},
  journal = {Reviews in the neurosciences},
  year = {2018},
  doi = {10.1515/revneuro-2017-0091},
  pmid = {29573379},
  url = {https://pubmed.ncbi.nlm.nih.gov/29573379/},
  abstract = {Abnormalities in reward processing are crucial symptoms of major depressive disorder (MDD) and schizophrenia (SCH). Recent neuroscientific findings regarding MDD have led to conclusions about two different symptoms related to reward processing: motivational and consummatory anhedonia, corresponding, respectively, to impaired motivation to obtain rewards ('wanting'), and diminished satisfaction from consuming them ('liking'). One can ask: which of these is common for MDD and SCH. In our review of the latest neuroscientific studies, we show that MDD and SCH do not share consummatory anhedonia, as SCH patients usually have unaltered liking. Therefore, we investigated whether motivational anhedonia is the common symptom across MDD and SCH. With regard to the similarities and differences between the neural mechanisms of MDD and SCH, here we expand the current knowledge of motivation deficits and present the common underlying mechanism of motivational anhedonia - the dopamine dysregulation hypothesis - stating that any prolonged dysregulation in tonic dopamine signaling that exceeds the given equilibrium can lead to striatal dysfunction and motivational anhedonia. The implications for further research and treatment of MDD and SCH are also discussed.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Khoshnoud201829258410,
  title = {Different cortical source activation patterns in children with attention deficit hyperactivity disorder during a time reproduction task.},
  author = {Khoshnoud, S and Shamsi, M and Nazari, MA and Makeig, S},
  journal = {Journal of clinical and experimental neuropsychology},
  year = {2018},
  doi = {10.1080/13803395.2017.1406897},
  pmid = {29258410},
  url = {https://pubmed.ncbi.nlm.nih.gov/29258410/},
  abstract = {Several neurocognitive studies have indicated that children with attention-deficit/hyperactivity disorder (ADHD) exhibit cognitive deficits in perceptual timing functions; however, only a few electroencephalographic studies have investigated their time reproduction abilities. In the present research, 15 children with ADHD were studied along with 19 age-matched control subjects (aged 7-11 years) as they attempted to reproduce shorter (1000 ms) and longer (2200 ms) time intervals. Trial-mean event-related potential (ERP) and event-related spectral perturbation measures were used to compare the electroencephalography (EEG) source-level activity patterns of the ADHD and control subjects during the time-encoding and reproduction phases. For both short and long intervals, the performance of subjects with ADHD was significantly less accurate and more variable than that of the age-matched controls. During the encoding phase, the ADHD and control ERPs differed significantly for the midfrontal source cluster. The midfrontal P300 amplitude evoked by the onset of the encoding phase was significantly higher for the ADHD group. Similarly, the amplitude of contingent negative variation for the ADHD group was lower for the midfrontal independent component (IC) cluster during long-interval encoding. Theta event-related synchronization in the right occipital cluster also differed between groups during both the encoding and reproduction phases. Moreover, children with ADHD failed to show a frontal selection positivity component in the reproduction phase. Significant differences were found in the mean alpha power for the prefrontal source cluster during the time reproduction phase. These results suggest electrophysiological evidence for time perception deficiencies, selective visual processing disturbances, and working memory impairment in children with ADHD.},
  note = {PubMed query source: Scott Makeig}
}

@article{Efrati201829787293,
  title = {Compulsive sexual behavior: A twelve-step therapeutic approach.},
  author = {Efrati, Y and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2018},
  doi = {10.1556/2006.7.2018.26},
  pmid = {29787293},
  url = {https://pubmed.ncbi.nlm.nih.gov/29787293/},
  abstract = {Background and aims Sexuality is natural to human life and inseparable from it, yet some individuals develop compulsive sexual behavior (CSB). Many individuals with CSB seek treatment in free self-support groups based on the twelve-step program. This program was extensively studied in substance abuse disorders (e.g., Alcoholics Anonymous), but little is known about its efficiency in CSB. Methods We "assesed" questionnaire data on sociodemographical-, psychological-, and recovery-related factors from 97 male participants of Sexaholics Anonymous (SA) programs in Israel. Results Our results indicated that advancement in the SA program, measured as a current step of the program, is significantly related to lower levels of sexual-related overall sense of helplessness, avoidant help-seeking, self-control, overall CSB, and sexual suppression. It is also related to the higher well-being. Discussion This is the first study to examine psychological factors of CSB recovery process in twelve-step groups, and future research is needed to replicate our results within a longitudinal study.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Delorme201830344471,
  title = {Briefly Flashed Scenes Can Be Stored in Long-Term Memory.},
  author = {Delorme, A and Poncet, M and Fabre-Thorpe, M},
  journal = {Frontiers in neuroscience},
  year = {2018},
  doi = {10.3389/fnins.2018.00688},
  pmid = {30344471},
  url = {https://pubmed.ncbi.nlm.nih.gov/30344471/},
  abstract = {The capacity of human memory is impressive. Previous reports have shown that when asked to memorize images, participants can recognize several thousands of visual objects in great details even with a single viewing of a few seconds per image. In this experiment, we tested recognition performance for natural scenes that participants saw for 20 ms only once (untrained group) or 22 times over many days (trained group) in an unrelated task. 400 images (200 previously viewed and 200 novel images) were flashed one at a time and participants were asked to lift their finger from a pad whenever they thought they had already seen the image (go/no-go paradigm). Compared to previous reports of excellent recognition performance with only single presentations of a few seconds, untrained participants were able to recognize only 64% of the 200 images they had seen few minutes before. On the other hand, trained participants, who had processed the flashed images (20 ms) several times, could correctly recognize 89% of them. EEG recordings confirmed these behavioral results. As early as 230 ms after stimulus onset, a significant event-related-potential (ERP) difference between familiar and new images was observed for the trained but not for the untrained group. These results show that briefly flashed unmasked scenes can be incidentally stored in long-term memory when repeated.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Papp201830605268,
  title = {Brain Zaps: An Underappreciated Symptom of Antidepressant Discontinuation.},
  author = {Papp, A and Onton, JA},
  journal = {The primary care companion for CNS disorders},
  year = {2018},
  doi = {10.4088/PCC.18m02311},
  pmid = {30605268},
  url = {https://pubmed.ncbi.nlm.nih.gov/30605268/},
  abstract = {To describe the characteristics of the electrical phenomena of antidepressant discontinuation syndrome known as brain zaps and their effect on quality of life. We examined 595 unsolicited posts made by individuals frequenting a popular lay mental health website. The site was accessed between December 13, 2014, and December 12, 2016, and its content was saved in a text document. The posts had been accumulating on the site since December 2014. These posts were analyzed and separated into 648 separate statements regarding antidepressant intake. Of the statements, 378 contained reference to symptoms experienced in the context of antidepressant discontinuation. These posts were further analyzed for specifics of the medications involved, temporal characteristics of the medication intake, associated symptoms, specifics of the "zap" experience itself, and effect of the zaps on quality of life. As this was a convenience sample, only qualitative analysis was performed. Venlafaxine and paroxetine were reported more frequently, and fluoxetine less frequently, in the sample compared to their frequency of prescription in clinical practice. This finding mirrors the frequency distribution of all withdrawal effects versus antidepressant prescriptions written as reported in the literature. The most likely cause of brain zaps was abrupt discontinuation of the medication, but gradual tapering had only a partial mitigating effect. An unexpected finding was the frequent association of brain zaps with lateral eye movements. The presence of brain zaps was typically transitory, but in a small number of cases it caused significant disability lasting for months or years with no treatment available. Patients' inability to obtain effective help from prescribers and the perceived lack of interest in this symptom on the part of the medical profession risks fueling antipsychiatry attitudes among patients. Brain zaps are a poorly understood symptom of antidepressant discontinuation, which require further study for both better prevention and treatment. The apparent association of brain zaps with lateral eye movements may open avenues for investigation of this process.},
  note = {PubMed query source: Julie Onton}
}

@article{Fonseca201830483080,
  title = {Brain Network Changes in Fatigued Drivers: A Longitudinal Study in a Real-World Environment Based on the Effective Connectivity Analysis and Actigraphy Data.},
  author = {Fonseca, A and Kerick, S and King, JT and Lin, CT and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2018},
  doi = {10.3389/fnhum.2018.00418},
  pmid = {30483080},
  url = {https://pubmed.ncbi.nlm.nih.gov/30483080/},
  abstract = {The analysis of neurophysiological changes during driving can clarify the mechanisms of fatigue, considered an important cause of vehicle accidents. The fluctuations in alertness can be investigated as changes in the brain network connections, reflected in the direction and magnitude of the information transferred. Those changes are induced not only by the time on task but also by the quality of sleep. In an unprecedented 5-month longitudinal study, daily sampling actigraphy and EEG data were collected during a sustained-attention driving task within a near-real-world environment. Using a performance index associated with the subjects' reaction times and a predictive score related to the sleep quality, we identify fatigue levels in drivers and investigate the shifts in their effective connectivity in different frequency bands, through the analysis of the dynamical coupling between brain areas. Study results support the hypothesis that combining EEG, behavioral and actigraphy data can reveal new features of the decline in alertness. In addition, the use of directed measures such as the Convergent Cross Mapping can contribute to the development of fatigue countermeasure devices.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Artoni201829526744,
  title = {Applying dimension reduction to EEG data by Principal Component Analysis reduces the quality of its subsequent Independent Component decomposition.},
  author = {Artoni, F and Delorme, A and Makeig, S},
  journal = {NeuroImage},
  year = {2018},
  doi = {10.1016/j.neuroimage.2018.03.016},
  pmid = {29526744},
  url = {https://pubmed.ncbi.nlm.nih.gov/29526744/},
  abstract = {Independent Component Analysis (ICA) has proven to be an effective data driven method for analyzing EEG data, separating signals from temporally and functionally independent brain and non-brain source processes and thereby increasing their definition. Dimension reduction by Principal Component Analysis (PCA) has often been recommended before ICA decomposition of EEG data, both to minimize the amount of required data and computation time. Here we compared ICA decompositions of fourteen 72-channel single subject EEG data sets obtained (i) after applying preliminary dimension reduction by PCA, (ii) after applying no such dimension reduction, or else (iii) applying PCA only. Reducing the data rank by PCA (even to remove only 1% of data variance) adversely affected both the numbers of dipolar independent components (ICs) and their stability under repeated decomposition. For example, decomposing a principal subspace retaining 95% of original data variance reduced the mean number of recovered 'dipolar' ICs from 30 to 10 per data set and reduced median IC stability from 90% to 76%. PCA rank reduction also decreased the numbers of near-equivalent ICs across subjects. For instance, decomposing a principal subspace retaining 95% of data variance reduced the number of subjects represented in an IC cluster accounting for frontal midline theta activity from 11 to 5. PCA rank reduction also increased uncertainty in the equivalent dipole positions and spectra of the IC brain effective sources. These results suggest that when applying ICA decomposition to EEG data, PCA rank reduction should best be avoided.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wei201829578026,
  title = {A subject-transfer framework for obviating inter- and intra-subject variability in EEG-based drowsiness detection.},
  author = {Wei, CS and Lin, YP and Wang, YT and Lin, CT and Jung, TP},
  journal = {NeuroImage},
  year = {2018},
  doi = {10.1016/j.neuroimage.2018.03.032},
  pmid = {29578026},
  url = {https://pubmed.ncbi.nlm.nih.gov/29578026/},
  abstract = {Inter- and intra-subject variability pose a major challenge to decoding human brain activity in brain-computer interfaces (BCIs) based on non-invasive electroencephalogram (EEG). Conventionally, a time-consuming and laborious training procedure is performed on each new user to collect sufficient individualized data, hindering the applications of BCIs on monitoring brain states (e.g. drowsiness) in real-world settings. This study proposes applying hierarchical clustering to assess the inter- and intra-subject variability within a large-scale dataset of EEG collected in a simulated driving task, and validates the feasibility of transferring EEG-based drowsiness-detection models across subjects. A subject-transfer framework is thus developed for detecting drowsiness based on a large-scale model pool from other subjects and a small amount of alert baseline calibration data from a new user. The model pool ensures the availability of positive model transferring, whereas the alert baseline data serve as a selector of decoding models in the pool. Compared with the conventional within-subject approach, the proposed framework remarkably reduced the required calibration time for a new user by 90% (18.00 min-1.72 ± 0.36 min) without compromising performance (p = 0.0910) when sufficient existing data are available. These findings suggest a practical pathway toward plug-and-play drowsiness detection and can ignite numerous real-world BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Xu201829683431,
  title = {A Brain-Computer Interface Based on Miniature-Event-Related Potentials Induced by Very Small Lateral Visual Stimuli.},
  author = {Xu, M and Xiao, X and Wang, Y and Qi, H and Jung, TP and Ming, D},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2018},
  doi = {10.1109/TBME.2018.2799661},
  pmid = {29683431},
  url = {https://pubmed.ncbi.nlm.nih.gov/29683431/},
  abstract = {Traditional visual brain-computer interfaces (BCIs) preferred to use large-size stimuli to attract the user's attention and elicit distinct electroencephalography (EEG) features. However, the visual stimuli are of no interest to the users as they just serve as the hidden codes behind the characters. Furthermore, using stronger visual stimuli could cause visual fatigue and other adverse symptoms to users. Therefore, it's imperative for visual BCIs to use small and inconspicuous visual stimuli to code characters. This study developed a new BCI speller based on miniature asymmetric visual evoked potentials (aVEPs), which encodes 32 characters with a space-code division multiple access scheme and decodes EEG features with a discriminative canonical pattern matching algorithm. Notably, the visual stimulus used in this study only subtended 0.5° of visual angle and was placed outside the fovea vision on the lateral side, which could only induce a miniature potential about 0.5 μV in amplitude and about 16.5 dB in signal-to-noise rate. A total of 12 subjects were recruited to use the miniature aVEP speller in both offline and online tests. Information transfer rates up to 63.33 b/min could be achieved from online tests (online demo URL: https://www.youtube.com/edit?o=U&video_id=kC7btB3mvGY ). Experimental results demonstrate the feasibility of using very small and inconspicuous visual stimuli to implement an efficient BCI system, even though the elicited EEG features are very weak. The proposed innovative technique can broaden the category of BCIs and strengthen the brain-computer communication.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wordecha201829865868,
  title = {"Pornographic binges" as a key characteristic of males seeking treatment for compulsive sexual behaviors: Qualitative and quantitative 10-week-long diary assessment.},
  author = {Wordecha, M and Wilk, M and Kowalewska, E and Skorko, M and Łapiński, A and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2018},
  doi = {10.1556/2006.7.2018.33},
  pmid = {29865868},
  url = {https://pubmed.ncbi.nlm.nih.gov/29865868/},
  abstract = {Background and aims Compulsive sexual behaviors (CSBs) are an important clinical and social issue. Despite the increasing number of studies, some of CSB's aspects remain under-investigated. Here, we explore the nature of CSB, such as binge pornography use and masturbation (PuM), and verify the correspondence between self-perceived factors leading to such behavior with its measures obtained in a diary assessment. Methods Semi-structuralized interviews with nine treatment-seeking males aged 22-37 years (M = 31.7, SD = 4.85) were followed by a questionnaire and a 10-week-long diary assessment, allowing us to acquire real-life daily patterns of CSB. Results Six out of nine subjects experienced binge (multiple hours or times a day) PuM. All subjects presented a high level of anxiety and perceived PuM as a way to regulate mood and stress. Data collected in the diary assessment uncovered a high diversity in the patterns of sexual behaviors (such as frequency of regular and binge PuM) and its correlates. Binge PuM was related to decreased mood and/or increased stress or anxiety. The causal relation between these correlates remains undetermined. Discussion and conclusions Binge PuM seems to be one of the most characteristic behavior among males who are seeking treatment for CSB and is related to the feeling of losing control over one's sexual activity. CSB individuals indicate a variety of binge triggers. Also, diary assessment data indicate that specific correlates of binge PuM (decreased mood, increased stress, and anxiety) differ between subjects. It suggests the existence of significant individual differences in binge PuM behaviors, and a need to study these differences, as it may help guide personalized treatment.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Carrier201728792563,
  title = {[Initiating an antipsychotic drug treatment for schizophrenia: the situation in Quebec, Canada, from 1998 to 2006].},
  author = {Carrier, JD and Blais, L and Cohen, A and Courteau, J and Roberge, P and Larouche, A and Grignon, S and Fleury, MJ and Lesage, A and Demers, MF and Roy, MA and Delorme, A and Vanasse, A},
  journal = {Sante mentale au Quebec},
  year = {2017},
  pmid = {28792563},
  url = {https://pubmed.ncbi.nlm.nih.gov/28792563/},
  abstract = {Objectives To describe factors associated with the following characteristics of the first prescription of an antipsychotic drug treatment (ADT): 1) prescribing physician type (psychiatrist vs. general practitioner); 2) second-generation vs. first-generation antipsychotic drug; 3) in conjunction with at least one additional antipsychotic drug (multitherapy); 4) never renewed by the patient.Methods This is a pharmacoepidemiologic study using administrative data from the Régie de l'assurance maladie du Québec (RAMQ), the public healthcare insurer in Quebec, Canada. Available data sample was exhaustive for adults with a diagnosis of schizophrenia who received an ADT under RAMQ drug coverage from 1998 to 2006. We report multiple logistic regression results.Results Among 16,225 patients who met inclusion criteria 46.2% were women and 70% were beneficiaries of governmental financial assistance. Patients who had their ADT prescribed by psychiatrists tended to be younger and were more burdened by their mental illness. Multitherapy was associated with hospitalization with a psychotic disorder as main diagnosis, lower socioeconomic status, and age between 35 and 64. Second-generation antipsychotic use became progressively more prominent during the period under study. Antipsychotic non renewal was correlated with substance use disorders and was less likely to happen following hospitalization with a psychiatric main diagnosis. Conclusions Although this study is subject to the intrinsic limitations of secondary analysis of administrative data, the database available for study was exhaustive within the Quebec healthcare system and included data from both general practice and specialized care, which allowed us to draw a relevant picture of how ADT were initiated for schizophrenia in Quebec, Canada, from 1998 to 2006. This timeframe is especially relevant since the 1990s were marked by the introduction of second-generation antipsychotics in Canada.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Artoni201728782683,
  title = {Unidirectional brain to muscle connectivity reveals motor cortex control of leg muscles during stereotyped walking.},
  author = {Artoni, F and Fanciullacci, C and Bertolucci, F and Panarese, A and Makeig, S and Micera, S and Chisari, C},
  journal = {NeuroImage},
  year = {2017},
  doi = {10.1016/j.neuroimage.2017.07.013},
  pmid = {28782683},
  url = {https://pubmed.ncbi.nlm.nih.gov/28782683/},
  abstract = {In lower mammals, locomotion seems to be mainly regulated by subcortical and spinal networks. On the contrary, recent evidence suggests that in humans the motor cortex is also significantly engaged during complex locomotion tasks. However, a detailed understanding of cortical contribution to locomotion is still lacking especially during stereotyped activities. Here, we show that cortical motor areas finely control leg muscle activation during treadmill stereotyped walking. Using a novel technique based on a combination of Reliable Independent Component Analysis, source localization and effective connectivity, and by combining electroencephalographic (EEG) and electromyographic (EMG) recordings in able-bodied adults we were able to examine for the first time cortical activation patterns and cortico-muscular connectivity including information flow direction. Results not only provided evidence of cortical activity associated with locomotion, but demonstrated significant causal unidirectional drive from contralateral motor cortex to muscles in the swing leg. These insights overturn the traditional view that human cortex has a limited role in the control of stereotyped locomotion, and suggest useful hypotheses concerning mechanisms underlying gait under other conditions. Motor cortex proactively drives contralateral swing leg muscles during treadmill walking, counter to the traditional view of stereotyped human locomotion.},
  note = {PubMed query source: Scott Makeig}
}

@article{Tllner201728137968,
  title = {Two Independent Frontal Midline Theta Oscillations during Conflict Detection and Adaptation in a Simon-Type Manual Reaching Task.},
  author = {Töllner, T and Wang, Y and Makeig, S and Müller, HJ and Jung, TP and Gramann, K},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2017},
  doi = {10.1523/JNEUROSCI.1752-16.2017},
  pmid = {28137968},
  url = {https://pubmed.ncbi.nlm.nih.gov/28137968/},
  abstract = {One of the most firmly established factors determining the speed of human behavioral responses toward action-critical stimuli is the spatial correspondence between the stimulus and response locations. If both locations match, the time taken for response production is markedly reduced relative to when they mismatch, a phenomenon called the Simon effect. While there is a consensus that this stimulus-response (S-R) conflict is associated with brief (4-7 Hz) frontal midline theta (fmθ) complexes generated in medial frontal cortex, it remains controversial (1) whether there are multiple, simultaneously active theta generator areas in the medial frontal cortex that commonly give rise to conflict-related fmθ complexes; and if so, (2) whether they are all related to the resolution of conflicting task information. Here, we combined mental chronometry with high-density electroencephalographic measures during a Simon-type manual reaching task and used independent component analysis and time-frequency domain statistics on source-level activities to model fmθ sources. During target processing, our results revealed two independent fmθ generators simultaneously active in or near anterior cingulate cortex, only one of them reflecting the correspondence between current and previous S-R locations. However, this fmθ response is not exclusively linked to conflict but also to other, conflict-independent processes associated with response slowing. These results paint a detailed picture regarding the oscillatory correlates of conflict processing in Simon tasks, and challenge the prevalent notion that fmθ complexes induced by conflicting task information represent a unitary phenomenon related to cognitive control, which governs conflict processing across various types of response-override tasks. SIGNIFICANCE STATEMENT  Humans constantly monitor their environment for and adjust their cognitive control settings in response to conflicts, an ability that arguably paves the way for survival in ever-changing situations. Anterior cingulate-generated frontal midline theta (fmθ) complexes have been hypothesized to play a role in this conflict-monitoring function. However, it remains a point of contention whether fmθ complexes govern conflict processing in a unitary, paradigm-nonspecific manner. Here, we identified two independent fmθ oscillations triggered during a Simon-type task, only one of them reflecting current and previous conflicts. Importantly, this signal differed in various respects (cortical origin, intertrial history) from fmθ phenomena in other response-override tasks, challenging the prevalent notion of conflict-induced fmθ as a unitary phenomenon associated with the resolution of conflict.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lewczuk201729034717,
  title = {Treatment seeking for problematic pornography use among women.},
  author = {Lewczuk, K and Szmyd, J and Skorko, M and Gola, M},
  journal = {Journal of behavioral addictions},
  year = {2017},
  doi = {10.1556/2006.6.2017.063},
  pmid = {29034717},
  url = {https://pubmed.ncbi.nlm.nih.gov/29034717/},
  abstract = {Background and aims Previous studies examined psychological factors related to treatment seeking for problematic pornography use (PU) among males. In this study, we focused on females who seek treatment for problematic PU and compared them with non-problematic pornography users with regard to variables related to problematic PU. Second, we investigated the relationships between critical constructs related to problematic PU with the path analysis method, emphasizing the predictors for treatment seeking among women. We also compared our results with previous studies on males. Methods A survey study was conducted on 719 Polish-speaking Caucasian females, 14-63 years old, including 39 treatment seekers for problematic PU. Results The positive relationship between the mere amount of PU and treatment seeking loses its significance after introducing two other predictors of treatment-seeking: religiosity and negative symptoms associated with PU. This pattern is different from the results obtained in previous studies on males. Discussion Different from previous studies on male samples, our analysis showed that in the case of women, mere amount of PU may be related to treatment-seeking behavior even after accounting for negative symptoms associated with PU. Moreover, religiousness is a significant predictor of treatment seeking among women, which may indicate that in the case of women, treatment seeking for problematic PU is motivated not only by experienced negative symptoms of PU but also by personal beliefs about PU and social norms. Conclusion For females, negative symptoms associated with PU, the amount of PU and religiosity is associated with treatment seeking. Those factors should be considered in treatment.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Ko201728824396,
  title = {Sustained Attention in Real Classroom Settings: An EEG Study.},
  author = {Ko, LW and Komarov, O and Hairston, WD and Jung, TP and Lin, CT},
  journal = {Frontiers in human neuroscience},
  year = {2017},
  doi = {10.3389/fnhum.2017.00388},
  pmid = {28824396},
  url = {https://pubmed.ncbi.nlm.nih.gov/28824396/},
  abstract = {Sustained attention is a process that enables the maintenance of response persistence and continuous effort over extended periods of time. Performing attention-related tasks in real life involves the need to ignore a variety of distractions and inhibit attention shifts to irrelevant activities. This study investigates electroencephalography (EEG) spectral changes during a sustained attention task within a real classroom environment. Eighteen healthy students were instructed to recognize as fast as possible special visual targets that were displayed during regular university lectures. Sorting their EEG spectra with respect to response times, which indicated the level of visual alertness to randomly introduced visual stimuli, revealed significant changes in the brain oscillation patterns. The results of power-frequency analysis demonstrated a relationship between variations in the EEG spectral dynamics and impaired performance in the sustained attention task. Across subjects and sessions, prolongation of the response time was preceded by an increase in the delta and theta EEG powers over the occipital region, and decrease in the beta power over the occipital and temporal regions. Meanwhile, implementation of the complex attention task paradigm into a real-world classroom setting makes it possible to investigate specific mutual links between brain activities and factors that cause impaired behavioral performance, such as development and manifestation of classroom mental fatigue. The findings of the study set a basis for developing a system capable of estimating the level of visual attention during real classroom activities by monitoring changes in the EEG spectra.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{FeldmannWstefeld201729216195,
  title = {Reduced visual attention in heterogeneous textures is reflected in occipital alpha and theta band activity.},
  author = {Feldmann-Wüstefeld, T and Miyakoshi, M and Petilli, MA and Schubö, A and Makeig, S},
  journal = {PloS one},
  year = {2017},
  doi = {10.1371/journal.pone.0187763},
  pmid = {29216195},
  url = {https://pubmed.ncbi.nlm.nih.gov/29216195/},
  abstract = {Increasing context heterogeneity has been found to reduce attention deployment towards an embedded target item. Heterogeneity in visual search tasks is typically induced by segmenting the background into several perceptual groups. In the present study, however, context heterogeneity was induced by varying whole-field heterogeneity, i.e., the degree of distractor variability within the entire context. This allowed us to (i) more gradually vary context heterogeneity, and (ii) investigate attention deployment on a whole-field scale. Results showed that both search performance and amplitude of the N2pc (lateralized ERP; posterior contralateral negativity in the N2 range) monotonically decreased with increasing context heterogeneity, which confirmed that there was less efficient attention deployment for more heterogeneous contexts. The amplitude of the bilateral N2 exhibited a U-shaped function, suggesting global perception for the lowest and highest levels of heterogeneity, but local processing for intermediate heterogeneity levels. Independent component analyses revealed an occipital ERP-contributing effective source cluster that may reflect stimulus representations on a saliency map. With increasing heterogeneity, these sources exhibited more theta band activity for distractors and less theta band activity for targets. Alpha band activity of a second component cluster varied with heterogeneity level, and low-theta/delta activity of a third source cluster distinguished target presence versus absence. In sum, our results suggest that independent brain sources contributed to the differential processing of heterogeneous versus homogeneous contexts.},
  note = {PubMed query source: Scott Makeig}
}

@article{Chien201728000607,
  title = {Polychromatic SSVEP stimuli with subtle flickering adapted to brain-display interactions.},
  author = {Chien, YY and Lin, FC and Zao, JK and Chou, CC and Huang, YP and Kuo, HY and Wang, Y and Jung, TP and Shieh, HD},
  journal = {Journal of neural engineering},
  year = {2017},
  doi = {10.1088/1741-2552/aa550d},
  pmid = {28000607},
  url = {https://pubmed.ncbi.nlm.nih.gov/28000607/},
  abstract = {Interactive displays armed with natural user interfaces (NUIs) will likely lead the next breakthrough in consumer electronics, and brain-computer interfaces (BCIs) are often regarded as the ultimate NUI-enabling machines to respond to human emotions and mental states. Steady-state visual evoked potentials (SSVEPs) are a commonly used BCI modality due to the ease of detection and high information transfer rates. However, the presence of flickering stimuli may cause user discomfort and can even induce migraines and seizures. With the aim of designing visual stimuli that can be embedded into video images, this study developed a novel approach to induce detectable SSVEPs using a composition of red/green/blue flickering lights. Based on the opponent theory of colour vision, this study used 32 Hz/40 Hz rectangular red-green or red-blue LED light pulses with a 50% duty cycle, balanced/equal luminance and 0°/180° phase shifts as the stimulating light sources and tested their efficacy in producing SSVEP responses with high signal-to-noise ratios (SNRs) while reducing the perceived flickering sensation. The empirical results from ten healthy subjects showed that dual-colour lights flickering at 32 Hz/40 Hz with a 50% duty cycle and 180° phase shift achieved a greater than 90% detection accuracy with little or no flickering sensation. As a first step in developing an embedded SSVEP stimulus in commercial displays, this study provides a foundation for developing a combination of three primary colour flickering backlights with adjustable luminance proportions to create a subtle flickering polychromatic light that can elicit SSVEPs at the basic flickering frequency.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gola201728455898,
  title = {Polish adaptation of Sexual Addiction Screening Test - Revised.},
  author = {Gola, M and Skorko, M and Kowalewska, E and Kołodziej, A and Sikora, M and Wodyk, M and Wodyk, Z and Dobrowolski, P},
  journal = {Psychiatria polska},
  year = {2017},
  doi = {10.12740/PP/OnlineFirst/61414},
  pmid = {28455898},
  url = {https://pubmed.ncbi.nlm.nih.gov/28455898/},
  abstract = {Addictive sexual behaviours are gaining more and more attention from researchers. There are actually 25 different questionnaires for assessing the level of loss of control over sexual. The main aim of this work was to make such an adaptation of the Sexual Addiction Screening Test-Revised (SAST-R; the most popular and questionnaire). behaviours (LoCoSB). None of them have been adapted and validated in a Polish language version. For the purpose of psychometric features examination and validation of the Polish version of SAST-R (SAST-PL-M), we recruited 116 heterosexual men receiving psychological treatment due to LoCoSB and meeting the criteria for hypersexual disorder. The control group consisted of 442 heterosexual males having never looked for any psychological or psychiatric help due to LoCoSB. SAST-PL-M has high reliability (Cronbach's alpha = 0.904) and good filtering characteristics for identification of people who are potentially experiencing difficulty with control over sexual behaviours (the ROC curve for a threshold of 5 out of a maximum 20 points is characterised by a sensitivity of 99.1% and a specificity of 78.3%). SAST-PL-M can be used as an efficient screening test for symptoms of LoCoSB in clinical and research setups. Results below 5 points indicate a high probability of no problems, while more than 5 points can indicate the need for additional clinical interviews. SAST-PL-M results may be successfully referred to the results of SAST-R when used with heterosexual male populations for research purposes.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Somon201728744209,
  title = {Performance Monitoring Applied to System Supervision.},
  author = {Somon, B and Campagne, A and Delorme, A and Berberian, B},
  journal = {Frontiers in human neuroscience},
  year = {2017},
  doi = {10.3389/fnhum.2017.00360},
  pmid = {28744209},
  url = {https://pubmed.ncbi.nlm.nih.gov/28744209/},
  abstract = {Nowadays, automation is present in every aspect of our daily life and has some benefits. Nonetheless, empirical data suggest that traditional automation has many negative performance and safety consequences as it changed task performers into task supervisors. In this context, we propose to use recent insights into the anatomical and neurophysiological substrates of action monitoring in humans, to help further characterize performance monitoring during system supervision. Error monitoring is critical for humans to learn from the consequences of their actions. A wide variety of studies have shown that the error monitoring system is involved not only in our own errors, but also in the errors of others. We hypothesize that the neurobiological correlates of the self-performance monitoring activity can be applied to system supervision. At a larger scale, a better understanding of system supervision may allow its negative effects to be anticipated or even countered. This review is divided into three main parts. First, we assess the neurophysiological correlates of self-performance monitoring and their characteristics during error execution. Then, we extend these results to include performance monitoring and error observation of others or of systems. Finally, we provide further directions in the study of system supervision and assess the limits preventing us from studying a well-known phenomenon: the Out-Of-the-Loop (OOL) performance problem.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Hsu201728627505,
  title = {Monitoring alert and drowsy states by modeling EEG source nonstationarity.},
  author = {Hsu, SH and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2017},
  doi = {10.1088/1741-2552/aa7a25},
  pmid = {28627505},
  url = {https://pubmed.ncbi.nlm.nih.gov/28627505/},
  abstract = {As a human brain performs various cognitive functions within ever-changing environments, states of the brain characterized by recorded brain activities such as electroencephalogram (EEG) are inevitably nonstationary. The challenges of analyzing the nonstationary EEG signals include finding neurocognitive sources that underlie different brain states and using EEG data to quantitatively assess the state changes. This study hypothesizes that brain activities under different states, e.g. levels of alertness, can be modeled as distinct compositions of statistically independent sources using independent component analysis (ICA). This study presents a framework to quantitatively assess the EEG source nonstationarity and estimate levels of alertness. The framework was tested against EEG data collected from 10 subjects performing a sustained-attention task in a driving simulator. Empirical results illustrate that EEG signals under alert versus drowsy states, indexed by reaction speeds to driving challenges, can be characterized by distinct ICA models. By quantifying the goodness-of-fit of each ICA model to the EEG data using the model deviation index (MDI), we found that MDIs were significantly correlated with the reaction speeds (r  =  -0.390 with alertness models and r  =  0.449 with drowsiness models) and the opposite correlations indicated that the two models accounted for sources in the alert and drowsy states, respectively. Based on the observed source nonstationarity, this study also proposes an online framework using a subject-specific ICA model trained with an initial (alert) state to track the level of alertness. For classification of alert against drowsy states, the proposed online framework achieved an averaged area-under-curve of 0.745 and compared favorably with a classic power-based approach. This ICA-based framework provides a new way to study changes of brain states and can be applied to monitoring cognitive or mental states of human operators in attention-critical settings or in passive brain-computer interfaces.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Perez201728139679,
  title = {Mismatch Negativity is a Sensitive and Predictive Biomarker of Perceptual Learning During Auditory Cognitive Training in Schizophrenia.},
  author = {Perez, VB and Tarasenko, M and Miyakoshi, M and Pianka, ST and Makeig, SD and Braff, DL and Swerdlow, NR and Light, GA},
  journal = {Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology},
  year = {2017},
  doi = {10.1038/npp.2017.25},
  pmid = {28139679},
  url = {https://pubmed.ncbi.nlm.nih.gov/28139679/},
  abstract = {Computerized cognitive training is gaining empirical support for use in the treatment of schizophrenia (SZ). Although cognitive training is efficacious for SZ at a group level when delivered in sufficiently intensive doses (eg, 30-50 h), there is variability in individual patient response. The identification of biomarkers sensitive to the neural systems engaged by cognitive training interventions early in the course of treatment could facilitate personalized assignment to treatment. This proof-of-concept study was conducted to determine whether mismatch negativity (MMN), an event-related potential index of auditory sensory discrimination associated with cognitive and psychosocial functioning, would predict gains in auditory perceptual learning and exhibit malleability after initial exposure to the early stages of auditory cognitive training in SZ. MMN was assessed in N=28 SZ patients immediately before and after completing 1 h of a speeded time-order judgment task of two successive frequency-modulated sweeps (Posit Science 'Sound Sweeps' exercise). All SZ patients exhibited the expected improvements in auditory perceptual learning over the 1 h training period (p<0.001), consistent with previous results. Larger MMN amplitudes recorded both before and after the training exercises were associated with greater gains in auditory perceptual learning (r=-0.5 and r=-0.67, respectively, p's<0.01). Significant pretraining vs posttraining MMN amplitude reduction was also observed (p<0.02). MMN is a sensitive index of the neural systems engaged in a single session of auditory cognitive training in SZ. These findings encourage future trials of MMN as a biomarker for individual assignment, prediction, and/or monitoring of patient response to procognitive interventions, including auditory cognitive training in SZ.},
  note = {PubMed query source: Scott Makeig}
}

@article{Potenza201728853408,
  title = {Is excessive sexual behaviour an addictive disorder?},
  author = {Potenza, MN and Gola, M and Voon, V and Kor, A and Kraus, SW},
  journal = {The lancet. Psychiatry},
  year = {2017},
  doi = {10.1016/S2215-0366(17)30316-4},
  pmid = {28853408},
  url = {https://pubmed.ncbi.nlm.nih.gov/28853408/},
  note = {PubMed query source: Mateusz Gola}
}

@article{Braboszcz201728118405,
  title = {Increased Gamma Brainwave Amplitude Compared to Control in Three Different Meditation Traditions.},
  author = {Braboszcz, C and Cahn, BR and Levy, J and Fernandez, M and Delorme, A},
  journal = {PloS one},
  year = {2017},
  doi = {10.1371/journal.pone.0170647},
  pmid = {28118405},
  url = {https://pubmed.ncbi.nlm.nih.gov/28118405/},
  abstract = {Despite decades of research, effects of different types of meditation on electroencephalographic (EEG) activity are still being defined. We compared practitioners of three different meditation traditions (Vipassana, Himalayan Yoga and Isha Shoonya) with a control group during a meditative and instructed mind-wandering (IMW) block. All meditators showed higher parieto-occipital 60-110 Hz gamma amplitude than control subjects as a trait effect observed during meditation and when considering meditation and IMW periods together. Moreover, this gamma power was positively correlated with participants meditation experience. Independent component analysis was used to show that gamma activity did not originate in eye or muscle artifacts. In addition, we observed higher 7-11 Hz alpha activity in the Vipassana group compared to all the other groups during both meditation and instructed mind wandering and lower 10-11 Hz activity in the Himalayan yoga group during meditation only. We showed that meditation practice is correlated to changes in the EEG gamma frequency range that are common to a variety of meditation practices.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lin201728701938,
  title = {Improving EEG-Based Emotion Classification Using Conditional Transfer Learning.},
  author = {Lin, YP and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2017},
  doi = {10.3389/fnhum.2017.00334},
  pmid = {28701938},
  url = {https://pubmed.ncbi.nlm.nih.gov/28701938/},
  abstract = {To overcome the individual differences, an accurate electroencephalogram (EEG)-based emotion-classification system requires a considerable amount of ecological calibration data for each individual, which is labor-intensive and time-consuming. Transfer learning (TL) has drawn increasing attention in the field of EEG signal mining in recent years. The TL leverages existing data collected from other people to build a model for a new individual with little calibration data. However, brute-force transfer to an individual (i.e., blindly leveraged the labeled data from others) may lead to a negative transfer that degrades performance rather than improving it. This study thus proposed a conditional TL (cTL) framework to facilitate a positive transfer (improving subject-specific performance without increasing the labeled data) for each individual. The cTL first assesses an individual's transferability for positive transfer and then selectively leverages the data from others with comparable feature spaces. The empirical results showed that among 26 individuals, the proposed cTL framework identified 16 and 14 transferable individuals who could benefit from the data from others for emotion valence and arousal classification, respectively. These transferable individuals could then leverage the data from 18 and 12 individuals who had similar EEG signatures to attain maximal TL improvements in valence- and arousal-classification accuracy. The cTL improved the overall classification performance of 26 individuals by ~15% for valence categorization and ~12% for arousal counterpart, as compared to their default performance based solely on the subject-specific data. This study evidently demonstrated the feasibility of the proposed cTL framework for improving an individual's default emotion-classification performance given a data repository. The cTL framework may shed light on the development of a robust emotion-classification model using fewer labeled subject-specific data toward a real-life affective brain-computer interface (ABCI).},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Rajagopalan201729104256,
  title = {Fall Prediction and Prevention Systems: Recent Trends, Challenges, and Future Research Directions.},
  author = {Rajagopalan, R and Litvan, I and Jung, TP},
  journal = {Sensors (Basel, Switzerland)},
  year = {2017},
  doi = {10.3390/s17112509},
  pmid = {29104256},
  url = {https://pubmed.ncbi.nlm.nih.gov/29104256/},
  abstract = {Fall prediction is a multifaceted problem that involves complex interactions between physiological, behavioral, and environmental factors. Existing fall detection and prediction systems mainly focus on physiological factors such as gait, vision, and cognition, and do not address the multifactorial nature of falls. In addition, these systems lack efficient user interfaces and feedback for preventing future falls. Recent advances in internet of things (IoT) and mobile technologies offer ample opportunities for integrating contextual information about patient behavior and environment along with physiological health data for predicting falls. This article reviews the state-of-the-art in fall detection and prediction systems. It also describes the challenges, limitations, and future directions in the design and implementation of effective fall prediction and prevention systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu201728463203,
  title = {EEG-Based User Reaction Time Estimation Using Riemannian Geometry Features.},
  author = {Wu, D and Lance, BJ and Lawhern, VJ and Gordon, S and Jung, TP and Lin, CT},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2017},
  doi = {10.1109/TNSRE.2017.2699784},
  pmid = {28463203},
  url = {https://pubmed.ncbi.nlm.nih.gov/28463203/},
  abstract = {Riemannian geometry has been successfully used in many brain-computer interface (BCI) classification problems and demonstrated superior performance. In this paper, for the first time, it is applied to BCI regression problems, an important category of BCI applications. More specifically, we propose a new feature extraction approach for electroencephalogram (EEG)-based BCI regression problems: a spatial filter is first used to increase the signal quality of the EEG trials and also to reduce the dimensionality of the covariance matrices, and then Riemannian tangent space features are extracted. We validate the performance of the proposed approach in reaction time estimation from EEG signals measured in a large-scale sustained-attention psychomotor vigilance task, and show that compared with the traditional powerband features, the tangent space features can reduce the root mean square estimation error by 4.30%-8.30%, and increase the estimation correlation coefficient by 6.59%-11.13%.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Nakanishi201728448641,
  title = {Detecting Glaucoma With a Portable Brain-Computer Interface for Objective Assessment of Visual Function Loss.},
  author = {Nakanishi, M and Wang, YT and Jung, TP and Zao, JK and Chien, YY and Diniz-Filho, A and Daga, FB and Lin, YP and Wang, Y and Medeiros, FA},
  journal = {JAMA ophthalmology},
  year = {2017},
  doi = {10.1001/jamaophthalmol.2017.0738},
  pmid = {28448641},
  url = {https://pubmed.ncbi.nlm.nih.gov/28448641/},
  abstract = {The current assessment of visual field loss in diseases such as glaucoma is affected by the subjectivity of patient responses and the lack of portability of standard perimeters. To describe the development and initial validation of a portable brain-computer interface (BCI) for objectively assessing visual function loss. This case-control study involved 62 eyes of 33 patients with glaucoma and 30 eyes of 17 healthy participants. Glaucoma was diagnosed based on a masked grading of optic disc stereophotographs. All participants underwent testing with a BCI device and standard automated perimetry (SAP) within 3 months. The BCI device integrates wearable, wireless, dry electroencephalogram and electrooculogram systems and a cellphone-based head-mounted display to enable the detection of multifocal steady state visual-evoked potentials associated with visual field stimulation. The performances of global and sectoral multifocal steady state visual-evoked potentials metrics to discriminate glaucomatous from healthy eyes were compared with global and sectoral SAP parameters. The repeatability of the BCI device measurements was assessed by collecting results of repeated testing in 20 eyes of 10 participants with glaucoma for 3 sessions of measurements separated by weekly intervals. Receiver operating characteristic curves summarizing diagnostic accuracy. Intraclass correlation coefficients and coefficients of variation for assessing repeatability. Among the 33 participants with glaucoma, 19 (58%) were white, 12 (36%) were black, and 2 (6%) were Asian, while among the 17 participants with healthy eyes, 9 (53%) were white, 8 (47%) were black, and none were Asian. The receiver operating characteristic curve area for the global BCI multifocal steady state visual-evoked potentials parameter was 0.92 (95% CI, 0.86-0.96), which was larger than for SAP mean deviation (area under the curve, 0.81; 95% CI, 0.72-0.90), SAP mean sensitivity (area under the curve, 0.80; 95% CI, 0.69-0.88; P = .03), and SAP pattern standard deviation (area under the curve, 0.77; 95% CI, 0.66-0.87; P = .01). No statistically significant differences were seen for the sectoral measurements between the BCI and SAP. Intraclass coefficients for global and sectoral parameters ranged from 0.74 to 0.92, and mean coefficients of variation ranged from 3.03% to 7.45%. The BCI device may be useful for assessing the electrical brain responses associated with visual field stimulation. The device discriminated eyes with glaucomatous neuropathy from healthy eyes in a clinically based setting. Further studies should investigate the feasibility of the BCI device for home-based testing as well as for detecting visual function loss over time.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{PionTonachini201730416242,
  title = {Crowd labeling latent Dirichlet allocation.},
  author = {Pion-Tonachini, L and Makeig, S and Kreutz-Delgado, K},
  journal = {Knowledge and information systems},
  year = {2017},
  doi = {10.1007/s10115-017-1053-1},
  pmid = {30416242},
  url = {https://pubmed.ncbi.nlm.nih.gov/30416242/},
  abstract = {Large, unlabeled datasets are abundant nowadays, but getting labels for those datasets can be expensive and time-consuming. Crowd labeling is a crowdsourcing approach for gathering such labels from workers whose suggestions are not always accurate. While a variety of algorithms exist for this purpose, we present crowd labeling latent Dirichlet allocation (CL-LDA), a generalization of latent Dirichlet allocation that can solve a more general set of crowd labeling problems. We show that it performs as well as other methods and at times better on a variety of simulated and actual datasets while treating each label as compositional rather than indicating a discrete class. In addition, prior knowledge of workers' abilities can be incorporated into the model through a structured Bayesian framework. We then apply CL-LDA to the EEG independent component labeling dataset, using its generalizations to further explore the utility of the algorithm. We discuss prospects for creating classifiers from the generated labels.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gola201728409565,
  title = {Can Pornography be Addictive? An fMRI Study of Men Seeking Treatment for Problematic Pornography Use.},
  author = {Gola, M and Wordecha, M and Sescousse, G and Lew-Starowicz, M and Kossowski, B and Wypych, M and Makeig, S and Potenza, MN and Marchewka, A},
  journal = {Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology},
  year = {2017},
  doi = {10.1038/npp.2017.78},
  pmid = {28409565},
  url = {https://pubmed.ncbi.nlm.nih.gov/28409565/},
  abstract = {Pornography consumption is highly prevalent, particularly among young adult males. For some individuals, problematic pornography use (PPU) is a reason for seeking treatment. Despite the pervasiveness of pornography, PPU appears under-investigated, including with respect to the underlying neural mechanisms. Using functional magnetic resonance imaging (fMRI), we examined ventral striatal responses to erotic and monetary stimuli, disentangling cue-related 'wanting' from reward-related 'liking' among 28 heterosexual males seeking treatment for PPU and 24 heterosexual males without PPU. Subjects engaged in an incentive delay task in the scanner, in which they received erotic or monetary rewards preceded by predictive cues. Blood-oxygen-level-dependent responses to erotic and monetary cues were analyzed and examined with respect to self-reported data on sexual activity collected over the 2 preceding months. Men with and without PPU differed in their striatal responses to cues predicting erotic pictures but not in their responses to erotic pictures. PPU subjects when compared with control subjects showed increased activation of ventral striatum specifically for cues predicting erotic pictures but not for cues predicting monetary gains. Relative sensitivity to cues predicting erotic pictures vs monetary gains was significantly related to the increased behavioral motivation to view erotic images (suggestive of higher 'wanting'), severity of PPU, amount of pornography use per week, and number of weekly masturbations. Our findings suggest that, similar to what is observed in substance and gambling addictions, the neural and behavioral mechanisms associated with the anticipatory processing of cues specifically predicting erotic rewards relate importantly to clinically relevant features of PPU. These findings suggest that PPU may represent a behavioral addiction and that interventions helpful in targeting behavioral and substance addictions warrant consideration for adaptation and use in helping men with PPU.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gouraud201729051723,
  title = {Autopilot, Mind Wandering, and the Out of the Loop Performance Problem.},
  author = {Gouraud, J and Delorme, A and Berberian, B},
  journal = {Frontiers in neuroscience},
  year = {2017},
  doi = {10.3389/fnins.2017.00541},
  pmid = {29051723},
  url = {https://pubmed.ncbi.nlm.nih.gov/29051723/},
  abstract = {To satisfy the increasing demand for safer critical systems, engineers have integrated higher levels of automation, such as glass cockpits in aircraft, power plants, and driverless cars. These guiding principles relegate the operator to a monitoring role, increasing risks for humans to lack system understanding. The out of the loop performance problem arises when operators suffer from complacency and vigilance decrement; consequently, when automation does not behave as expected, understanding the system or taking back manual control may be difficult. Close to the out of the loop problem, mind wandering points to the propensity of the human mind to think about matters unrelated to the task at hand. This article reviews the literature related to both mind wandering and the out of the loop performance problem as it relates to task automation. We highlight studies showing how these phenomena interact with each other while impacting human performance within highly automated systems. We analyze how this proximity is supported by effects observed in automated environment, such as decoupling, sensory attention, and cognitive comprehension decrease. We also show that this link could be useful for detecting out of the loop situations through mind wandering markers. Finally, we examine the limitations of the current knowledge because many questions remain open to characterize interactions between out of the loop, mind wandering, and automation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wang201727254871,
  title = {An Online Brain-Computer Interface Based on SSVEPs Measured From Non-Hair-Bearing Areas.},
  author = {Wang, YT and Nakanishi, M and Wang, Y and Wei, CS and Cheng, CK and Jung, TP},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2017},
  doi = {10.1109/TNSRE.2016.2573819},
  pmid = {27254871},
  url = {https://pubmed.ncbi.nlm.nih.gov/27254871/},
  abstract = {Steady state visual evoked potential (SSVEP)-based brain-computer interface (BCI) has gained a lot of attention due to its robustness and high information transfer rate (ITR). However, transitioning well-controlled laboratory-oriented BCI demonstrations to real-world applications poses severe challenges for this exciting field. For instance, conducting BCI experiments usually requires skilled technicians to abrade the area of skin underneath each electrode and apply an electrolytic gel or paste to acquire high-quality SSVEPs from hair-covered areas. Our previous proof-of-concept study has proposed an alternative approach that employed electroencephalographic signals collected from easily accessible non-hair-bearing areas including neck, behind the ears, and face to realize an SSVEP-based BCI. The study results showed that, with proper electrode placements and advanced signal-processing algorithms, the SSVEPs measured from non-hair-bearing areas in off-line SSVEP experiments could achieve comparable SNR to that obtained from the hair-bearing occipital areas. This study extended the previous work to systematically investigate the costs and benefits of non-hair SSVEPs. Furthermore, this study developed and evaluated an online BCI system based solely on non-hair EEG signals. A 12-target identification task was employed to quantitatively assess the performance of the online SSVEP-based BCI system. All subjects successfully completed the tasks using non-hair SSVEPs with 84.08 ± 15.60% averaged accuracy and 30.21 ± 10.61 bits/min averaged ITR. The empirical results of this study demonstrated the practicality of implementing an SSVEP-based BCI based on signals from non-hair-bearing areas, significantly improving the feasibility and practicality of real-world BCIs.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gola201627012817,
  title = {What Matters: Quantity or Quality of Pornography Use? Psychological and Behavioral Factors of Seeking Treatment for Problematic Pornography Use.},
  author = {Gola, M and Lewczuk, K and Skorko, M},
  journal = {The journal of sexual medicine},
  year = {2016},
  doi = {10.1016/j.jsxm.2016.02.169},
  pmid = {27012817},
  url = {https://pubmed.ncbi.nlm.nih.gov/27012817/},
  abstract = {Pornography has become popular with Internet technology. For most people, pornography use (PU) is entertainment; for some, it can result in seeking treatment for out-of-control behavior. Previous studies have suggested that PU can influence sexual behaviors, but the direct relation between frequency of PU and treatment-seeking behaviors has not been examined. To investigate whether individuals seeking treatment as a consequence of their problematic PU do so because of their quantity of pornography consumption or because of more complex psychological and behavioral factors related to PU, such as the severity of negative symptoms associated with PU and/or subjective feeling of loss of control over one's behavior. A survey study was conducted of 569 heterosexual Caucasian men 18 to 68 years old, including 132 seeking treatment for problematic PU (referred by psychotherapists after their initial visit). The main outcome measures were self-reported PU, its negative symptoms, and actual treatment-seeking behavior. We tested models explaining sources of seeking treatment for problematic PU with negative symptoms associated with PU and additional factors (eg, onset and number of years of PU, religiosity, age, dyadic sexual activity, and relationship status). Seeking treatment was significantly, yet weakly, correlated solely with the frequency of PU (r = 0.21, P < .05) and this relation was significantly mediated by negative symptoms associated with PU (strong, nearly full mediation effect size; k(2) = 0.266). The relation between PU and negative symptoms was significant and mediated by self-reported subjective religiosity (weak, partial mediation; k(2) = 0.066) in those not seeking treatment. Onset of PU and age appeared to be insignificant. Our model was fairly fitted (comparative fit index = 0.989; root mean square error of approximation = 0.06; standardized root mean square residual = 0.035) and explained 43% of the variance in treatment-seeking behavior (1% was explained by frequency of PU and 42% was explained by negative symptoms associated with PU). Negative symptoms associated with PU more strongly predict seeking treatment than mere quantity of pornography consumption. Thus, treatment of problematic PU should address qualitative factors, rather than merely mitigating the frequency of the behavior, because frequency of PU might not be a core issue for all patients. Future diagnostic criteria for problematic PU should consider the complexity of this issue.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Brunner201627920674,
  title = {Volume Conduction Influences Scalp-Based Connectivity Estimates.},
  author = {Brunner, C and Billinger, M and Seeber, M and Mullen, TR and Makeig, S},
  journal = {Frontiers in computational neuroscience},
  year = {2016},
  doi = {10.3389/fncom.2016.00121},
  pmid = {27920674},
  url = {https://pubmed.ncbi.nlm.nih.gov/27920674/},
  note = {PubMed query source: Scott Makeig}
}

@article{Onton201627965558,
  title = {Visualization of Whole-Night Sleep EEG From 2-Channel Mobile Recording Device Reveals Distinct Deep Sleep Stages with Differential Electrodermal Activity.},
  author = {Onton, JA and Kang, DY and Coleman, TP},
  journal = {Frontiers in human neuroscience},
  year = {2016},
  doi = {10.3389/fnhum.2016.00605},
  pmid = {27965558},
  url = {https://pubmed.ncbi.nlm.nih.gov/27965558/},
  abstract = {Brain activity during sleep is a powerful marker of overall health, but sleep lab testing is prohibitively expensive and only indicated for major sleep disorders. This report demonstrates that mobile 2-channel in-home electroencephalogram (EEG) recording devices provided sufficient information to detect and visualize sleep EEG. Displaying whole-night sleep EEG in a spectral display allowed for quick assessment of general sleep stability, cycle lengths, stage lengths, dominant frequencies and other indices of sleep quality. By visualizing spectral data down to 0.1 Hz, a differentiation emerged between slow-wave sleep with dominant frequency between 0.1-1 Hz or 1-3 Hz, but rarely both. Thus, we present here the new designations, Hi and Lo Deep sleep, according to the frequency range with dominant power. Simultaneously recorded electrodermal activity (EDA) was primarily associated with Lo Deep and very rarely with Hi Deep or any other stage. Therefore, Hi and Lo Deep sleep appear to be physiologically distinct states that may serve unique functions during sleep. We developed an algorithm to classify five stages (Awake, Light, Hi Deep, Lo Deep and rapid eye movement (REM)) using a Hidden Markov Model (HMM), model fitting with the expectation-maximization (EM) algorithm, and estimation of the most likely sleep state sequence by the Viterbi algorithm. The resulting automatically generated sleep hypnogram can help clinicians interpret the spectral display and help researchers computationally quantify sleep stages across participants. In conclusion, this study demonstrates the feasibility of in-home sleep EEG collection, a rapid and informative sleep report format, and novel deep sleep designations accounting for spectral and physiological differences.},
  note = {PubMed query source: Julie Onton}
}

@article{Gola201627574507,
  title = {Visual Sexual Stimuli-Cue or Reward? A Perspective for Interpreting Brain Imaging Findings on Human Sexual Behaviors.},
  author = {Gola, M and Wordecha, M and Marchewka, A and Sescousse, G},
  journal = {Frontiers in human neuroscience},
  year = {2016},
  doi = {10.3389/fnhum.2016.00402},
  pmid = {27574507},
  url = {https://pubmed.ncbi.nlm.nih.gov/27574507/},
  abstract = {There is an increasing number of neuroimaging studies using visual sexual stimuli (VSS), especially within the emerging field of research on compulsive sexual behaviors (CSB). A central question in this field is whether behaviors such as excessive pornography consumption share common brain mechanisms with widely studied substance and behavioral addictions. Depending on how VSS are conceptualized, different predictions can be formulated within the frameworks of Reinforcement Learning or Incentive Salience Theory, where a crucial distinction is made between conditioned and unconditioned stimuli (related to reward anticipation vs. reward consumption, respectively). Surveying 40 recent human neuroimaging studies we show existing ambiguity about the conceptualization of VSS. Therefore, we feel that it is important to address the question of whether VSS should be considered as conditioned stimuli (cue) or unconditioned stimuli (reward). Here we present our own perspective, which is that in most laboratory settings VSS play a role of reward, as evidenced by: (1) experience of pleasure while watching VSS, possibly accompanied by genital reaction; (2) reward-related brain activity correlated with these pleasurable feelings in response to VSS; (3) a willingness to exert effort to view VSS similarly as for other rewarding stimuli such as money; and (4) conditioning for cues predictive of VSS. We hope that this perspective article will initiate a scientific discussion on this important and overlooked topic and increase attention for appropriate interpretations of results of human neuroimaging studies using VSS.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Grandchamp201627698660,
  title = {The Brainarium: An Interactive Immersive Tool for Brain Education, Art, and Neurotherapy.},
  author = {Grandchamp, R and Delorme, A},
  journal = {Computational intelligence and neuroscience},
  year = {2016},
  doi = {10.1155/2016/4204385},
  pmid = {27698660},
  url = {https://pubmed.ncbi.nlm.nih.gov/27698660/},
  abstract = {Recent theoretical and technological advances in neuroimaging techniques now allow brain electrical activity to be recorded using affordable and user-friendly equipment for nonscientist end-users. An increasing number of educators and artists have begun using electroencephalogram (EEG) to control multimedia and live artistic contents. In this paper, we introduce a new concept based on brain computer interface (BCI) technologies: the Brainarium. The Brainarium is a new pedagogical and artistic tool, which can deliver and illustrate scientific knowledge, as well as a new framework for scientific exploration. The Brainarium consists of a portable planetarium device that is being used as brain metaphor. This is done by projecting multimedia content on the planetarium dome and displaying EEG data recorded from a subject in real time using Brain Machine Interface (BMI) technologies. The system has been demonstrated through several performances involving an interaction between the subject controlling the BMI, a musician, and the audience during series of exhibitions and workshops in schools. We report here feedback from 134 participants who filled questionnaires to rate their experiences. Our results show improved subjective learning compared to conventional methods, improved entertainment value, improved absorption into the material being presented, and little discomfort.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Menear201627678546,
  title = {Strategies and impacts of patient and family engagement in collaborative mental healthcare: protocol for a systematic and realist review.},
  author = {Menear, M and Gervais, M and Careau, E and Chouinard, MC and Cloutier, G and Delorme, A and Dogba, MJ and Dugas, M and Gagnon, MP and Gilbert, M and Harvey, D and Houle, J and Kates, N and Knowles, S and Martin, N and Nease, D and Pluye, P and Samson, E and Zomahoun, HT and Légaré, F},
  journal = {BMJ open},
  year = {2016},
  doi = {10.1136/bmjopen-2016-012949},
  pmid = {27678546},
  url = {https://pubmed.ncbi.nlm.nih.gov/27678546/},
  abstract = {Collaborative mental healthcare (CMHC) has garnered worldwide interest as an effective, team-based approach to managing common mental disorders in primary care. However, questions remain about how CMHC works and why it works in some circumstances but not others. In this study, we will review the evidence on one understudied but potentially critical component of CMHC, namely the engagement of patients and families in care. Our aims are to describe the strategies used to engage people with depression or anxiety disorders and their families in CMHC and understand how these strategies work, for whom and in what circumstances. We are conducting a review with systematic and realist review components. Review part 1 seeks to identify and describe the patient and family engagement strategies featured in CMHC interventions based on systematic searches and descriptive analysis of these interventions. We will use a 2012 Cochrane review of CMHC as a starting point and perform new searches in multiple databases and trial registers to retrieve more recent CMHC intervention studies. In review part 2, we will build and refine programme theories for each of these engagement strategies. Initial theory building will proceed iteratively through content expert consultations, electronic searches for theoretical literature and review team brainstorming sessions. Cluster searches will then retrieve additional data on contexts, mechanisms and outcomes associated with engagement strategies, and pairs of review authors will analyse and synthesise the evidence and adjust initial programme theories. Our review follows a participatory approach with multiple knowledge users and persons with lived experience of mental illness. These partners will help us develop and tailor project outputs, including publications, policy briefs, training materials and guidance on how to make CMHC more patient-centred and family-centred. CRD42015025522.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Congedo201627090947,
  title = {Spatio-temporal common pattern: A companion method for ERP analysis in the time domain.},
  author = {Congedo, M and Korczowski, L and Delorme, A and Lopes da Silva, F},
  journal = {Journal of neuroscience methods},
  year = {2016},
  doi = {10.1016/j.jneumeth.2016.04.008},
  pmid = {27090947},
  url = {https://pubmed.ncbi.nlm.nih.gov/27090947/},
  abstract = {Already used at the incept of research on event-related potentials (ERP) over half a century ago, the arithmetic mean is still the benchmark for ERP estimation. Such estimation, however, requires a large number of sweeps and/or a careful rejection of artifacts affecting the electroencephalographic recording. In this article we propose a method for estimating ERPs as they are naturally contaminated by biological and instrumental artifacts. The proposed estimator makes use of multivariate spatio-temporal filtering to increase the signal-to-noise ratio. This approach integrates a number of relevant advances in ERP data analysis, such as single-sweep adaptive estimation of amplitude and latency and the use of multivariate regression to account for ERP overlapping in time. We illustrate the effectiveness of the proposed estimator analyzing a dataset comprising 24 subjects involving a visual odd-ball paradigm, without performing any artifact rejection. As compared to the arithmetic average, a lower number of sweeps is needed. Furthermore, artifact rejection can be performed roughly using permissive automatic procedures. The proposed ensemble average estimator yields a reference companion to the arithmetic ensemble average estimation, suitable both in clinical and research settings. The method can be applied equally to event related fields (ERF) recorded by means of magnetoencephalography. In this article we describe all necessary methodological details to promote testing and comparison of this proposed method by peers. Furthermore, we release a MATLAB toolbox, a plug-in for the EEGLAB software suite and a stand-alone executable application.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Okruszek201627327377,
  title = {Social and nonsocial affective processing in schizophrenia - An ERP study.},
  author = {Okruszek, Ł and Wichniak, A and Jarkiewicz, M and Schudy, A and Gola, M and Jednoróg, K and Marchewka, A and Łojek, E},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2016},
  doi = {10.1016/j.ijpsycho.2016.06.007},
  pmid = {27327377},
  url = {https://pubmed.ncbi.nlm.nih.gov/27327377/},
  abstract = {Despite social cognitive dysfunction that may be observed in patients with schizophrenia, the knowledge about social and nonsocial affective processing in schizophrenia is scant. The aim of this study was to examine neurophysiological and behavioural responses to neutral and negative stimuli with (faces, people) and without (animals, objects) social content in schizophrenia. Twenty-six patients with schizophrenia (SCZ) and 21 healthy controls (HC) completed a visual oddball paradigm with either negative or neutral pictures from the Nencki Affective Picture System (NAPS) as targets while EEG was recorded. Half of the stimuli within each category presented social content (faces, people). Negative stimuli with social content produced lower N2 amplitude and higher mean LPP than any other type of stimuli in both groups. Despite differences in behavioural ratings and alterations in ERP processing of affective stimuli (lack of EPN differentiation, decreased P3 to neutral stimuli) SCZ were still able to respond to specific categories of stimuli similarly to HC. The pattern of results suggests that with no additional emotion-related task demands patients with schizophrenia may present similar attentional engagement with negative social stimuli as healthy controls.},
  note = {PubMed query source: Mateusz Gola}
}

@article{AkalinAcar201626302675,
  title = {Simultaneous head tissue conductivity and EEG source location estimation.},
  author = {Akalin Acar, Z and Acar, CE and Makeig, S},
  journal = {NeuroImage},
  year = {2016},
  doi = {10.1016/j.neuroimage.2015.08.032},
  pmid = {26302675},
  url = {https://pubmed.ncbi.nlm.nih.gov/26302675/},
  abstract = {Accurate electroencephalographic (EEG) source localization requires an electrical head model incorporating accurate geometries and conductivity values for the major head tissues. While consistent conductivity values have been reported for scalp, brain, and cerebrospinal fluid, measured brain-to-skull conductivity ratio (BSCR) estimates have varied between 8 and 80, likely reflecting both inter-subject and measurement method differences. In simulations, mis-estimation of skull conductivity can produce source localization errors as large as 3cm. Here, we describe an iterative gradient-based approach to Simultaneous tissue Conductivity And source Location Estimation (SCALE). The scalp projection maps used by SCALE are obtained from near-dipolar effective EEG sources found by adequate independent component analysis (ICA) decomposition of sufficient high-density EEG data. We applied SCALE to simulated scalp projections of 15cm(2)-scale cortical patch sources in an MR image-based electrical head model with simulated BSCR of 30. Initialized either with a BSCR of 80 or 20, SCALE estimated BSCR as 32.6. In Adaptive Mixture ICA (AMICA) decompositions of (45-min, 128-channel) EEG data from two young adults we identified sets of 13 independent components having near-dipolar scalp maps compatible with a single cortical source patch. Again initialized with either BSCR 80 or 25, SCALE gave BSCR estimates of 34 and 54 for the two subjects respectively. The ability to accurately estimate skull conductivity non-invasively from any well-recorded EEG data in combination with a stable and non-invasively acquired MR imaging-derived electrical head model could remove a critical barrier to using EEG as a sub-cm(2)-scale accurate 3-D functional cortical imaging modality.},
  note = {PubMed query source: Scott Makeig}
}

@article{Loo201626099166,
  title = {Research Review: Use of EEG biomarkers in child psychiatry research - current state and future directions.},
  author = {Loo, SK and Lenartowicz, A and Makeig, S},
  journal = {Journal of child psychology and psychiatry, and allied disciplines},
  year = {2016},
  doi = {10.1111/jcpp.12435},
  pmid = {26099166},
  url = {https://pubmed.ncbi.nlm.nih.gov/26099166/},
  abstract = {Electroencephalography (EEG) and related measures have a long and productive history in child psychopathology research and are currently experiencing a renaissance in interest, particularly for use as putative biomarkers. First, the recent history leading to the use of EEG measures as endophenotypes and biomarkers for disease and treatment response are reviewed. Two key controversies within the area of noninvasive human electrophysiology research are discussed, and problems that currently either function as barriers or provide gateways to progress. First, the differences between the main types of EEG measurements (event-related potentials, quantitative EEG, and time-frequency measures) and how they can contribute collectively to better understanding of cortical dynamics underlying cognition and behavior are highlighted. Second, we focus on the ongoing shift in analytic focus to specific cortical sources and source networks whose dynamics are relevant to the clinical and experimental focus of the study, and the effective increase in source signal-to-noise ratio (SNR) that may be obtained in the process. Understanding of these issues informs any discussion of current trends in EEG research. We highlight possible ways to evolve our understanding of brain dynamics beyond the apparent contradictions in understanding and modeling EEG activity highlighted by these controversies. Finally, we summarize some promising future directions of EEG biomarker research in child psychopathology.},
  note = {PubMed query source: Scott Makeig}
}

@article{Hsu201626685257,
  title = {Real-Time Adaptive EEG Source Separation Using Online Recursive Independent Component Analysis.},
  author = {Hsu, SH and Mullen, TR and Jung, TP and Cauwenberghs, G},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2016},
  doi = {10.1109/TNSRE.2015.2508759},
  pmid = {26685257},
  url = {https://pubmed.ncbi.nlm.nih.gov/26685257/},
  abstract = {Independent component analysis (ICA) has been widely applied to electroencephalographic (EEG) biosignal processing and brain-computer interfaces. The practical use of ICA, however, is limited by its computational complexity, data requirements for convergence, and assumption of data stationarity, especially for high-density data. Here we study and validate an optimized online recursive ICA algorithm (ORICA) with online recursive least squares (RLS) whitening for blind source separation of high-density EEG data, which offers instantaneous incremental convergence upon presentation of new data. Empirical results of this study demonstrate the algorithm's: 1) suitability for accurate and efficient source identification in high-density (64-channel) realistically-simulated EEG data; 2) capability to detect and adapt to nonstationarity in 64-ch simulated EEG data; and 3) utility for rapidly extracting principal brain and artifact sources in real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment. ORICA was implemented as functions in BCILAB and EEGLAB and was integrated in an open-source Real-time EEG Source-mapping Toolbox (REST), supporting applications in ICA-based online artifact rejection, feature extraction for real-time biosignal monitoring in clinical environments, and adaptable classifications in brain-computer interfaces.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{BigdelyShamlo201627014048,
  title = {Preparing Laboratory and Real-World EEG Data for Large-Scale Analysis: A Containerized Approach.},
  author = {Bigdely-Shamlo, N and Makeig, S and Robbins, KA},
  journal = {Frontiers in neuroinformatics},
  year = {2016},
  doi = {10.3389/fninf.2016.00007},
  pmid = {27014048},
  url = {https://pubmed.ncbi.nlm.nih.gov/27014048/},
  abstract = {Large-scale analysis of EEG and other physiological measures promises new insights into brain processes and more accurate and robust brain-computer interface models. However, the absence of standardized vocabularies for annotating events in a machine understandable manner, the welter of collection-specific data organizations, the difficulty in moving data across processing platforms, and the unavailability of agreed-upon standards for preprocessing have prevented large-scale analyses of EEG. Here we describe a "containerized" approach and freely available tools we have developed to facilitate the process of annotating, packaging, and preprocessing EEG data collections to enable data sharing, archiving, large-scale machine learning/data mining and (meta-)analysis. The EEG Study Schema (ESS) comprises three data "Levels," each with its own XML-document schema and file/folder convention, plus a standardized (PREP) pipeline to move raw (Data Level 1) data to a basic preprocessed state (Data Level 2) suitable for application of a large class of EEG analysis methods. Researchers can ship a study as a single unit and operate on its data using a standardized interface. ESS does not require a central database and provides all the metadata data necessary to execute a wide variety of EEG processing pipelines. The primary focus of ESS is automated in-depth analysis and meta-analysis EEG studies. However, ESS can also encapsulate meta-information for the other modalities such as eye tracking, that are increasingly used in both laboratory and real-world neuroimaging. ESS schema and tools are freely available at www.eegstudy.org and a central catalog of over 850 GB of existing data in ESS format is available at studycatalog.org. These tools and resources are part of a larger effort to enable data sharing at sufficient scale for researchers to engage in truly large-scale EEG analysis and data mining (BigEEG.org).},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme201627242466,
  title = {Prediction of Mortality Based on Facial Characteristics.},
  author = {Delorme, A and Pierce, A and Michel, L and Radin, D},
  journal = {Frontiers in human neuroscience},
  year = {2016},
  doi = {10.3389/fnhum.2016.00173},
  pmid = {27242466},
  url = {https://pubmed.ncbi.nlm.nih.gov/27242466/},
  abstract = {Recent studies have shown that characteristics of the face contain a wealth of information about health, age and chronic clinical conditions. Such studies involve objective measurement of facial features correlated with historical health information. But some individuals also claim to be adept at gauging mortality based on a glance at a person's photograph. To test this claim, we invited 12 such individuals to see if they could determine if a person was alive or dead based solely on a brief examination of facial photographs. All photos used in the experiment were transformed into a uniform gray scale and then counterbalanced across eight categories: gender, age, gaze direction, glasses, head position, smile, hair color, and image resolution. Participants examined 404 photographs displayed on a computer monitor, one photo at a time, each shown for a maximum of 8 s. Half of the individuals in the photos were deceased, and half were alive at the time the experiment was conducted. Participants were asked to press a button if they thought the person in a photo was living or deceased. Overall mean accuracy on this task was 53.8%, where 50% was expected by chance (p < 0.004, two-tail). Statistically significant accuracy was independently obtained in 5 of the 12 participants. We also collected 32-channel electrophysiological recordings and observed a robust difference between images of deceased individuals correctly vs. incorrectly classified in the early event related potential (ERP) at 100 ms post-stimulus onset. Our results support claims of individuals who report that some as-yet unknown features of the face predict mortality. The results are also compatible with claims about clairvoyance warrants further investigation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Gola201627440474,
  title = {Paroxetine Treatment of Problematic Pornography Use: A Case Series.},
  author = {Gola, M and Potenza, MN},
  journal = {Journal of behavioral addictions},
  year = {2016},
  doi = {10.1556/2006.5.2016.046},
  pmid = {27440474},
  url = {https://pubmed.ncbi.nlm.nih.gov/27440474/},
  abstract = {Background How best to conceptualize problematic pornography use (PPU) and intervene most effectively remain debated, with obsessive-compulsive disorder (OCD) and addiction frameworks. We investigated the efficacy of the serotonin-reuptake inhibitor paroxetine in combination with cognitive-behavioral therapy in the treatment of problematic pornography use (PPU). Case presentation Three heterosexual males with PPU were treated with cognitive-behavioral therapy and paroxetine. Frequency of pornography use, other sexual behaviors, and anxiety were assessed during treatment. Discussion Paroxetine treatment, although seemingly initially effective in reducing pornography use and anxiety, appeared related to new compulsive sexual behaviors after 3 months. Conclusions Paroxetine may hold promise for short-term reduction of PPU and related anxiety, but new potentially distressing sexual behaviors may emerge. The cases suggest that PPU may arise from multiple domains. We propose an explanation of the effects based on recent neuroscientific research on sexual behaviors and alcohol use.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Lin201626882993,
  title = {Mind-Wandering Tends to Occur under Low Perceptual Demands during Driving.},
  author = {Lin, CT and Chuang, CH and Kerick, S and Mullen, T and Jung, TP and Ko, LW and Chen, SA and King, JT and McDowell, K},
  journal = {Scientific reports},
  year = {2016},
  doi = {10.1038/srep21353},
  pmid = {26882993},
  url = {https://pubmed.ncbi.nlm.nih.gov/26882993/},
  abstract = {Fluctuations in attention behind the wheel poses a significant risk for driver safety. During transient periods of inattention, drivers may shift their attention towards internally-directed thoughts or feelings at the expense of staying focused on the road. This study examined whether increasing task difficulty by manipulating involved sensory modalities as the driver detected the lane-departure in a simulated driving task would promote a shift of brain activity between different modes of processing, reflected by brain network dynamics on electroencephalographic sources. Results showed that depriving the driver of salient sensory information imposes a relatively more perceptually-demanding task, leading to a stronger activation in the task-positive network. When the vehicle motion feedback is available, the drivers may rely on vehicle motion to perceive the perturbations, which frees attentional capacity and tends to activate the default mode network. Such brain network dynamics could have major implications for understanding fluctuations in driver attention and designing advance driver assistance systems.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Nonoda201627178869,
  title = {Interictal high-frequency oscillations generated by seizure onset and eloquent areas may be differentially coupled with different slow waves.},
  author = {Nonoda, Y and Miyakoshi, M and Ojeda, A and Makeig, S and Juhász, C and Sood, S and Asano, E},
  journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
  year = {2016},
  doi = {10.1016/j.clinph.2016.03.022},
  pmid = {27178869},
  url = {https://pubmed.ncbi.nlm.nih.gov/27178869/},
  abstract = {High-frequency oscillations (HFOs) can be spontaneously generated by seizure-onset and functionally-important areas. We determined if consideration of the spectral frequency bands of coupled slow-waves could distinguish between epileptogenic and physiological HFOs. We studied a consecutive series of 13 children with focal epilepsy who underwent extraoperative electrocorticography. We measured the occurrence rate of HFOs during slow-wave sleep at each electrode site. We subsequently determined the performance of HFO rate for localization of seizure-onset sites and undesirable detection of nonepileptic sensorimotor-visual sites defined by neurostimulation. We likewise determined the predictive performance of modulation index: MI(XHz)&(YHz), reflecting the strength of coupling between amplitude of HFOsXHz and phase of slow-waveYHz. The predictive accuracy was quantified using the area under the curve (AUC) on receiver-operating characteristics analysis. Increase in HFO rate localized seizure-onset sites (AUC⩾0.72; p<0.001), but also undesirably detected nonepileptic sensorimotor-visual sites (AUC⩾0.58; p<0.001). Increase in MI(HFOs)&(3-4Hz) also detected both seizure-onset (AUC⩾0.74; p<0.001) and nonepileptic sensorimotor-visual sites (AUC⩾0.59; p<0.001). Increase in subtraction-MIHFOs [defined as subtraction of MI(HFOs)&(0.5-1Hz) from MI(HFOs)&(3-4Hz)] localized seizure-onset sites (AUC⩾0.71; p<0.001), but rather avoided detection of nonepileptic sensorimotor-visual sites (AUC⩽0.42; p<0.001). Our data suggest that epileptogenic HFOs may be coupled with slow-wave3-4Hz more preferentially than slow-wave0.5-1Hz, whereas physiologic HFOs with slow-wave0.5-1Hz more preferentially than slow-wave3-4Hz during slow-wave sleep. Further studies in larger samples are warranted to determine if consideration of the spectral frequency bands of slow-waves coupled with HFOs can positively contribute to presurgical evaluation of patients with focal epilepsy.},
  note = {PubMed query source: Scott Makeig}
}

@article{Piazza201626944858,
  title = {ICA-derived cortical responses indexing rapid multi-feature auditory processing in six-month-old infants.},
  author = {Piazza, C and Cantiani, C and Akalin-Acar, Z and Miyakoshi, M and Benasich, AA and Reni, G and Bianchi, AM and Makeig, S},
  journal = {NeuroImage},
  year = {2016},
  doi = {10.1016/j.neuroimage.2016.02.060},
  pmid = {26944858},
  url = {https://pubmed.ncbi.nlm.nih.gov/26944858/},
  abstract = {The abilities of infants to perceive basic acoustic differences, essential for language development, can be studied using auditory event-related potentials (ERPs). However, scalp-channel averaged ERPs sum volume-conducted contributions from many cortical areas, reducing the functional specificity and interpretability of channel-based ERP measures. This study represents the first attempt to investigate rapid auditory processing in infancy using independent component analysis (ICA), allowing exploration of source-resolved ERP dynamics and identification of ERP cortical generators. Here, we recorded 60-channel EEG data in 34 typically developing 6-month-old infants during a passive acoustic oddball paradigm presenting 'standard' tones interspersed with frequency- or duration-deviant tones. ICA decomposition was applied to single-subject EEG data. The best-fitting equivalent dipole or bilaterally symmetric dipole pair was then estimated for each resulting independent component (IC) process using a four-layer infant head model. Similar brain-source ICs were clustered across subjects. Results showed ERP contributions from auditory cortex and multiple extra-auditory cortical areas (often, bilaterally paired). Different cortical source combinations contributed to the frequency- and duration-deviant ERP peak sequences. For ICs in an ERP-dominant source cluster located in or near the mid-cingulate cortex, source-resolved frequency-deviant response N2 latency and P3 amplitude at 6 months-of-age predicted vocabulary size at 20 months-of-age. The same measures for scalp channel F6 (though not for other frontal channels) showed similar but weaker correlations. These results demonstrate the significant potential of ICA analyses to facilitate a deeper understanding of the neural substrates of infant sensory processing.},
  note = {PubMed query source: Scott Makeig}
}

@article{Acar201628268293,
  title = {High-resolution EEG source imaging of one-year-old children.},
  author = {Acar, ZA and Ortiz-Mantilla, S and Benasich, A and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2016},
  doi = {10.1109/EMBC.2016.7590654},
  pmid = {28268293},
  url = {https://pubmed.ncbi.nlm.nih.gov/28268293/},
  abstract = {Recently we described an iterative skull conductivity and source location estimation (SCALE) algorithm for simultaneously estimating head tissue conductivities and brain source locations. SCALE uses a realistic FEM forward problem head model and scalp maps of 10 or more near-dipolar sources identified by independent component analysis (ICA) decomposition of sufficient high-density EEG data. In this study, we applied SCALE to 20 minutes of 64-channel EEG data and magnetic resonance (MR) head images from four twelve-months-of-age infants. For each child, we selected 15-16 near-dipolar independent components from multiple-model adaptive mixture ICA (AMICA) decomposition of their EEG data. SCALE converged to brain-to-skull conductivity ratio (BSCR) estimates in the 10-12 range and mostly compact gyral or sulcal cortical distributions for the IC sources.},
  note = {PubMed query source: Scott Makeig}
}

@article{BigdelyShamlo201627799907,
  title = {Hierarchical Event Descriptors (HED): Semi-Structured Tagging for Real-World Events in Large-Scale EEG.},
  author = {Bigdely-Shamlo, N and Cockfield, J and Makeig, S and Rognon, T and La Valle, C and Miyakoshi, M and Robbins, KA},
  journal = {Frontiers in neuroinformatics},
  year = {2016},
  doi = {10.3389/fninf.2016.00042},
  pmid = {27799907},
  url = {https://pubmed.ncbi.nlm.nih.gov/27799907/},
  abstract = {Real-world brain imaging by EEG requires accurate annotation of complex subject-environment interactions in event-rich tasks and paradigms. This paper describes the evolution of the Hierarchical Event Descriptor (HED) system for systematically describing both laboratory and real-world events. HED version 2, first described here, provides the semantic capability of describing a variety of subject and environmental states. HED descriptions can include stimulus presentation events on screen or in virtual worlds, experimental or spontaneous events occurring in the real world environment, and events experienced via one or multiple sensory modalities. Furthermore, HED 2 can distinguish between the mere presence of an object and its actual (or putative) perception by a subject. Although the HED framework has implicit ontological and linked data representations, the user-interface for HED annotation is more intuitive than traditional ontological annotation. We believe that hiding the formal representations allows for a more user-friendly interface, making consistent, detailed tagging of experimental, and real-world events possible for research users. HED is extensible while retaining the advantages of having an enforced common core vocabulary. We have developed a collection of tools to support HED tag assignment and validation; these are available at hedtags.org. A plug-in for EEGLAB (sccn.ucsd.edu/eeglab), CTAGGER, is also available to speed the process of tagging existing studies.},
  note = {PubMed query source: Scott Makeig}
}

@article{Horikoshi201627680694,
  title = {Genome-wide associations for birth weight and correlations with adult disease.},
  author = {Horikoshi, M and Beaumont, RN and Day, FR and Warrington, NM and Kooijman, MN and Fernandez-Tajes, J and Feenstra, B and van Zuydam, NR and Gaulton, KJ and Grarup, N and Bradfield, JP and Strachan, DP and Li-Gao, R and Ahluwalia, TS and Kreiner, E and Rueedi, R and Lyytikäinen, LP and Cousminer, DL and Wu, Y and Thiering, E and Wang, CA and Have, CT and Hottenga, JJ and Vilor-Tejedor, N and Joshi, PK and Boh, ETH and Ntalla, I and Pitkänen, N and Mahajan, A and van Leeuwen, EM and Joro, R and Lagou, V and Nodzenski, M and Diver, LA and Zondervan, KT and Bustamante, M and Marques-Vidal, P and Mercader, JM and Bennett, AJ and Rahmioglu, N and Nyholt, DR and Ma, RCW and Tam, CHT and Tam, WH and CHARGE Consortium Hematology Working Group and Ganesh, SK and van Rooij, FJ and Jones, SE and Loh, PR and Ruth, KS and Tuke, MA and Tyrrell, J and Wood, AR and Yaghootkar, H and Scholtens, DM and Paternoster, L and Prokopenko, I and Kovacs, P and Atalay, M and Willems, SM and Panoutsopoulou, K and Wang, X and Carstensen, L and Geller, F and Schraut, KE and Murcia, M and van Beijsterveldt, CE and Willemsen, G and Appel, EVR and Fonvig, CE and Trier, C and Tiesler, CM and Standl, M and Kutalik, Z and Bonas-Guarch, S and Hougaard, DM and Sánchez, F and Torrents, D and Waage, J and Hollegaard, MV and de Haan, HG and Rosendaal, FR and Medina-Gomez, C and Ring, SM and Hemani, G and McMahon, G and Robertson, NR and Groves, CJ and Langenberg, C and Luan, J and Scott, RA and Zhao, JH and Mentch, FD and MacKenzie, SM and Reynolds, RM and Early Growth Genetics (EGG) Consortium and Lowe, WL and Tönjes, A and Stumvoll, M and Lindi, V and Lakka, TA and van Duijn, CM and Kiess, W and Körner, A and Sørensen, TI and Niinikoski, H and Pahkala, K and Raitakari, OT and Zeggini, E and Dedoussis, GV and Teo, YY and Saw, SM and Melbye, M and Campbell, H and Wilson, JF and Vrijheid, M and de Geus, EJ and Boomsma, DI and Kadarmideen, HN and Holm, JC and Hansen, T and Sebert, S and Hattersley, AT and Beilin, LJ and Newnham, JP and Pennell, CE and Heinrich, J and Adair, LS and Borja, JB and Mohlke, KL and Eriksson, JG and Widén, EE and Kähönen, M and Viikari, JS and Lehtimäki, T and Vollenweider, P and Bønnelykke, K and Bisgaard, H and Mook-Kanamori, DO and Hofman, A and Rivadeneira, F and Uitterlinden, AG and Pisinger, C and Pedersen, O and Power, C and Hyppönen, E and Wareham, NJ and Hakonarson, H and Davies, E and Walker, BR and Jaddoe, VW and Jarvelin, MR and Grant, SF and Vaag, AA and Lawlor, DA and Frayling, TM and Davey Smith, G and Morris, AP and Ong, KK and Felix, JF and Timpson, NJ and Perry, JR and Evans, DM and McCarthy, MI and Freathy, RM},
  journal = {Nature},
  year = {2016},
  doi = {10.1038/nature19806},
  pmid = {27680694},
  url = {https://pubmed.ncbi.nlm.nih.gov/27680694/},
  abstract = {Birth weight (BW) has been shown to be influenced by both fetal and maternal factors and in observational studies is reproducibly associated with future risk of adult metabolic diseases including type 2 diabetes (T2D) and cardiovascular disease. These life-course associations have often been attributed to the impact of an adverse early life environment. Here, we performed a multi-ancestry genome-wide association study (GWAS) meta-analysis of BW in 153,781 individuals, identifying 60 loci where fetal genotype was associated with BW (P < 5 × 10 -8 ). Overall, approximately 15% of variance in BW was captured by assays of fetal genetic variation. Using genetic association alone, we found strong inverse genetic correlations between BW and systolic blood pressure (R g  = -0.22, P = 5.5 × 10 -13 ), T2D (R g  = -0.27, P = 1.1 × 10 -6 ) and coronary artery disease (R g  = -0.30, P = 6.5 × 10 -9 ). In addition, using large -cohort datasets, we demonstrated that genetic factors were the major contributor to the negative covariance between BW and future cardiometabolic risk. Pathway analyses indicated that the protein products of genes within BW-associated regions were enriched for diverse processes including insulin signalling, glucose homeostasis, glycogen biosynthesis and chromatin remodelling. There was also enrichment of associations with BW in known imprinted regions (P = 1.9 × 10 -4 ). We demonstrate that life-course associations between early growth phenotypes and adult cardiometabolic disease are in part the result of shared genetic effects and identify some of the pathways through which these causal genetic effects are mediated.},
  note = {PubMed query source: Ying Wu}
}

@article{Xu201627705952,
  title = {Fast detection of covert visuospatial attention using hybrid N2pc and SSVEP features.},
  author = {Xu, M and Wang, Y and Nakanishi, M and Wang, YT and Qi, H and Jung, TP and Ming, D},
  journal = {Journal of neural engineering},
  year = {2016},
  doi = {10.1088/1741-2560/13/6/066003},
  pmid = {27705952},
  url = {https://pubmed.ncbi.nlm.nih.gov/27705952/},
  abstract = {Detecting the shift of covert visuospatial attention (CVSA) is vital for gaze-independent brain-computer interfaces (BCIs), which might be the only communication approach for severely disabled patients who cannot move their eyes. Although previous studies had demonstrated that it is feasible to use CVSA-related electroencephalography (EEG) features to control a BCI system, the communication speed remains very low. This study aims to improve the speed and accuracy of CVSA detection by fusing EEG features of N2pc and steady-state visual evoked potential (SSVEP). A new paradigm was designed to code the left and right CVSA with the N2pc and SSVEP features, which were then decoded by a classification strategy based on canonical correlation analysis. Eleven subjects were recruited to perform an offline experiment in this study. Temporal waves, amplitudes, and topographies for brain responses related to N2pc and SSVEP were analyzed. The classification accuracy derived from the hybrid EEG features (SSVEP and N2pc) was compared with those using the single EEG features (SSVEP or N2pc). The N2pc could be significantly enhanced under certain conditions of SSVEP modulations. The hybrid EEG features achieved significantly higher accuracy than the single features. It obtained an average accuracy of 72.9% by using a data length of 400 ms after the attention shift. Moreover, the average accuracy reached ∼80% (peak values above 90%) when using 2 s long data. The results indicate that the combination of N2pc and SSVEP is effective for fast detection of CVSA. The proposed method could be a promising approach for implementing a gaze-independent BCI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cruz201627520471,
  title = {ERPs and their brain sources in perceptual and conceptual prospective memory tasks: Commonalities and differences between the two tasks.},
  author = {Cruz, G and Miyakoshi, M and Makeig, S and Kilborn, K and Evans, J},
  journal = {Neuropsychologia},
  year = {2016},
  doi = {10.1016/j.neuropsychologia.2016.08.005},
  pmid = {27520471},
  url = {https://pubmed.ncbi.nlm.nih.gov/27520471/},
  abstract = {The present study examined whether Event-Related Potential (ERP) components and their neural generators are common to perceptual and conceptual prospective memory (PM) tasks or specific to the form of PM cue involved. We used Independent Component Analysis (ICA) to study the contributions of brain source activities to scalp ERPs across the different phases of two event-based PM-tasks: (1) holding intentions during a delay (monitoring) (2) detecting the correct context to perform the delayed intention (cue detection) and (3) carrying out the action (realisation of delayed intentions). Results showed that monitoring for both perceptual and conceptual PM-tasks was characterised by an enhanced early occipital negativity (N200). In addition the conceptual PM-task showed a long-lasting effect of monitoring significant around 700ms. Perceptual PM-task cues elicited an N300 enhancement associated with cue detection, whereas a midline N400-like response was evoked by conceptual PM-task cues. The Prospective Positivity associated with realisation of delayed intentions was observed in both conceptual and perceptual tasks. A common frontal-midline brain source contributed to the Prospective Positivity in both tasks and a strong contribution from parieto-frontal brain sources was observed only for the perceptually cued PM-task. These findings support the idea that: (1) The enhanced N200 can be understood as a neural correlate of a 'retrieval mode' for perceptual and conceptual PM-tasks, and additional strategic monitoring is implemented according the nature of the PM task; (2) ERPs associated with cue detection are specific to the nature of the PM cues; (3) Prospective Positivity reflects a general PM process, but the specific brain sources contributing to it depend upon the nature of the PM task.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wagner201626888931,
  title = {Distinct β Band Oscillatory Networks Subserving Motor and Cognitive Control during Gait Adaptation.},
  author = {Wagner, J and Makeig, S and Gola, M and Neuper, C and Müller-Putz, G},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2016},
  doi = {10.1523/JNEUROSCI.3543-15.2016},
  pmid = {26888931},
  url = {https://pubmed.ncbi.nlm.nih.gov/26888931/},
  abstract = {Everyday locomotion and obstacle avoidance requires effective gait adaptation in response to sensory cues. Many studies have shown that efficient motor actions are associated with μ rhythm (8-13 Hz) and β band (13-35 Hz) local field desynchronizations in sensorimotor and parietal cortex, whereas a number of cognitive task studies have reported higher behavioral accuracy to be associated with increases in β band power in prefrontal and sensory cortex. How these two distinct patterns of β band oscillations interplay during gait adaptation, however, has not been established. Here we recorded 108 channel EEG activity from 18 participants (10 males, 22-35 years old) attempting to walk on a treadmill in synchrony with a series of pacing cue tones, and quickly adapting their step rate and length to sudden shifts in pacing cue tempo. Independent component analysis parsed each participant's EEG data into maximally independent component (IC) source processes, which were then grouped across participants into distinct spatial/spectral clusters. Following cue tempo shifts, mean β band power was suppressed for IC sources in central midline and parietal regions, whereas mean β band power increased in IC sources in or near medial prefrontal and dorsolateral prefrontal cortex. In the right dorsolateral prefrontal cortex IC cluster, the β band power increase was stronger during (more effortful) step shortening than during step lengthening. These results thus show that two distinct patterns of β band activity modulation accompany gait adaptations: one likely serving movement initiation and execution; and the other, motor control and inhibition. Understanding brain dynamics supporting gait adaptation is crucial for understanding motor deficits in walking, such as those associated with aging, stroke, and Parkinson's. Only a few electromagnetic brain imaging studies have examined neural correlates of human upright walking. Here, application of independent component analysis to EEG data recorded during treadmill walking allowed us to uncover two distinct β band oscillatory cortical networks that are active during gait adaptation to shifts in the tempo of an auditory pacing cue: (8-13 Hz) μ rhythm and (13-35 Hz) β band power decreases in central and parietal cortex and (14-20 Hz) β band power increases in frontal brain areas. These results provide a fuller framework for electrophysiological studies of cortical gait control and its disorders.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gola201627235125,
  title = {Decreased LPP for sexual images in problematic pornography users may be consistent with addiction models. Everything depends on the model. (Commentary on Prause, Steele, Staley, Sabatinelli, & Hajcak, 2015).},
  author = {Gola, M},
  journal = {Biological psychology},
  year = {2016},
  doi = {10.1016/j.biopsycho.2016.05.003},
  pmid = {27235125},
  url = {https://pubmed.ncbi.nlm.nih.gov/27235125/},
  note = {PubMed query source: Mateusz Gola}
}

@article{Huang201627121994,
  title = {An EEG-Based Fatigue Detection and Mitigation System.},
  author = {Huang, KC and Huang, TY and Chuang, CH and King, JT and Wang, YK and Lin, CT and Jung, TP},
  journal = {International journal of neural systems},
  year = {2016},
  doi = {10.1142/S0129065716500180},
  pmid = {27121994},
  url = {https://pubmed.ncbi.nlm.nih.gov/27121994/},
  abstract = {Research has indicated that fatigue is a critical factor in cognitive lapses because it negatively affects an individual's internal state, which is then manifested physiologically. This study explores neurophysiological changes, measured by electroencephalogram (EEG), due to fatigue. This study further demonstrates the feasibility of an online closed-loop EEG-based fatigue detection and mitigation system that detects physiological change and can thereby prevent fatigue-related cognitive lapses. More importantly, this work compares the efficacy of fatigue detection and mitigation between the EEG-based and a nonEEG-based random method. Twelve healthy subjects participated in a sustained-attention driving experiment. Each participant's EEG signal was monitored continuously and a warning was delivered in real-time to participants once the EEG signature of fatigue was detected. Study results indicate suppression of the alpha- and theta-power of an occipital component and improved behavioral performance following a warning signal; these findings are in line with those in previous studies. However, study results also showed reduced warning efficacy (i.e. increased response times (RTs) to lane deviations) accompanied by increased alpha-power due to the fluctuation of warnings over time. Furthermore, a comparison of EEG-based and nonEEG-based random approaches clearly demonstrated the necessity of adaptive fatigue-mitigation systems, based on a subject's cognitive level, to deliver warnings. Analytical results clearly demonstrate and validate the efficacy of this online closed-loop EEG-based fatigue detection and mitigation mechanism to identify cognitive lapses that may lead to catastrophic incidents in countless operational environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Zhang201525592429,
  title = {Ultra-slow frequency bands reflecting potential coherence between neocortical brain regions.},
  author = {Zhang, X and Wang, YT and Wang, Y and Jung, TP and Huang, M and Cheng, CK and Mandell, AJ},
  journal = {Neuroscience},
  year = {2015},
  doi = {10.1016/j.neuroscience.2014.12.050},
  pmid = {25592429},
  url = {https://pubmed.ncbi.nlm.nih.gov/25592429/},
  abstract = {Recent studies of electromagnetic ultra-slow waves (⩽0.1Hz) have suggested that they play a role in the integration of otherwise disassociated brain regions supporting vital functions (Ackermann and Borbely, 1997; Picchioni et al., 2010; Knyazev, 2012; Le Bon et al., 2012). We emphasize this spectral domain in probing sensor coherence issues raised by these studies using Hilbert phase coherences in the human MEG. In addition, we ask: will temporal-spatial phase coherence in regional brain oscillations obtained from the ultraslow spectral bands of multi-channel magnetoencephalograms (MEG) differentiate resting, "task-free" MEG records of normal control and schizophrenic subjects? The goal of the study is a comparison of the relative persistence of intra-regional phase locking values (PLVs), among 10, region-defined, sensors in examined in the resting multichannel, MEG records as a function of spectral frequency bands and diagnostic category. The following comparison of Hilbert-transform-engendered relative phases of each designated spectral band was made using their pair-wise PLVs. This indicated the proportion of shared cycle time in which the phase relations between the index location and reference leads were maintained. Leave one out, bootstrapping of the PLVs via a support vector machine (SVM), classified clinical status with 97.3% accuracy. It was generally the case that spectral bands ⩽1.0Hz generated the highest values of the PLVs and discriminated best between control and patient populations. We conclude that PLV analysis of the oscillatory patterns of MEG recordings in the ultraslow frequency bands suggest their functional significance in intra-regional signal coherence and provide a higher rate of classification of patients and normal subjects than the other spectral domains examined.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hsu201526737197,
  title = {Tracking non-stationary EEG sources using adaptive online recursive independent component analysis.},
  author = {Hsu, SH and Pion-Tonachini, L and Jung, TP and Cauwenberghs, G},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7319297},
  pmid = {26737197},
  url = {https://pubmed.ncbi.nlm.nih.gov/26737197/},
  abstract = {Electroencephalographic (EEG) source-level analyses such as independent component analysis (ICA) have uncovered features related to human cognitive functions or artifactual activities. Among these methods, Online Recursive ICA (ORICA) has been shown to achieve fast convergence in decomposing high-density EEG data for real-time applications. However, its adaptation performance has not been fully explored due to the difficulty in choosing an appropriate forgetting factor: the weight applied to new data in a recursive update which determines the trade-off between the adaptation capability and convergence quality. This study proposes an adaptive forgetting factor for ORICA (adaptive ORICA) to learn and adapt to non-stationarity in the EEG data. Using a realistically simulated non-stationary EEG dataset, we empirically show adaptive forgetting factors outperform other commonly-used non-adaptive rules when underlying source dynamics are changing. Standard offline ICA can only extract a subset of the changing sources while adaptive ORICA can recover all. Applied to actual EEG data recorded from a task-switching experiments, adaptive ORICA can learn and re-learn the task-related components as they change. With an adaptive forgetting factor, adaptive ORICA can track non-stationary EEG sources, opening many new online applications in brain-computer interfaces and in monitoring of brain dynamics.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wei201526737815,
  title = {Toward non-hair-bearing brain-computer interfaces for neurocognitive lapse detection.},
  author = {Wei, CS and Wang, YT and Lin, CT and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7319915},
  pmid = {26737815},
  url = {https://pubmed.ncbi.nlm.nih.gov/26737815/},
  abstract = {Recent advances in mobile electroencephalogram (EEG) acquisition based on dry electrodes have started moving Brain-Computer Interface (BCI) applications from well-controlled laboratory settings to real-world environments. However, the application mechanisms and high impedance of dry electrodes over the hair-covered areas remain challenging for everyday use of BCI. In addition, whole-scalp recordings are not always necessary or applicable due to various practical constrains. Therefore, alternative montages for EEG recordings to meet the everyday needs are in-demand. Inspired by our previous work on measuring non-hair-bearing steady state visual evoked potentials for BCI applications, this study explores the feasibility and efficacy of detecting cognitive lapses of participants based on EEG signals collected from the non-hair-bearing areas. Study results suggest that informative EEG features associated with lapses could be assessed from non-hair-bearing areas with comparable accuracy obtained from the whole-scalp EEG. The design principles, validation processes and promising findings reported in this study may enable and/or facilitate numerous BCI applications in real-world environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cao201526431430,
  title = {The Global Cognition, Frontal Lobe Dysfunction and Behavior Changes in Chinese Patients with Multiple System Atrophy.},
  author = {Cao, B and Zhao, B and Wei, QQ and Chen, K and Yang, J and Ou, R and Wu, Y and Shang, HF},
  journal = {PloS one},
  year = {2015},
  doi = {10.1371/journal.pone.0139773},
  pmid = {26431430},
  url = {https://pubmed.ncbi.nlm.nih.gov/26431430/},
  abstract = {Studies on cognition in multiple system atrophy (MSA) patients are limited. A total of 110 MSA patients were evaluated using Addenbrooke's Cognitive Examination-Revised (ACE-R), Frontal Assessment Battery (FAB), Frontal Behavioral Inventory (FBI), and Unified MSA Rating Scale (UMSARS) tests. Fifty-five age-, sex-, education- and domicile-matched healthy controls were recruited to perform the FAB and ACE-R scales. Approximately 32.7% of the patients had global cognitive deficits with the most impaired domain being verbal fluency and visuospatial ability (26.4%), followed by memory (24.5%), language (20%) and orientation/attention (20%) based on a cut-off score of ACE-R ≤ 70. A total of 41.6% of the patients had frontal lobe dysfunction, with inhibitory control (60.9%) as the most impaired domain based on a cut-off score of FAB ≤14. Most patients (57.2%) showed moderate frontal behavior changes (FBI score 4-15), with incontinence (64.5%) as the most impaired domain. The binary logistic regression model revealed that an education level < 9 years (OR:13.312, 95% CI:2.931-60.469, P = 0.001) and UMSARS ≥ 40 (OR: 2.444, 95%CI: 1.002-5.962, P< 0.049) were potential determinants of abnormal ACE-R, while MSA-C (OR: 4.326, 95%CI: 1.631-11.477, P = 0.003), an education level < 9 years (OR:2.809 95% CI:1.060-7.444, P = 0.038) and UMSARS ≥ 40 (OR:5.396, 95%CI: 2.103-13.846, P < 0.0001) were potential determinants of abnormal FAB. Cognitive impairment is common in Chinese MSA patients. MSA-C patients with low education levels and severe motor symptoms are likely to experience frontal lobe dysfunction, while MSA patients with low education levels and severe motor symptoms are likely to experience global cognitive deficits. These findings strongly suggest that cognitive impairment should not be an exclusion criterion for the diagnosis of MSA.},
  note = {PubMed query source: Ying Wu}
}

@article{Balkan201526737184,
  title = {Source-domain spectral EEG analysis of sports-related concussion via Measure Projection Analysis.},
  author = {Balkan, O and Virji-Babul, N and Miyakoshi, M and Makeig, S and Garudadri, H},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7319284},
  pmid = {26737184},
  url = {https://pubmed.ncbi.nlm.nih.gov/26737184/},
  abstract = {Here, we investigated EEG-based source-level spectral differences between adolescents with sports-related concussions and healthy age matched controls. We transformed resting state EEG collected in both groups to the source domain using Independent Component Analysis (ICA) and computed the component process power spectra. For group-level analysis in the source domain, we used a probabilistic framework, Measure Projection Analysis (MPA), that has advantages over parametric k-means clustering of brain sources. MPA revealed that some frontal brain sources in the concussed group had significantly more power in the beta band (p<;0.005) and significantly less delta (p<;0.01) and theta band power (p<;0.05) than the healthy control group. These results suggest that a shift in spectral profile toward higher frequencies in some frontal brain regions might distinguish individuals with concussion from healthy controls.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gola201526586811,
  title = {Sex, Impulsivity, and Anxiety: Interplay between Ventral Striatum and Amygdala Reactivity in Sexual Behaviors.},
  author = {Gola, M and Miyakoshi, M and Sescousse, G},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2015},
  doi = {10.1523/JNEUROSCI.3273-15.2015},
  pmid = {26586811},
  url = {https://pubmed.ncbi.nlm.nih.gov/26586811/},
  note = {PubMed query source: Mateusz Gola}
}

@article{PionTonachini201526737199,
  title = {Real-time EEG Source-mapping Toolbox (REST): Online ICA and source localization.},
  author = {Pion-Tonachini, L and Hsu, SH and Makeig, S and Jung, TP and Cauwenberghs, G},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7319299},
  pmid = {26737199},
  url = {https://pubmed.ncbi.nlm.nih.gov/26737199/},
  abstract = {The Electroencephalogram (EEG) is a noninvasive functional brain activity recording method that shows promise for becoming a 3-D cortical imaging modality with high temporal resolution. Currently, most of the tools developed for EEG analysis focus mainly on offline processing. This study introduces and demonstrates the Real-time EEG Source-mapping Toolbox (REST), an extension to the widely distributed EEGLAB environment. REST allows blind source separation of EEG data in real-time using Online Recursive Independent Component Analysis (ORICA), plus near real-time localization of separated sources. Two source localization methods are available to fit equivalent current dipoles or estimate spatial source distributions of selected sources. Selected measures of raw EEG data or component activations (e.g. time series of the data, spectral changes over time, equivalent current dipoles, etc.) can be visualized in near real-time. Finally, this study demonstrates the accuracy and functionality of REST with data from two experiments and discusses some relevant applications.},
  note = {PubMed query source: Scott Makeig}
}

@article{Mullen201526415149,
  title = {Real-Time Neuroimaging and Cognitive Monitoring Using Wearable Dry EEG.},
  author = {Mullen, TR and Kothe, CA and Chi, YM and Ojeda, A and Kerth, T and Makeig, S and Jung, TP and Cauwenberghs, G},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2015},
  doi = {10.1109/TBME.2015.2481482},
  pmid = {26415149},
  url = {https://pubmed.ncbi.nlm.nih.gov/26415149/},
  abstract = {We present and evaluate a wearable high-density dry-electrode EEG system and an open-source software framework for online neuroimaging and state classification. The system integrates a 64-channel dry EEG form factor with wireless data streaming for online analysis. A real-time software framework is applied, including adaptive artifact rejection, cortical source localization, multivariate effective connectivity inference, data visualization, and cognitive state classification from connectivity features using a constrained logistic regression approach (ProxConn). We evaluate the system identification methods on simulated 64-channel EEG data. Then, we evaluate system performance, using ProxConn and a benchmark ERP method, in classifying response errors in nine subjects using the dry EEG system. Simulations yielded high accuracy (AUC = 0.97 ± 0.021) for real-time cortical connectivity estimation. Response error classification using cortical effective connectivity [short-time direct-directed transfer function (sdDTF)] was significantly above chance with similar performance (AUC) for cLORETA (0.74 ±0.09) and LCMV (0.72 ±0.08) source localization. Cortical ERP-based classification was equivalent to ProxConn for cLORETA (0.74 ±0.16) but significantly better for LCMV (0.82 ±0.12) . We demonstrated the feasibility for real-time cortical connectivity analysis and cognitive state classification from high-density wearable dry EEG. This paper is the first validated application of these methods to 64-channel dry EEG. This study addresses a need for robust real-time measurement and interpretation of complex brain activity in the dynamic environment of the wearable setting. Such advances can have broad impact in research, medicine, and brain-computer interfaces. The pipelines are made freely available in the open-source SIFT and BCILAB toolboxes.},
  note = {PubMed query source: Scott Makeig}
}

@article{Durantin201526834607,
  title = {Processing Functional Near Infrared Spectroscopy Signal with a Kalman Filter to Assess Working Memory during Simulated Flight.},
  author = {Durantin, G and Scannella, S and Gateau, T and Delorme, A and Dehais, F},
  journal = {Frontiers in human neuroscience},
  year = {2015},
  doi = {10.3389/fnhum.2015.00707},
  pmid = {26834607},
  url = {https://pubmed.ncbi.nlm.nih.gov/26834607/},
  abstract = {Working memory (WM) is a key executive function for operating aircraft, especially when pilots have to recall series of air traffic control instructions. There is a need to implement tools to monitor WM as its limitation may jeopardize flight safety. An innovative way to address this issue is to adopt a Neuroergonomics approach that merges knowledge and methods from Human Factors, System Engineering, and Neuroscience. A challenge of great importance for Neuroergonomics is to implement efficient brain imaging techniques to measure the brain at work and to design Brain Computer Interfaces (BCI). We used functional near infrared spectroscopy as it has been already successfully tested to measure WM capacity in complex environment with air traffic controllers (ATC), pilots, or unmanned vehicle operators. However, the extraction of relevant features from the raw signal in ecological environment is still a critical issue due to the complexity of implementing real-time signal processing techniques without a priori knowledge. We proposed to implement the Kalman filtering approach, a signal processing technique that is efficient when the dynamics of the signal can be modeled. We based our approach on the Boynton model of hemodynamic response. We conducted a first experiment with nine participants involving a basic WM task to estimate the noise covariances of the Kalman filter. We then conducted a more ecological experiment in our flight simulator with 18 pilots who interacted with ATC instructions (two levels of difficulty). The data was processed with the same Kalman filter settings implemented in the first experiment. This filter was benchmarked with a classical pass-band IIR filter and a Moving Average Convergence Divergence (MACD) filter. Statistical analysis revealed that the Kalman filter was the most efficient to separate the two levels of load, by increasing the observed effect size in prefrontal areas involved in WM. In addition, the use of a Kalman filter increased the performance of the classification of WM levels based on brain signal. The results suggest that Kalman filter is a suitable approach for real-time improvement of near infrared spectroscopy signal in ecological situations and the development of BCI.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lee201526738014,
  title = {Non-parametric group-level statistics for source-resolved ERP analysis.},
  author = {Lee, C and Miyakoshi, M and Delorme, A and Cauwenberghs, G and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7320114},
  pmid = {26738014},
  url = {https://pubmed.ncbi.nlm.nih.gov/26738014/},
  abstract = {We have developed a new statistical framework for group-level event-related potential (ERP) analysis in EEGLAB. The framework calculates the variance of scalp channel signals accounted for by the activity of homogeneous clusters of sources found by independent component analysis (ICA). When ICA data decomposition is performed on each subject's data separately, functionally equivalent ICs can be grouped into EEGLAB clusters. Here, we report a new addition (statPvaf) to the EEGLAB plug-in std_envtopo to enable inferential statistics on main effects and interactions in event related potentials (ERPs) of independent component (IC) processes at the group level. We demonstrate the use of the updated plug-in on simulated and actual EEG data.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lin201525666500,
  title = {Neural correlates of mathematical problem solving.},
  author = {Lin, CL and Jung, M and Wu, YC and She, HC and Jung, TP},
  journal = {International journal of neural systems},
  year = {2015},
  doi = {10.1142/S0129065715500045},
  pmid = {25666500},
  url = {https://pubmed.ncbi.nlm.nih.gov/25666500/},
  abstract = {This study explores electroencephalography (EEG) brain dynamics associated with mathematical problem solving. EEG and solution latencies (SLs) were recorded as 11 neurologically healthy volunteers worked on intellectually challenging math puzzles that involved combining four single-digit numbers through basic arithmetic operators (addition, subtraction, division, multiplication) to create an arithmetic expression equaling 24. Estimates of EEG spectral power were computed in three frequency bands - θ (4-7 Hz), α (8-13 Hz) and β (14-30 Hz) - over a widely distributed montage of scalp electrode sites. The magnitude of power estimates was found to change in a linear fashion with SLs - that is, relative to a base of power spectrum, theta power increased with longer SLs, while alpha and beta power tended to decrease. Further, the topographic distribution of spectral fluctuations was characterized by more pronounced asymmetries along the left-right and anterior-posterior axes for solutions that involved a longer search phase. These findings reveal for the first time the topography and dynamics of EEG spectral activities important for sustained solution search during arithmetical problem solving.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu201526381507,
  title = {Iconic Gestures Facilitate Discourse Comprehension in Individuals With Superior Immediate Memory for Body Configurations.},
  author = {Wu, YC and Coulson, S},
  journal = {Psychological science},
  year = {2015},
  doi = {10.1177/0956797615597671},
  pmid = {26381507},
  url = {https://pubmed.ncbi.nlm.nih.gov/26381507/},
  abstract = {To understand a speaker's gestures, people may draw on kinesthetic working memory (KWM)-a system for temporarily remembering body movements. The present study explored whether sensitivity to gesture meaning was related to differences in KWM capacity. KWM was evaluated through sequences of novel movements that participants viewed and reproduced with their own bodies. Gesture sensitivity was assessed through a priming paradigm. Participants judged whether multimodal utterances containing congruent, incongruent, or no gestures were related to subsequent picture probes depicting the referents of those utterances. Individuals with low KWM were primarily inhibited by incongruent speech-gesture primes, whereas those with high KWM showed facilitation-that is, they were able to identify picture probes more quickly when preceded by congruent speech and gestures than by speech alone. Group differences were most apparent for discourse with weakly congruent speech and gestures. Overall, speech-gesture congruency effects were positively correlated with KWM abilities, which may help listeners match spatial properties of gestures to concepts evoked by speech.},
  note = {PubMed query source: Ying Wu}
}

@article{Chen201526483479,
  title = {High-speed spelling with a noninvasive brain-computer interface.},
  author = {Chen, X and Wang, Y and Nakanishi, M and Gao, X and Jung, TP and Gao, S},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  year = {2015},
  doi = {10.1073/pnas.1508080112},
  pmid = {26483479},
  url = {https://pubmed.ncbi.nlm.nih.gov/26483479/},
  abstract = {The past 20 years have witnessed unprecedented progress in brain-computer interfaces (BCIs). However, low communication rates remain key obstacles to BCI-based communication in humans. This study presents an electroencephalogram-based BCI speller that can achieve information transfer rates (ITRs) up to 5.32 bits per second, the highest ITRs reported in BCI spellers using either noninvasive or invasive methods. Based on extremely high consistency of frequency and phase observed between visual flickering signals and the elicited single-trial steady-state visual evoked potentials, this study developed a synchronous modulation and demodulation paradigm to implement the speller. Specifically, this study proposed a new joint frequency-phase modulation method to tag 40 characters with 0.5-s-long flickering signals and developed a user-specific target identification algorithm using individual calibration data. The speller achieved high ITRs in online spelling tasks. This study demonstrates that BCIs can provide a truly naturalistic high-speed communication channel using noninvasively recorded brain activities.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Delorme201525447029,
  title = {Grand average ERP-image plotting and statistics: A method for comparing variability in event-related single-trial EEG activities across subjects and conditions.},
  author = {Delorme, A and Miyakoshi, M and Jung, TP and Makeig, S},
  journal = {Journal of neuroscience methods},
  year = {2015},
  doi = {10.1016/j.jneumeth.2014.10.003},
  pmid = {25447029},
  url = {https://pubmed.ncbi.nlm.nih.gov/25447029/},
  abstract = {With the advent of modern computing methods, modeling trial-to-trial variability in biophysical recordings including electroencephalography (EEG) has become of increasingly interest. Yet no widely used method exists for comparing variability in ordered collections of single-trial data epochs across conditions and subjects. We have developed a method based on an ERP-image visualization tool in which potential, spectral power, or some other measure at each time point in a set of event-related single-trial data epochs are represented as color coded horizontal lines that are then stacked to form a 2-D colored image. Moving-window smoothing across trial epochs can make otherwise hidden event-related features in the data more perceptible. Stacking trials in different orders, for example ordered by subject reaction time, by context-related information such as inter-stimulus interval, or some other characteristic of the data (e.g., latency-window mean power or phase of some EEG source) can reveal aspects of the multifold complexities of trial-to-trial EEG data variability. This study demonstrates new methods for computing and visualizing 'grand' ERP-image plots across subjects and for performing robust statistical testing on the resulting images. These methods have been implemented and made freely available in the EEGLAB signal-processing environment that we maintain and distribute.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Chen201526035476,
  title = {Filter bank canonical correlation analysis for implementing a high-speed SSVEP-based brain-computer interface.},
  author = {Chen, X and Wang, Y and Gao, S and Jung, TP and Gao, X},
  journal = {Journal of neural engineering},
  year = {2015},
  doi = {10.1088/1741-2560/12/4/046008},
  pmid = {26035476},
  url = {https://pubmed.ncbi.nlm.nih.gov/26035476/},
  abstract = {Recently, canonical correlation analysis (CCA) has been widely used in steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) due to its high efficiency, robustness, and simple implementation. However, a method with which to make use of harmonic SSVEP components to enhance the CCA-based frequency detection has not been well established. This study proposed a filter bank canonical correlation analysis (FBCCA) method to incorporate fundamental and harmonic frequency components to improve the detection of SSVEPs. A 40-target BCI speller based on frequency coding (frequency range: 8-15.8 Hz, frequency interval: 0.2 Hz) was used for performance evaluation. To optimize the filter bank design, three methods (M1: sub-bands with equally spaced bandwidths; M2: sub-bands corresponding to individual harmonic frequency bands; M3: sub-bands covering multiple harmonic frequency bands) were proposed for comparison. Classification accuracy and information transfer rate (ITR) of the three FBCCA methods and the standard CCA method were estimated using an offline dataset from 12 subjects. Furthermore, an online BCI speller adopting the optimal FBCCA method was tested with a group of 10 subjects. The FBCCA methods significantly outperformed the standard CCA method. The method M3 achieved the highest classification performance. At a spelling rate of ∼33.3 characters/min, the online BCI speller obtained an average ITR of 151.18 ± 20.34 bits min(-1). By incorporating the fundamental and harmonic SSVEP components in target identification, the proposed FBCCA method significantly improves the performance of the SSVEP-based BCI, and thereby facilitates its practical applications such as high-speed spelling.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chou201526039885,
  title = {Explore the Functional Connectivity between Brain Regions during a Chemistry Working Memory Task.},
  author = {Chou, WC and Duann, JR and She, HC and Huang, LY and Jung, TP},
  journal = {PloS one},
  year = {2015},
  doi = {10.1371/journal.pone.0129019},
  pmid = {26039885},
  url = {https://pubmed.ncbi.nlm.nih.gov/26039885/},
  abstract = {Previous studies have rarely examined how temporal dynamic patterns, event-related coherence, and phase-locking are related to each other. This study assessed reaction-time-sorted spectral perturbation and event-related spectral perturbation in order to examine the temporal dynamic patterns in the frontal midline (F), central parietal (CP), and occipital (O) regions during a chemistry working memory task at theta, alpha, and beta frequencies. Furthermore, the functional connectivity between F-CP, CP-O, and F-O were assessed by component event-related coherence (ERCoh) and component phase-locking (PL) at different frequency bands. In addition, this study examined whether the temporal dynamic patterns are consistent with the functional connectivity patterns across different frequencies and time courses. Component ERCoh/PL measured the interactions between different independent components decomposed from the scalp EEG, mixtures of time courses of activities arising from different brain, and artifactual sources. The results indicate that the O and CP regions' temporal dynamic patterns are similar to each other. Furthermore, pronounced component ERCoh/PL patterns were found to exist between the O and CP regions across each stimulus and probe presentation, in both theta and alpha frequencies. The consistent theta component ERCoh/PL between the F and O regions was found at the first stimulus and after probe presentation. These findings demonstrate that temporal dynamic patterns at different regions are in accordance with the functional connectivity patterns. Such coordinated and robust EEG temporal dynamics and component ERCoh/PL patterns suggest that these brain regions' neurons work together both to induce similar event-related spectral perturbation and to synchronize or desynchronize simultaneously in order to swiftly accomplish a particular goal. The possible mechanisms for such distinct component phase-locking and coherence patterns were also further discussed.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wierzba201526441715,
  title = {Erotic subset for the Nencki Affective Picture System (NAPS ERO): cross-sexual comparison study.},
  author = {Wierzba, M and Riegel, M and Pucz, A and Leśniewska, Z and Dragan, WŁ and Gola, M and Jednoróg, K and Marchewka, A},
  journal = {Frontiers in psychology},
  year = {2015},
  doi = {10.3389/fpsyg.2015.01336},
  pmid = {26441715},
  url = {https://pubmed.ncbi.nlm.nih.gov/26441715/},
  abstract = {Research on the processing of sexual stimuli has proved that such material has high priority in human cognition. Yet, although sex differences in response to sexual stimuli were extensively discussed in the literature, sexual orientation was given relatively little consideration, and material suitable for relevant research is difficult to come by. With this in mind, we present a collection of 200 erotic images, accompanied by their self-report ratings of emotional valence and arousal by homo- and heterosexual males and females (n = 80, divided into four equal-sized subsamples). The collection complements the Nencki Affective Picture System (NAPS) and is intended to be used as stimulus material in experimental research. The erotic images are divided into five categories, depending on their content: opposite-sex couple (50), male couple (50), female couple (50), male (25) and female (25). Additional 100 control images from the NAPS depicting people in a non-erotic context were also used in the study. We showed that recipient sex and sexual orientation strongly influenced the evaluation of erotic content. Thus, comparisons of valence and arousal ratings in different subject groups will help researchers select stimuli set for the purpose of various experimental designs. To facilitate the use of the dataset, we provide an on-line tool, which allows the user to browse the images interactively and select proper stimuli on the basis of several parameters. The NAPS ERO image collection together with the data are available to the scientific community for non-commercial use at http://naps.nencki.gov.pl.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Light201525524305,
  title = {Electroencephalographic biomarkers of psychosis: present and future.},
  author = {Light, GA and Makeig, S},
  journal = {Biological psychiatry},
  year = {2015},
  doi = {10.1016/j.biopsych.2014.11.002},
  pmid = {25524305},
  url = {https://pubmed.ncbi.nlm.nih.gov/25524305/},
  note = {PubMed query source: Scott Makeig}
}

@article{Wang201525850090,
  title = {EEG-Based Attention Tracking During Distracted Driving.},
  author = {Wang, YK and Jung, TP and Lin, CT},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2015},
  doi = {10.1109/TNSRE.2015.2415520},
  pmid = {25850090},
  url = {https://pubmed.ncbi.nlm.nih.gov/25850090/},
  abstract = {Distracted driving might lead to many catastrophic consequences. Developing a countermeasure to track drivers' focus of attention (FOA) and engagement of operators in dual (multi)-tasking conditions is thus imperative. Ten healthy volunteers participated in a dual-task experiment that comprised two tasks: a lane-keeping driving task and a mathematical problem-solving task (e.g., 24+15=37?) during which their electroencephalogram (EEG) and behaviors were concurrently recorded. Independent component analysis (ICA) was employed as a spatial filter to separate the contributions of independent sources from the recorded EEG data. The power spectra of six components (i.e., frontal, central, parietal, occipital, left motor, and right motor) extracted from single-task conditions were fed into support vector machine (SVM) based on the radial basis function (RBF) kernel to build an FOA assessment system. The system achieved 84.6±5.8% and 86.2±5.4% classification accuracies in detecting the participants' FOAs on the math versus driving tasks, respectively. This FOA assessment system was then applied to evaluate participants' FOAs during dual-task conditions. The detected FOAs revealed that participants' cognitive attention and strategies dynamically changed between tasks to optimize the overall performance, as attention was limited and competed. The empirical results of this study demonstrate the feasibility of a practical system to continuously estimating cognitive attention through EEG spectra.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Liao201525731992,
  title = {EEG imaging of toddlers during dyadic turn-taking: Mu-rhythm modulation while producing or observing social actions.},
  author = {Liao, Y and Acar, ZA and Makeig, S and Deak, G},
  journal = {NeuroImage},
  year = {2015},
  doi = {10.1016/j.neuroimage.2015.02.055},
  pmid = {25731992},
  url = {https://pubmed.ncbi.nlm.nih.gov/25731992/},
  abstract = {Contemporary active-EEG and EEG-imaging methods show particular promise for studying the development of action planning and social-action representation in infancy and early childhood. Action-related mu suppression was measured in eleven 3-year-old children and their mothers during a 'live,' largely unscripted social interaction. High-density EEG was recorded from children and synchronized with motion-captured records of children's and mothers' hand actions, and with video recordings. Independent Component Analysis (ICA) was used to separate brain and non-brain source signals in toddlers' EEG records. EEG source dynamics were compared across three kinds of epochs: toddlers' own actions (execution), mothers' actions (observation), and between-turn intervals (no action). Mu (6-9Hz) power was suppressed in left and right somatomotor cortex during both action execution and observation, as reflected by independent components of individual children's EEG data. These mu rhythm components were accompanied by beta-harmonic (~16Hz) suppression, similar to findings from adults. The toddlers' power spectrum and scalp density projections provide converging evidence of adult-like mu-suppression features. Mu-suppression components' source locations were modeled using an age-specific 4-layer forward head model. Putative sources clustered around somatosensory cortex, near the hand/arm region. The results demonstrate that action-locked, event-related EEG dynamics can be measured, and source-resolved, from toddlers during social interactions with relatively unrestricted social behaviors.},
  note = {PubMed query source: Scott Makeig}
}

@article{Joshi201526131930,
  title = {Directional dominance on stature and cognition in diverse human populations.},
  author = {Joshi, PK and Esko, T and Mattsson, H and Eklund, N and Gandin, I and Nutile, T and Jackson, AU and Schurmann, C and Smith, AV and Zhang, W and Okada, Y and Stančáková, A and Faul, JD and Zhao, W and Bartz, TM and Concas, MP and Franceschini, N and Enroth, S and Vitart, V and Trompet, S and Guo, X and Chasman, DI and O'Connel, JR and Corre, T and Nongmaithem, SS and Chen, Y and Mangino, M and Ruggiero, D and Traglia, M and Farmaki, AE and Kacprowski, T and Bjonnes, A and van der Spek, A and Wu, Y and Giri, AK and Yanek, LR and Wang, L and Hofer, E and Rietveld, CA and McLeod, O and Cornelis, MC and Pattaro, C and Verweij, N and Baumbach, C and Abdellaoui, A and Warren, HR and Vuckovic, D and Mei, H and Bouchard, C and Perry, JRB and Cappellani, S and Mirza, SS and Benton, MC and Broeckel, U and Medland, SE and Lind, PA and Malerba, G and Drong, A and Yengo, L and Bielak, LF and Zhi, D and van der Most, PJ and Shriner, D and Mägi, R and Hemani, G and Karaderi, T and Wang, Z and Liu, T and Demuth, I and Zhao, JH and Meng, W and Lataniotis, L and van der Laan, SW and Bradfield, JP and Wood, AR and Bonnefond, A and Ahluwalia, TS and Hall, LM and Salvi, E and Yazar, S and Carstensen, L and de Haan, HG and Abney, M and Afzal, U and Allison, MA and Amin, N and Asselbergs, FW and Bakker, SJL and Barr, RG and Baumeister, SE and Benjamin, DJ and Bergmann, S and Boerwinkle, E and Bottinger, EP and Campbell, A and Chakravarti, A and Chan, Y and Chanock, SJ and Chen, C and Chen, YI and Collins, FS and Connell, J and Correa, A and Cupples, LA and Smith, GD and Davies, G and Dörr, M and Ehret, G and Ellis, SB and Feenstra, B and Feitosa, MF and Ford, I and Fox, CS and Frayling, TM and Friedrich, N and Geller, F and Scotland, G and Gillham-Nasenya, I and Gottesman, O and Graff, M and Grodstein, F and Gu, C and Haley, C and Hammond, CJ and Harris, SE and Harris, TB and Hastie, ND and Heard-Costa, NL and Heikkilä, K and Hocking, LJ and Homuth, G and Hottenga, JJ and Huang, J and Huffman, JE and Hysi, PG and Ikram, MA and Ingelsson, E and Joensuu, A and Johansson, Å and Jousilahti, P and Jukema, JW and Kähönen, M and Kamatani, Y and Kanoni, S and Kerr, SM and Khan, NM and Koellinger, P and Koistinen, HA and Kooner, MK and Kubo, M and Kuusisto, J and Lahti, J and Launer, LJ and Lea, RA and Lehne, B and Lehtimäki, T and Liewald, DCM and Lind, L and Loh, M and Lokki, ML and London, SJ and Loomis, SJ and Loukola, A and Lu, Y and Lumley, T and Lundqvist, A and Männistö, S and Marques-Vidal, P and Masciullo, C and Matchan, A and Mathias, RA and Matsuda, K and Meigs, JB and Meisinger, C and Meitinger, T and Menni, C and Mentch, FD and Mihailov, E and Milani, L and Montasser, ME and Montgomery, GW and Morrison, A and Myers, RH and Nadukuru, R and Navarro, P and Nelis, M and Nieminen, MS and Nolte, IM and O'Connor, GT and Ogunniyi, A and Padmanabhan, S and Palmas, WR and Pankow, JS and Patarcic, I and Pavani, F and Peyser, PA and Pietilainen, K and Poulter, N and Prokopenko, I and Ralhan, S and Redmond, P and Rich, SS and Rissanen, H and Robino, A and Rose, LM and Rose, R and Sala, C and Salako, B and Salomaa, V and Sarin, AP and Saxena, R and Schmidt, H and Scott, LJ and Scott, WR and Sennblad, B and Seshadri, S and Sever, P and Shrestha, S and Smith, BH and Smith, JA and Soranzo, N and Sotoodehnia, N and Southam, L and Stanton, AV and Stathopoulou, MG and Strauch, K and Strawbridge, RJ and Suderman, MJ and Tandon, N and Tang, ST and Taylor, KD and Tayo, BO and Töglhofer, AM and Tomaszewski, M and Tšernikova, N and Tuomilehto, J and Uitterlinden, AG and Vaidya, D and van Hylckama Vlieg, A and van Setten, J and Vasankari, T and Vedantam, S and Vlachopoulou, E and Vozzi, D and Vuoksimaa, E and Waldenberger, M and Ware, EB and Wentworth-Shields, W and Whitfield, JB and Wild, S and Willemsen, G and Yajnik, CS and Yao, J and Zaza, G and Zhu, X and Project, TBJ and Salem, RM and Melbye, M and Bisgaard, H and Samani, NJ and Cusi, D and Mackey, DA and Cooper, RS and Froguel, P and Pasterkamp, G and Grant, SFA and Hakonarson, H and Ferrucci, L and Scott, RA and Morris, AD and Palmer, CNA and Dedoussis, G and Deloukas, P and Bertram, L and Lindenberger, U and Berndt, SI and Lindgren, CM and Timpson, NJ and Tönjes, A and Munroe, PB and Sørensen, TIA and Rotimi, CN and Arnett, DK and Oldehinkel, AJ and Kardia, SLR and Balkau, B and Gambaro, G and Morris, AP and Eriksson, JG and Wright, MJ and Martin, NG and Hunt, SC and Starr, JM and Deary, IJ and Griffiths, LR and Tiemeier, H and Pirastu, N and Kaprio, J and Wareham, NJ and Pérusse, L and Wilson, JG and Girotto, G and Caulfield, MJ and Raitakari, O and Boomsma, DI and Gieger, C and van der Harst, P and Hicks, AA and Kraft, P and Sinisalo, J and Knekt, P and Johannesson, M and Magnusson, PKE and Hamsten, A and Schmidt, R and Borecki, IB and Vartiainen, E and Becker, DM and Bharadwaj, D and Mohlke, KL and Boehnke, M and van Duijn, CM and Sanghera, DK and Teumer, A and Zeggini, E and Metspalu, A and Gasparini, P and Ulivi, S and Ober, C and Toniolo, D and Rudan, I and Porteous, DJ and Ciullo, M and Spector, TD and Hayward, C and Dupuis, J and Loos, RJF and Wright, AF and Chandak, GR and Vollenweider, P and Shuldiner, A and Ridker, PM and Rotter, JI and Sattar, N and Gyllensten, U and North, KE and Pirastu, M and Psaty, BM and Weir, DR and Laakso, M and Gudnason, V and Takahashi, A and Chambers, JC and Kooner, JS and Strachan, DP and Campbell, H and Hirschhorn, JN and Perola, M and Polašek, O and Wilson, JF},
  journal = {Nature},
  year = {2015},
  doi = {10.1038/nature14618},
  pmid = {26131930},
  url = {https://pubmed.ncbi.nlm.nih.gov/26131930/},
  abstract = {Homozygosity has long been associated with rare, often devastating, Mendelian disorders, and Darwin was one of the first to recognize that inbreeding reduces evolutionary fitness. However, the effect of the more distant parental relatedness that is common in modern human populations is less well understood. Genomic data now allow us to investigate the effects of homozygosity on traits of public health importance by observing contiguous homozygous segments (runs of homozygosity), which are inferred to be homozygous along their complete length. Given the low levels of genome-wide homozygosity prevalent in most human populations, information is required on very large numbers of people to provide sufficient power. Here we use runs of homozygosity to study 16 health-related quantitative traits in 354,224 individuals from 102 cohorts, and find statistically significant associations between summed runs of homozygosity and four complex traits: height, forced expiratory lung volume in one second, general cognitive ability and educational attainment (P < 1 × 10(-300), 2.1 × 10(-6), 2.5 × 10(-10) and 1.8 × 10(-10), respectively). In each case, increased homozygosity was associated with decreased trait value, equivalent to the offspring of first cousins being 1.2 cm shorter and having 10 months' less education. Similar effect sizes were found across four continental groups and populations with different degrees of genome-wide homozygosity, providing evidence that homozygosity, rather than confounding, directly contributes to phenotypic variance. Contrary to earlier reports in substantially smaller samples, no evidence was seen of an influence of genome-wide homozygosity on blood pressure and low density lipoprotein cholesterol, or ten other cardio-metabolic traits. Since directional dominance is predicted for traits under directional evolutionary selection, this study provides evidence that increased stature and cognitive function have been positively selected in human evolution, whereas many important risk factors for late-onset complex diseases may not have been.},
  note = {PubMed query source: Ying Wu}
}

@article{Wang201526736745,
  title = {Developing an online steady-state visual evoked potential-based brain-computer interface system using EarEEG.},
  author = {Wang, YT and Nakanishi, M and Kappel, SL and Kidmose, P and Mandic, DP and Wang, Y and Cheng, CK and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7318845},
  pmid = {26736745},
  url = {https://pubmed.ncbi.nlm.nih.gov/26736745/},
  abstract = {The purpose of this study is to demonstrate an online steady-state visual evoked potential (SSVEP)-based BCI system using EarEEG. EarEEG is a novel recording concept where electrodes are embedded on the surface of earpieces customized to the individual anatomical shape of users' ear. It has been shown that the EarEEG can be used to record SSVEPs in previous studies. However, a long distance between the visual cortex and the ear makes the signal-to-noise ratio (SNR) of SSVEPs acquired by the EarEEG relatively low. Recently, filter bank- and training data-based canonical correlation analysis algorithms have shown significant performance improvement in terms of accuracy of target detection and information transfer rate (ITR). This study implemented an online four-class SSVEP-based BCI system using EarEEG. Four subjects participated in offline and online BCI experiments. For the offline classification, an average accuracy of 82.71±11.83 % was obtained using 4 sec-long SSVEPs acquired from earpieces. In the online experiment, all subjects successfully completed the tasks with an average accuracy of 87.92±12.10 %, leading to an average ITR of 16.60±6.55 bits/min. The results suggest that EarEEG can be used to perform practical BCI applications. The EarEEG has the potential to be used as a portable EEG recordings platform, that could enable real-world BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Yousefi201526440445,
  title = {Detecting glaucomatous change in visual fields: Analysis with an optimization framework.},
  author = {Yousefi, S and Goldbaum, MH and Varnousfaderani, ES and Belghith, A and Jung, TP and Medeiros, FA and Zangwill, LM and Weinreb, RN and Liebmann, JM and Girkin, CA and Bowd, C},
  journal = {Journal of biomedical informatics},
  year = {2015},
  doi = {10.1016/j.jbi.2015.09.019},
  pmid = {26440445},
  url = {https://pubmed.ncbi.nlm.nih.gov/26440445/},
  abstract = {Detecting glaucomatous progression is an important aspect of glaucoma management. The assessment of longitudinal series of visual fields, measured using Standard Automated Perimetry (SAP), is considered the reference standard for this effort. We seek efficient techniques for determining progression from longitudinal visual fields by formulating the problem as an optimization framework, learned from a population of glaucoma data. The longitudinal data from each patient's eye were used in a convex optimization framework to find a vector that is representative of the progression direction of the sample population, as a whole. Post-hoc analysis of longitudinal visual fields across the derived vector led to optimal progression (change) detection. The proposed method was compared to recently described progression detection methods and to linear regression of instrument-defined global indices, and showed slightly higher sensitivities at the highest specificities than other methods (a clinically desirable result). The proposed approach is simpler, faster, and more efficient for detecting glaucomatous changes, compared to our previously proposed machine learning-based methods, although it provides somewhat less information. This approach has potential application in glaucoma clinics for patient monitoring and in research centers for classification of study participants.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Yeung201526737936,
  title = {Comparison of foam-based and spring-loaded dry EEG electrodes with wet electrodes in resting and moving conditions.},
  author = {Yeung, A and Garudadri, H and Van Toen, C and Mercier, P and Balkan, O and Makeig, S and Virji-Babul, N},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2015},
  doi = {10.1109/EMBC.2015.7320036},
  pmid = {26737936},
  url = {https://pubmed.ncbi.nlm.nih.gov/26737936/},
  abstract = {The introduction of dry electrodes for EEG measurements has opened up possibilities of recording EEG outside of standard clinical environments by reducing required preparation and maintenance. However, the signal quality of dry electrodes in comparison with wet electrodes has not yet been evaluated under activities of daily life (ADL) or high motion tasks. In this study, we compared the performances of foam-based and spring-loaded dry electrodes with wet electrodes under three different task conditions: resting state, walking, and cycling. Our analysis showed that signals obtained by the 2 types of dry electrodes and obtained by wet electrodes displayed high correlation for all conditions, while being prone to similar environmental and electrode-based artifacts. Overall, our results suggest that dry electrodes have a similar signal quality in comparison to wet electrodes during motion and may be more practical for use in mobile and real-time motion applications due to their convenience. In addition, we conclude that as with wet electrodes, post-processing can mitigate motion artifacts in ambulatory EEG acquisition.},
  note = {PubMed query source: Scott Makeig}
}

@article{Durantin201525859190,
  title = {Characterization of mind wandering using fNIRS.},
  author = {Durantin, G and Dehais, F and Delorme, A},
  journal = {Frontiers in systems neuroscience},
  year = {2015},
  doi = {10.3389/fnsys.2015.00045},
  pmid = {25859190},
  url = {https://pubmed.ncbi.nlm.nih.gov/25859190/},
  abstract = {Assessing whether someone is attending to a task has become important for educational and professional applications. Such attentional drifts are usually termed mind wandering (MW). The purpose of the current study is to test to what extent a recent neural imaging modality can be used to detect MW episodes. Functional near infrared spectroscopy is a non-invasive neuroimaging technique that has never been used so far to measure MW. We used the Sustained Attention to Response Task (SART) to assess when subjects attention leaves a primary task. Sixteen-channel fNIRS data were collected over frontal cortices. We observed significant activations over the medial prefrontal cortex (mPFC) during MW, a brain region associated with the default mode network (DMN). fNIRS data were used to classify MW data above chance level. In line with previous brain-imaging studies, our results confirm the ability of fNIRS to detect Default Network activations in the context of MW.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Nakanishi201526479067,
  title = {A Comparison Study of Canonical Correlation Analysis Based Methods for Detecting Steady-State Visual Evoked Potentials.},
  author = {Nakanishi, M and Wang, Y and Wang, YT and Jung, TP},
  journal = {PloS one},
  year = {2015},
  doi = {10.1371/journal.pone.0140703},
  pmid = {26479067},
  url = {https://pubmed.ncbi.nlm.nih.gov/26479067/},
  abstract = {Canonical correlation analysis (CCA) has been widely used in the detection of the steady-state visual evoked potentials (SSVEPs) in brain-computer interfaces (BCIs). The standard CCA method, which uses sinusoidal signals as reference signals, was first proposed for SSVEP detection without calibration. However, the detection performance can be deteriorated by the interference from the spontaneous EEG activities. Recently, various extended methods have been developed to incorporate individual EEG calibration data in CCA to improve the detection performance. Although advantages of the extended CCA methods have been demonstrated in separate studies, a comprehensive comparison between these methods is still missing. This study performed a comparison of the existing CCA-based SSVEP detection methods using a 12-class SSVEP dataset recorded from 10 subjects in a simulated online BCI experiment. Classification accuracy and information transfer rate (ITR) were used for performance evaluation. The results suggest that individual calibration data can significantly improve the detection performance. Furthermore, the results showed that the combination method based on the standard CCA and the individual template based CCA (IT-CCA) achieved the highest performance.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Gramann201424994978,
  title = {Toward a new cognitive neuroscience: modeling natural brain dynamics.},
  author = {Gramann, K and Jung, TP and Ferris, DP and Lin, CT and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2014},
  doi = {10.3389/fnhum.2014.00444},
  pmid = {24994978},
  url = {https://pubmed.ncbi.nlm.nih.gov/24994978/},
  note = {PubMed query source: Scott Makeig}
}

@article{Tarasenko201425352811,
  title = {The auditory brain-stem response to complex sounds: a potential biomarker for guiding treatment of psychosis.},
  author = {Tarasenko, MA and Swerdlow, NR and Makeig, S and Braff, DL and Light, GA},
  journal = {Frontiers in psychiatry},
  year = {2014},
  doi = {10.3389/fpsyt.2014.00142},
  pmid = {25352811},
  url = {https://pubmed.ncbi.nlm.nih.gov/25352811/},
  abstract = {Cognitive deficits limit psychosocial functioning in schizophrenia. For many patients, cognitive remediation approaches have yielded encouraging results. Nevertheless, therapeutic response is variable, and outcome studies consistently identify individuals who respond minimally to these interventions. Biomarkers that can assist in identifying patients likely to benefit from particular forms of cognitive remediation are needed. Here, we describe an event-related potential (ERP) biomarker - the auditory brain-stem response (ABR) to complex sounds (cABR) - that appears to be particularly well-suited for predicting response to at least one form of cognitive remediation that targets auditory information processing. Uniquely, the cABR quantifies the fidelity of sound encoded at the level of the brainstem and midbrain. This ERP biomarker has revealed auditory processing abnormalities in various neurodevelopmental disorders, correlates with functioning across several cognitive domains, and appears to be responsive to targeted auditory training. We present preliminary cABR data from 18 schizophrenia patients and propose further investigation of this biomarker for predicting and tracking response to cognitive interventions.},
  note = {PubMed query source: Scott Makeig}
}

@article{Zhang201424801887,
  title = {Spatiotemporal sparse Bayesian learning with applications to compressed sensing of multichannel physiological signals.},
  author = {Zhang, Z and Jung, TP and Makeig, S and Pi, Z and Rao, BD},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2014},
  doi = {10.1109/TNSRE.2014.2319334},
  pmid = {24801887},
  url = {https://pubmed.ncbi.nlm.nih.gov/24801887/},
  abstract = {Energy consumption is an important issue in continuous wireless telemonitoring of physiological signals. Compressed sensing (CS) is a promising framework to address it, due to its energy-efficient data compression procedure. However, most CS algorithms have difficulty in data recovery due to nonsparsity characteristic of many physiological signals. Block sparse Bayesian learning (BSBL) is an effective approach to recover such signals with satisfactory recovery quality. However, it is time-consuming in recovering multichannel signals, since its computational load almost linearly increases with the number of channels. This work proposes a spatiotemporal sparse Bayesian learning algorithm to recover multichannel signals simultaneously. It not only exploits temporal correlation within each channel signal, but also exploits inter-channel correlation among different channel signals. Furthermore, its computational load is not significantly affected by the number of channels. The proposed algorithm was applied to brain computer interface (BCI) and EEG-based driver's drowsiness estimation. Results showed that the algorithm had both better recovery performance and much higher speed than BSBL. Particularly, the proposed algorithm ensured that the BCI classification and the drowsiness estimation had little degradation even when data were compressed by 80%, making it very suitable for continuous wireless telemonitoring of multichannel signals.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lin201424581119,
  title = {Revealing spatio-spectral electroencephalographic dynamics of musical mode and tempo perception by independent component analysis.},
  author = {Lin, YP and Duann, JR and Feng, W and Chen, JH and Jung, TP},
  journal = {Journal of neuroengineering and rehabilitation},
  year = {2014},
  doi = {10.1186/1743-0003-11-18},
  pmid = {24581119},
  url = {https://pubmed.ncbi.nlm.nih.gov/24581119/},
  abstract = {Music conveys emotion by manipulating musical structures, particularly musical mode- and tempo-impact. The neural correlates of musical mode and tempo perception revealed by electroencephalography (EEG) have not been adequately addressed in the literature. This study used independent component analysis (ICA) to systematically assess spatio-spectral EEG dynamics associated with the changes of musical mode and tempo. Empirical results showed that music with major mode augmented delta-band activity over the right sensorimotor cortex, suppressed theta activity over the superior parietal cortex, and moderately suppressed beta activity over the medial frontal cortex, compared to minor-mode music, whereas fast-tempo music engaged significant alpha suppression over the right sensorimotor cortex. The resultant EEG brain sources were comparable with previous studies obtained by other neuroimaging modalities, such as functional magnetic resonance imaging (fMRI) and positron emission tomography (PET). In conjunction with advanced dry and mobile EEG technology, the EEG results might facilitate the translation from laboratory-oriented research to real-life applications for music therapy, training and entertainment in naturalistic environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu201425571228,
  title = {Resting state and task-related brain dynamics supporting insight.},
  author = {Wu, YC and Jung, M and Lock, D and Chao, E and Swartz, J and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944860},
  pmid = {25571228},
  url = {https://pubmed.ncbi.nlm.nih.gov/25571228/},
  abstract = {Problems can be solved in a variety of ways. One might systematically evaluate a known space of possible solutions until the right one is found. Alternatively, it may prove necessary to enlarge or restructure the expected problem space - so called "thinking outside the box." This approach can yield an experience of unexpected insight or feeling of Aha!. Current challenges to understanding this phenomenon from a neurocognitive perspective include the vast diversity of problem domains and time scales for solutions. Whereas the subjective suddenness of an "Aha!" moment may lead to the impression that insight must be precipitated by a set of discrete, short-lived neural events, this report outlines research revealing that even before a problem is presented, scalp-recorded measures of resting or baseline brain states are linked with future performance and likelihood of experiencing insight during the search for a solution. Additionally, this study also shows that compared to more systematic problem solving approaches, insight is accompanied by differences in cortical and likely cognitive engagement that are detectable throughout much of the problem solving phase, rather than being confined to a distinct interval immediately preceding the dawn of a solution. These findings are important for the development of therapies targeting problem solving and reasoning skills, such as those used in cognitive training interventions to mitigate the effects of cognitive decline.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Artoni201425234117,
  title = {RELICA: a method for estimating the reliability of independent components.},
  author = {Artoni, F and Menicucci, D and Delorme, A and Makeig, S and Micera, S},
  journal = {NeuroImage},
  year = {2014},
  doi = {10.1016/j.neuroimage.2014.09.010},
  pmid = {25234117},
  url = {https://pubmed.ncbi.nlm.nih.gov/25234117/},
  abstract = {Independent Component Analysis (ICA) is a widely applied data-driven method for parsing brain and non-brain EEG source signals, mixed by volume conduction to the scalp electrodes, into a set of maximally temporally and often functionally independent components (ICs). Many ICs may be identified with a precise physiological or non-physiological origin. However, this process is hindered by partial instability in ICA results that can arise from noise in the data. Here we propose RELICA (RELiable ICA), a novel method to characterize IC reliability within subjects. RELICA first computes IC "dipolarity" a measure of physiological plausibility, plus a measure of IC consistency across multiple decompositions of bootstrap versions of the input data. RELICA then uses these two measures to visualize and cluster the separated ICs, providing a within-subject measure of IC reliability that does not involve checking for its occurrence across subjects. We demonstrate the use of RELICA on EEG data recorded from 14 subjects performing a working memory experiment and show that many brain and ocular artifact ICs are correctly classified as "stable" (highly repeatable across decompositions of bootstrapped versions of the input data). Many stable ICs appear to originate in the brain, while other stable ICs account for identifiable non-brain processes such as line noise. RELICA might be used with any linear blind source separation algorithm to reduce the risk of basing conclusions on unstable or physiologically un-interpretable component processes.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Zao201424917804,
  title = {Pervasive brain monitoring and data sharing based on multi-tier distributed computing and linked data technology.},
  author = {Zao, JK and Gan, TT and You, CK and Chung, CE and Wang, YT and Rodríguez Méndez, SJ and Mullen, T and Yu, C and Kothe, C and Hsiao, CT and Chu, SL and Shieh, CK and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2014},
  doi = {10.3389/fnhum.2014.00370},
  pmid = {24917804},
  url = {https://pubmed.ncbi.nlm.nih.gov/24917804/},
  abstract = {EEG-based Brain-computer interfaces (BCI) are facing basic challenges in real-world applications. The technical difficulties in developing truly wearable BCI systems that are capable of making reliable real-time prediction of users' cognitive states in dynamic real-life situations may seem almost insurmountable at times. Fortunately, recent advances in miniature sensors, wireless communication and distributed computing technologies offered promising ways to bridge these chasms. In this paper, we report an attempt to develop a pervasive on-line EEG-BCI system using state-of-art technologies including multi-tier Fog and Cloud Computing, semantic Linked Data search, and adaptive prediction/classification models. To verify our approach, we implement a pilot system by employing wireless dry-electrode EEG headsets and MEMS motion sensors as the front-end devices, Android mobile phones as the personal user interfaces, compact personal computers as the near-end Fog Servers and the computer clusters hosted by the Taiwan National Center for High-performance Computing (NCHC) as the far-end Cloud Servers. We succeeded in conducting synchronous multi-modal global data streaming in March and then running a multi-player on-line EEG-BCI game in September, 2013. We are currently working with the ARL Translational Neuroscience Branch to use our system in real-life personal stress monitoring and the UCSD Movement Disorder Center to conduct in-home Parkinson's disease patient monitoring experiments. We shall proceed to develop the necessary BCI ontology and introduce automatic semantic annotation and progressive model refinement capability to our system.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Hsu201425570830,
  title = {Online recursive independent component analysis for real-time source separation of high-density EEG.},
  author = {Hsu, SH and Mullen, T and Jung, TP and Cauwenberghs, G},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944462},
  pmid = {25570830},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570830/},
  abstract = {Online Independent Component Analysis (ICA) algorithms have recently seen increasing development and application across a range of fields, including communications, biosignal processing, and brain-computer interfaces. However, prior work in this domain has primarily focused on algorithmic proofs of convergence, with application limited to small `toy' examples or to relatively low channel density EEG datasets. Furthermore, there is limited availability of computationally efficient online ICA implementations, suitable for real-time application. This study describes an optimized online recursive ICA algorithm (ORICA), with online recursive least squares (RLS) whitening, for blind source separation of high-density EEG data. It is implemented as an online-capable plugin within the open-source BCILAB (EEGLAB) framework. We further derive and evaluate a block-update modification to the ORICA learning rule. We demonstrate the algorithm's suitability for accurate and efficient source identification in high density (64-channel) realistically-simulated EEG data, as well as real 61-channel EEG data recorded by a dry and wearable EEG system in a cognitive experiment.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Grandchamp201424575056,
  title = {Oculometric variations during mind wandering.},
  author = {Grandchamp, R and Braboszcz, C and Delorme, A},
  journal = {Frontiers in psychology},
  year = {2014},
  doi = {10.3389/fpsyg.2014.00031},
  pmid = {24575056},
  url = {https://pubmed.ncbi.nlm.nih.gov/24575056/},
  abstract = {A significant body of literature supports the contention that pupil size varies depending on cognitive load, affective state, and level of drowsiness. Here we assessed whether oculometric measures such as gaze position, blink frequency and pupil size were correlated with the occurrence and time course of self-reported mind-wandering episodes. We recorded the pupil size of two subjects engaged in a monotonous breath counting task while keeping their eyes on a fixation cross. This task is conducive to producing mind-wandering episodes. Each subject performed ten 20-min sessions, for total duration of about 4 h. Subjects were instructed to report spontaneous mind-wandering episodes by pressing a button when they lost count of their breath. After each button press, subjects filled in a short questionnaire describing the characteristics of their mind-wandering episode. We observed larger pupil size during the breath-focusing period compared to the mind-wandering period (p < 0.01 for both subjects). Our findings contradict previous research showing a higher baseline pupil size during mind wandering episodes in visual tasks. We discuss possible explanations for this discrepancy. We also analyzed nine other oculometric measures including blink rate, blink duration and gaze position. We built a support vector machine (SVM) classifier and showed that mean pupil size was the most reliable predictor of mind wandering in both subjects. The classification accuracy of mind wandering data segments vs. breath-focusing data segments was 81% for the first subject and 77% for the second subject. Additionally, we analyzed oculometric measures in light of the phenomenological data collected in the questionnaires. We showed that how well subjects remembered their thoughts while mind wandering was positively correlated with pupil size (subject 1, p < 0.001; subject 2, p < 0.05). Feelings of well being were also positively correlated with pupil size (subject 1, p < 0.001; subject 2, p < 0.001). Our results suggest that oculometric data could be used as a neurocognitive marker of mind-wandering episodes.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Durantin201425570400,
  title = {Moving Average Convergence Divergence filter preprocessing for real-time event-related peak activity onset detection : application to fNIRS signals.},
  author = {Durantin, G and Scannella, S and Gateau, T and Delorme, A and Dehais, F},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944032},
  pmid = {25570400},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570400/},
  abstract = {Real-time solutions for noise reduction and signal processing represent a central challenge for the development of Brain Computer Interfaces (BCI). In this paper, we introduce the Moving Average Convergence Divergence (MACD) filter, a tunable digital passband filter for online noise reduction and onset detection without preliminary learning phase, used in economic markets analysis. MACD performance was tested and benchmarked with other filters using data collected with functional Near Infrared Spectoscopy (fNIRS) during a digit sequence memorization task. This filter has a good performance on filtering and real-time peak activity onset detection, compared to other techniques. Therefore, MACD could be implemented for efficient BCI design using fNIRS.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Ojeda201424634649,
  title = {MoBILAB: an open source toolbox for analysis and visualization of mobile brain/body imaging data.},
  author = {Ojeda, A and Bigdely-Shamlo, N and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2014},
  doi = {10.3389/fnhum.2014.00121},
  pmid = {24634649},
  url = {https://pubmed.ncbi.nlm.nih.gov/24634649/},
  abstract = {A new paradigm for human brain imaging, mobile brain/body imaging (MoBI), involves synchronous collection of human brain activity (via electroencephalography, EEG) and behavior (via body motion capture, eye tracking, etc.), plus environmental events (scene and event recording) to study joint brain/body dynamics supporting natural human cognition supporting performance of naturally motivated human actions and interactions in 3-D environments (Makeig et al., 2009). Processing complex, concurrent, multi-modal, multi-rate data streams requires a signal-processing environment quite different from one designed to process single-modality time series data. Here we describe MoBILAB (more details available at sccn.ucsd.edu/wiki/MoBILAB), an open source, cross platform toolbox running on MATLAB (The Mathworks, Inc.) that supports analysis and visualization of any mixture of synchronously recorded brain, behavioral, and environmental time series plus time-marked event stream data. MoBILAB can serve as a pre-processing environment for adding behavioral and other event markers to EEG data for further processing, and/or as a development platform for expanded analysis of simultaneously recorded data streams.},
  note = {PubMed query source: Scott Makeig}
}

@article{Chuang201424444995,
  title = {Kinesthesia in a sustained-attention driving task.},
  author = {Chuang, CH and Ko, LW and Jung, TP and Lin, CT},
  journal = {NeuroImage},
  year = {2014},
  doi = {10.1016/j.neuroimage.2014.01.015},
  pmid = {24444995},
  url = {https://pubmed.ncbi.nlm.nih.gov/24444995/},
  abstract = {This study investigated the effects of kinesthetic stimuli on brain activities during a sustained-attention task in an immersive driving simulator. Tonic and phasic brain responses on multiple timescales were analyzed using time-frequency analysis of electroencephalographic (EEG) sources identified by independent component analysis (ICA). Sorting EEG spectra with respect to reaction times (RT) to randomly introduced lane-departure events revealed distinct effects of kinesthetic stimuli on the brain under different performance levels. Experimental results indicated that EEG spectral dynamics highly correlated with performance lapses when driving involved kinesthetic feedback. Furthermore, in the realistic environment involving both visual and kinesthetic feedback, a transitive relationship of power spectra between optimal-, suboptimal-, and poor-performance groups was found predominately across most of the independent components. In contrast to the static environment with visual input only, kinesthetic feedback reduced theta-power augmentation in the central and frontal components when preparing for action and error monitoring, while strengthening alpha suppression in the central component while steering the wheel. In terms of behavior, subjects tended to have a short response time to process unexpected events with the assistance of kinesthesia, yet only when their performance was optimal. Decrease in attentional demand, facilitated by kinesthetic feedback, eventually significantly increased the reaction time in the suboptimal-performance state. Neurophysiological evidence of mutual relationships between behavioral performance and neurocognition in complex task paradigms and experimental environments, presented in this study, might elucidate our understanding of distributed brain dynamics, supporting natural human cognition and complex coordinated, multi-joint naturalistic behavior, and lead to improved understanding of brain-behavior relations in operating environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Huang201424613718,
  title = {Intrinsic mode functions locate implicit turbulent attractors in time in frontal lobe MEG recordings.},
  author = {Huang, X and Huang, L and Jung, TP and Cheng, CK and Mandell, AJ},
  journal = {Neuroscience},
  year = {2014},
  doi = {10.1016/j.neuroscience.2014.02.038},
  pmid = {24613718},
  url = {https://pubmed.ncbi.nlm.nih.gov/24613718/},
  abstract = {In seeking evidence for the presence and characteristic range of coupled time scale(s) of putative implicit turbulent attractors of dorsal frontal lobe magnetic fields, the recorded nonstationary, nonlinear MEG signals were non-orthogonally decomposed using Huang's Empirical Mode Decomposition, EMD, (Huang and Attoh-Okine, 2005) into 16 Intrinsic Mode Functions, EMD→IMFi, i=1…16. Measures known to be invariant in non-uniformly hyperbolic (turbulent) dynamical systems, topological entropy, hT, metric entropy, hM, non-uniform entropy, hU and power spectral scaling exponent, α, were imposed on each of the IMFi which evidenced most clearly an invariant temporal scale zone of IMFi, i=6…11, for hT, which we have found to be the most robust of invariant measures of MEG's magnetic field turbulent attractors (Mandell et al., 2011a,b; Mandell, 2013). The ergodic theory of dynamical systems (Walters, 1982; Pollicott and Yuri, 1998) allows the inference that an implicit attractor with consistently hT>0 will also evidence at least one positive Lyapounov exponent indicating the presence of a turbulent attractor with exponential separation of nearby initial conditions, exponential convergence of distant points and disordering, mixing, of orbital sequences. It appears that this approach permits the inference of the presence of chaotic, turbulent attractor and its characteristic time scales without the invocation of arbitrary n-dimensional embedding, phase space reconstructions or (inappropriate) orthogonal decompositions.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chuang201424608683,
  title = {Independent component ensemble of EEG for brain-computer interface.},
  author = {Chuang, CH and Ko, LW and Lin, YP and Jung, TP and Lin, CT},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2014},
  doi = {10.1109/TNSRE.2013.2293139},
  pmid = {24608683},
  url = {https://pubmed.ncbi.nlm.nih.gov/24608683/},
  abstract = {Recently, successful applications of independent component analysis (ICA) to electroencephalographic (EEG) signals have yielded tremendous insights into brain processes that underlie human cognition. Many studies have further established the feasibility of using independent processes to elucidate human cognitive states. However, various technical problems arise in the building of an online brain-computer interface (BCI). These include the lack of an automatic procedure for selecting independent components of interest (ICi) and the potential risk of not obtaining a desired ICi. Therefore, this study proposes an ICi-ensemble method that uses multiple classifiers with ICA processing to improve upon existing algorithms. The mechanisms that are used in this ensemble system include: 1) automatic ICi selection; 2) extraction of features of the resultant ICi; 3) the construction of parallel pipelines for effectively training multiple classifiers; and a 4) simple process that combines the multiple decisions. The proposed ICi-ensemble is demonstrated in a typical BCI application, which is the monitoring of participants' cognitive states in a realistic sustained-attention driving task. The results reveal that the proposed ICi-ensemble outperformed the previous method using a single ICi with  ∼ 7% (91.6% versus 84.3%) in the cognitive state classification. Additionally, the proposed ICi-ensemble method that characterizes the EEG dynamics of multiple brain areas favors the application of BCI in natural environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{McLoughlin201424273134,
  title = {In search of biomarkers in psychiatry: EEG-based measures of brain function.},
  author = {McLoughlin, G and Makeig, S and Tsuang, MT},
  journal = {American journal of medical genetics. Part B, Neuropsychiatric genetics : the official publication of the International Society of Psychiatric Genetics},
  year = {2014},
  doi = {10.1002/ajmg.b.32208},
  pmid = {24273134},
  url = {https://pubmed.ncbi.nlm.nih.gov/24273134/},
  abstract = {Current clinical parameters used for diagnosis and phenotypic definitions of psychopathology are both highly variable and subjective. Intensive research efforts for specific and sensitive biological markers, or biomarkers, for psychopathology as objective alternatives to the current paradigm are ongoing. While biomarker research in psychiatry has focused largely on functional neuroimaging methods for identifying the neural functions that associate with psychopathology, scalp electroencephalography (EEG) has been viewed, historically, as offering little specific brain source information, as scalp appearance is only loosely correlated to its brain source dynamics. However, ongoing advances in signal processing of EEG data can now deliver functional EEG brain-imaging with distinctly improved spatial, as well as fine temporal, resolution. One computational approach proving particularly useful for EEG cortical brain imaging is independent component analysis (ICA). ICA decomposition can be used to identify distinct cortical source activities that are sensitive and specific to the pathophysiology of psychiatric disorders. Given its practical research advantages, relatively low cost, and ease of use, EEG-imaging is now both feasible and attractive, in particular for studies involving the large samples required by genetically informative designs to characterize causal pathways to psychopathology. The completely non-invasive nature of EEG data acquisition, coupled with ongoing advances in dry, wireless, and wearable EEG technology, makes EEG-imaging increasingly attractive and appropriate for psychiatric research, including the study of developmentally young samples. Applied to large genetically and developmentally informative samples, EEG imaging can advance the search for robust diagnostic biomarkers and phenotypes in psychiatry.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gramann201424076470,
  title = {Imaging natural cognition in action.},
  author = {Gramann, K and Ferris, DP and Gwin, J and Makeig, S},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2014},
  doi = {10.1016/j.ijpsycho.2013.09.003},
  pmid = {24076470},
  url = {https://pubmed.ncbi.nlm.nih.gov/24076470/},
  abstract = {The primary function of the human brain is arguably to optimize the results of our motor actions in an ever-changing environment. Our cognitive processes and supporting brain dynamics are inherently coupled both to our environment and to our physical structure and actions. To investigate human cognition in its most natural forms demands imaging of brain activity while participants perform naturally motivated actions and interactions within a full three-dimensional environment. Transient, distributed brain activity patterns supporting spontaneous motor actions, performed in pursuit of naturally motivated goals, may involve any or all parts of cortex and must be precisely timed at a speed faster than the speed of thought and action. Hemodynamic imaging methods give information about brain dynamics on a much slower scale, and established techniques for imaging brain dynamics in all modalities forbid participants from making natural extensive movements so as to avoid intractable movement-related artifacts. To overcome these limitations, we are developing mobile brain/body imaging (MoBI) approaches to study natural human cognition. By synchronizing lightweight, high-density electroencephalographic (EEG) recording with recordings of participant sensory experience, body and eye movements, and other physiological measures, we can apply advanced data analysis techniques to the recorded signal ensemble. This MoBI approach enables the study of human brain dynamics accompanying active human cognition in its most natural forms. Results from our studies have provided new insights into the brain dynamics supporting natural cognition and can extend theories of human cognition and its evolutionary function - to optimize the results of our behavior to meet ever-changing goals, challenges, and opportunities.},
  note = {PubMed query source: Scott Makeig}
}

@article{Chen201425570867,
  title = {Hybrid frequency and phase coding for a high-speed SSVEP-based BCI speller.},
  author = {Chen, X and Wang, Y and Nakanishi, M and Jung, TP and Gao, X},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944499},
  pmid = {25570867},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570867/},
  abstract = {Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize high-speed communication between the human brain and the external environment. Recently, multiple access (MA) methods in telecommunications have been introduced into the system design of BCIs and showed their potential in improving BCI performance. This study investigated the feasibility of hybrid frequency and phase coding methods in multi-target SSVEP-based BCIs. Specifically, this study compared two hybrid target-coding strategies: (1) mixed frequency and phase coding, and (2) joint frequency and phase coding. In a simulated online BCI experiment using a 40-target BCI speller, BCI performance for both coding approaches were tested with a group of six subjects. At a spelling speed of 40 characters per minute (1.5 seconds per character), both approaches obtained high information transfer rates (ITR) (mixed coding: 172.37±28.67 bits/min, joint coding: 170.94±28.32 bits/min) across subjects. There was no statistically significant difference between the two approaches (p>0.05). These results suggest that the hybrid frequency and phase coding methods are highly efficient for multi-target coding in SSVEP BCIs with a large number of classes, providing a practical solution to implement a high-speed BCI speller.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{McLoughlin201424001472,
  title = {Genetic overlap between evoked frontocentral theta-band phase variability, reaction time variability, and attention-deficit/hyperactivity disorder symptoms in a twin study.},
  author = {McLoughlin, G and Palmer, JA and Rijsdijk, F and Makeig, S},
  journal = {Biological psychiatry},
  year = {2014},
  doi = {10.1016/j.biopsych.2013.07.020},
  pmid = {24001472},
  url = {https://pubmed.ncbi.nlm.nih.gov/24001472/},
  abstract = {Electrophysiological and hemodynamic activity is altered in attention-deficit/hyperactivity disorder (ADHD) during tasks requiring cognitive control. Frontal midline theta oscillations are a cortical correlate of cognitive control influencing behavioral outcomes including reaction times. Reaction time variability (RTV) is consistently increased in ADHD and is known to share genetic effects with the disorder. The etiological relationship between the cognitive control system, RTV, and ADHD is unknown. In a sample of twins selected for ADHD and matched control subjects, we aimed to quantify the strength of the phenotypic, genetic, and environmental relationships between event-related midline theta oscillations, RTV, and ADHD. Our sample included 134 participants aged 12 to 15 years: 67 twin pairs (34 monozygotic; 33 dizygotic) with concordance or discordance for ADHD symptomatology assessed at 8, 10, and 12 years of age. Our main outcome measures were frontal midline theta activity, derived from both channel and source decomposed electroencephalographic data, and behavioral performance on a response-choice arrow flanker task known to elicit theta activity. Variability in stimulus event-related theta phase from frontal midline cortex is strongly related to both RTV and ADHD, both phenotypically and genetically. This is the first finding to confirm the genetic link between the frontal midline cognitive control system and ADHD and the first to identify a genetically related neurophysiological marker of RTV in ADHD. Variability in the timing of the theta signal in ADHD may be part of a dysfunctional brain network that impairs regulation of task-relevant responses in the disorder.},
  note = {PubMed query source: Scott Makeig}
}

@article{Nakanishi201424918435,
  title = {Generating visual flickers for eliciting robust steady-state visual evoked potentials at flexible frequencies using monitor refresh rate.},
  author = {Nakanishi, M and Wang, Y and Wang, YT and Mitsukura, Y and Jung, TP},
  journal = {PloS one},
  year = {2014},
  doi = {10.1371/journal.pone.0099235},
  pmid = {24918435},
  url = {https://pubmed.ncbi.nlm.nih.gov/24918435/},
  abstract = {In the study of steady-state visual evoked potentials (SSVEPs), it remains a challenge to present visual flickers at flexible frequencies using monitor refresh rate. For example, in an SSVEP-based brain-computer interface (BCI), it is difficult to present a large number of visual flickers simultaneously on a monitor. This study aims to explore whether or how a newly proposed frequency approximation approach changes signal characteristics of SSVEPs. At 10 Hz and 12 Hz, the SSVEPs elicited using two refresh rates (75 Hz and 120 Hz) were measured separately to represent the approximation and constant-period approaches. This study compared amplitude, signal-to-noise ratio (SNR), phase, latency, scalp distribution, and frequency detection accuracy of SSVEPs elicited using the two approaches. To further prove the efficacy of the approximation approach, this study implemented an eight-target BCI using frequencies from 8-15 Hz. The SSVEPs elicited by the two approaches were found comparable with regard to all parameters except amplitude and SNR of SSVEPs at 12 Hz. The BCI obtained an averaged information transfer rate (ITR) of 95.0 bits/min across 10 subjects with a maximum ITR of 120 bits/min on two subjects, the highest ITR reported in the SSVEP-based BCIs. This study clearly showed that the frequency approximation approach can elicit robust SSVEPs at flexible frequencies using monitor refresh rate and thereby can largely facilitate various SSVEP-related studies in neural engineering and visual neuroscience.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lin201424822035,
  title = {Fusion of electroencephalographic dynamics and musical contents for estimating emotional responses in music listening.},
  author = {Lin, YP and Yang, YH and Jung, TP},
  journal = {Frontiers in neuroscience},
  year = {2014},
  doi = {10.3389/fnins.2014.00094},
  pmid = {24822035},
  url = {https://pubmed.ncbi.nlm.nih.gov/24822035/},
  abstract = {Electroencephalography (EEG)-based emotion classification during music listening has gained increasing attention nowadays due to its promise of potential applications such as musical affective brain-computer interface (ABCI), neuromarketing, music therapy, and implicit multimedia tagging and triggering. However, music is an ecologically valid and complex stimulus that conveys certain emotions to listeners through compositions of musical elements. Using solely EEG signals to distinguish emotions remained challenging. This study aimed to assess the applicability of a multimodal approach by leveraging the EEG dynamics and acoustic characteristics of musical contents for the classification of emotional valence and arousal. To this end, this study adopted machine-learning methods to systematically elucidate the roles of the EEG and music modalities in the emotion modeling. The empirical results suggested that when whole-head EEG signals were available, the inclusion of musical contents did not improve the classification performance. The obtained performance of 74~76% using solely EEG modality was statistically comparable to that using the multimodality approach. However, if EEG dynamics were only available from a small set of electrodes (likely the case in real-life applications), the music modality would play a complementary role and augment the EEG results from around 61-67% in valence classification and from around 58-67% in arousal classification. The musical timber appeared to replace less-discriminative EEG features and led to improvements in both valence and arousal classification, whereas musical loudness was contributed specifically to the arousal classification. The present study not only provided principles for constructing an EEG-based multimodal approach, but also revealed the fundamental insights into the interplay of the brain activity and musical contents in emotion modeling.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Nakanishi201425570635,
  title = {Enhancing unsupervised canonical correlation analysis-based frequency detection of SSVEPs by incorporating background EEG.},
  author = {Nakanishi, M and Wang, Y and Wang, YT and Mitsukura, Y and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944267},
  pmid = {25570635},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570635/},
  abstract = {Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to provide a fast communication channel between human brain and external devices. In SSVEP-based BCIs, Canonical Correlation Analysis (CCA) has been widely used to detect frequency-coded SSVEPs due to its high efficiency and robustness. However, the detectability of SSVEPs differs among frequencies due to a power-law distribution of the power spectra of spontaneous electroencephalogram (EEG) signals. This study proposed a new method based on the fact that changes of canonical correlation coefficients for SSVEPs and background EEG signals follow the same trend along frequency. The proposed method defined a normalized canonical correlation coefficient, the ratio of the canonical correlation coefficient for SSVEPs to the mean of the canonical correlation coefficients for background EEG signals, to enhance the frequency detection of SSVEPs. An SSVEP dataset from 13 subjects was used for comparing classification performance between the proposed method and the standard CCA method. Classification accuracy and simulated information transfer rates (ITR) suggest that, in an unsupervised way, the proposed method could considerably improve the frequency detection accuracy of SSVEPs with little computational effort.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wang201425570631,
  title = {Enhancing detection of steady-state visual evoked potentials using individual training data.},
  author = {Wang, Y and Nakanishi, M and Wang, YT and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944263},
  pmid = {25570631},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570631/},
  abstract = {Although the performance of steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) has improved gradually in the past decades, it still does not meet the requirement of a high communication speed in many applications. A major challenge is the interference of spontaneous background EEG activities in discriminating SSVEPs. An SSVEP BCI using frequency coding typically does not have a calibration procedure since the frequency of SSVEPs can be recognized by power spectrum density analysis (PSDA). However, the detection rate can be deteriorated by the spontaneous EEG activities within the same frequency range because phase information of SSVEPs is ignored in frequency detection. To address this problem, this study proposed to incorporate individual SSVEP training data into canonical correlation analysis (CCA) to improve the frequency detection of SSVEPs. An eight-class SSVEP dataset recorded from 10 subjects in a simulated online BCI experiment was used for performance evaluation. Compared to the standard CCA method, the proposed method obtained significantly improved detection accuracy (95.2% vs. 88.4%, p<0.05) and information transfer rates (ITR) (104.6 bits/min vs. 89.1 bits/min, p<0.05). The results suggest that the employment of individual SSVEP training data can significantly improve the detection rate and thereby facilitate the implementation of a high-speed BCI.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lenartowicz201424453310,
  title = {Electroencephalography correlates of spatial working memory deficits in attention-deficit/hyperactivity disorder: vigilance, encoding, and maintenance.},
  author = {Lenartowicz, A and Delorme, A and Walshaw, PD and Cho, AL and Bilder, RM and McGough, JJ and McCracken, JT and Makeig, S and Loo, SK},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2014},
  doi = {10.1523/JNEUROSCI.1765-13.2014},
  pmid = {24453310},
  url = {https://pubmed.ncbi.nlm.nih.gov/24453310/},
  abstract = {In the current study we sought to dissociate the component processes of working memory (WM) (vigilance, encoding and maintenance) that may be differentially impaired in attention-deficit/ hyperactivity disorder (ADHD). We collected electroencephalographic (EEG) data from 52 children with ADHD and 47 typically developing (TD) children, ages 7-14 years, while they performed a spatial Sternberg working memory task. We used independent component analysis and time-frequency analysis to identify midoccipital alpha (8-12 Hz) to evaluate encoding processes and frontal midline theta (4-7 Hz) to evaluate maintenance processes. We tested for effects of task difficulty and cue processing to evaluate vigilance. Children with ADHD showed attenuated alpha band event-related desynchronization (ERD) during encoding. This effect was more pronounced when task difficulty was low (consistent with impaired vigilance) and was predictive of memory task performance and symptom severity. Correlated with alpha ERD during encoding were alpha power increases during the maintenance period (relative to baseline), suggesting a compensatory effort. Consistent with this interpretation, midfrontal theta power increases during maintenance were stronger in ADHD and in high-load memory conditions. Furthermore, children with ADHD exhibited a maturational lag in development of posterior alpha power whereas age-related changes in frontal theta power deviated from the TD pattern. Last, subjects with ADHD showed age-independent attenuation of evoked responses to warning cues, suggesting low vigilance. Combined, these three EEG measures predicted diagnosis with 70% accuracy. We conclude that the interplay of impaired vigilance and encoding in ADHD may compromise maintenance and lead to impaired WM performance in this group.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wang201425352773,
  title = {Developing an EEG-based on-line closed-loop lapse detection and mitigation system.},
  author = {Wang, YT and Huang, KC and Wei, CS and Huang, TY and Ko, LW and Lin, CT and Cheng, CK and Jung, TP},
  journal = {Frontiers in neuroscience},
  year = {2014},
  doi = {10.3389/fnins.2014.00321},
  pmid = {25352773},
  url = {https://pubmed.ncbi.nlm.nih.gov/25352773/},
  abstract = {In America, 60% of adults reported that they have driven a motor vehicle while feeling drowsy, and at least 15-20% of fatal car accidents are fatigue-related. This study translates previous laboratory-oriented neurophysiological research to design, develop, and test an On-line Closed-loop Lapse Detection and Mitigation (OCLDM) System featuring a mobile wireless dry-sensor EEG headgear and a cell-phone based real-time EEG processing platform. Eleven subjects participated in an event-related lane-keeping task, in which they were instructed to manipulate a randomly deviated, fixed-speed cruising car on a 4-lane highway. This was simulated in a 1st person view with an 8-screen and 8-projector immersive virtual-reality environment. When the subjects experienced lapses or failed to respond to events during the experiment, auditory warning was delivered to rectify the performance decrements. However, the arousing auditory signals were not always effective. The EEG spectra exhibited statistically significant differences between effective and ineffective arousing signals, suggesting that EEG spectra could be used as a countermeasure of the efficacy of arousing signals. In this on-line pilot study, the proposed OCLDM System was able to continuously detect EEG signatures of fatigue, deliver arousing warning to subjects suffering momentary cognitive lapses, and assess the efficacy of the warning in near real-time to rectify cognitive lapses. The on-line testing results of the OCLDM System validated the efficacy of the arousing signals in improving subjects' response times to the subsequent lane-departure events. This study may lead to a practical on-line lapse detection and mitigation system in real-world environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu201429978858,
  title = {Design of Interactive Cancer Education Technology for Latina Farmworkers.},
  author = {Wu, Y and Samant, D and Squibbs, K and Chaet, A and Morshedi, B and Barnes, LE},
  journal = {Proceedings of the ... IEEE Systems and Information Engineering Design Symposium. IEEE Systems and Information Engineering Design Symposium},
  year = {2014},
  doi = {10.1109/SIEDS.2014.6829908},
  pmid = {29978858},
  url = {https://pubmed.ncbi.nlm.nih.gov/29978858/},
  abstract = {Latinas in the United States experience higher levels of cervical cancer (CC) incidence and mortality rates than the general population, and many lack access to healthcare or face communication, literacy, and knowledge barriers preventing proper CC screening. Interactive technological interventions, like embodied conversational agents (ECA)/virtual agents, are currently used in other populations, settings, and for other health topics, however, no known initiative has used culturally- and literacy-appropriate technological interventions to deliver Spanish-language CC education. This study aims to create a culturally tailored Spanish-language Virtual Patient Educator (VPE) application to augment a patient navigator (PN) intervention for increasing CC screening rates among Hispanic women in a rural agricultural community. The VPE is a computer character that can simulate face-to-face conversation with an actual person and will embody the characteristics of a PN. Through iterative interviews with the target population, key cultural design factors were identified to inform the design and implementation of a prototype VPE. This paper discusses design and usability issues associated with development of the VPE for low-literacy users in addition to a framework methodology for development of similar tools and a cultural matrix of design factors. A VPE might help close the knowledge gap between Hispanic women and the general population regarding cervical cancer screening. Incorporation of culturally tailored features in technology aids in increasing overall understanding and trust of health information presented. An iterative approach that engages the patient population in design of technology is important to identify population-specific patient preferences.},
  note = {PubMed query source: Ying Wu}
}

@article{Tsai201424113626,
  title = {Cortical surface alignment in multi-subject spatiotemporal independent EEG source imaging.},
  author = {Tsai, AC and Jung, TP and Chien, VS and Savostyanov, AN and Makeig, S},
  journal = {NeuroImage},
  year = {2014},
  doi = {10.1016/j.neuroimage.2013.09.045},
  pmid = {24113626},
  url = {https://pubmed.ncbi.nlm.nih.gov/24113626/},
  abstract = {Brain responses to stimulus presentations may vary widely across subjects in both time course and spatial origins. Multi-subject EEG source imaging studies that apply Independent Component Analysis (ICA) to data concatenated across subjects have overlooked the fact that projections to the scalp sensors from functionally equivalent cortical sources vary from subject to subject. This study demonstrates an approach to spatiotemporal independent component decomposition and alignment that spatially co-registers the MR-derived cortical topographies of individual subjects to a well-defined, shared spherical topology (Fischl et al., 1999). Its efficacy for identifying functionally equivalent EEG sources in multi-subject analysis is demonstrated by analyzing EEG and behavioral data from a stop-signal paradigm using two source-imaging approaches, both based on individual subject independent source decompositions. The first, two-stage approach uses temporal infomax ICA to separate each subject's data into temporally independent components (ICs), then estimates the source density distribution of each IC process from its scalp map and clusters similar sources across subjects (Makeig et al., 2002). The second approach, Electromagnetic Spatiotemporal Independent Component Analysis (EMSICA), combines ICA decomposition and source current density estimation of the artifact-rejected data into a single spatiotemporal ICA decomposition for each subject (Tsai et al., 2006), concurrently identifying both the spatial source distribution of each cortical source and its event-related dynamics. Applied to the stop-signal task data, both approaches gave IC clusters that separately accounted for EEG processes expected in stop-signal tasks, including pre/postcentral mu rhythms, anterior-cingulate theta rhythm, and right-inferior frontal responses, the EMSICA clusters exhibiting more tightly correlated source areas and time-frequency features.},
  note = {PubMed query source: Scott Makeig}
}

@article{Rissling201425379456,
  title = {Cortical substrates and functional correlates of auditory deviance processing deficits in schizophrenia.},
  author = {Rissling, AJ and Miyakoshi, M and Sugar, CA and Braff, DL and Makeig, S and Light, GA},
  journal = {NeuroImage. Clinical},
  year = {2014},
  doi = {10.1016/j.nicl.2014.09.006},
  pmid = {25379456},
  url = {https://pubmed.ncbi.nlm.nih.gov/25379456/},
  abstract = {Although sensory processing abnormalities contribute to widespread cognitive and psychosocial impairments in schizophrenia (SZ) patients, scalp-channel measures of averaged event-related potentials (ERPs) mix contributions from distinct cortical source-area generators, diluting the functional relevance of channel-based ERP measures. SZ patients (n = 42) and non-psychiatric comparison subjects (n = 47) participated in a passive auditory duration oddball paradigm, eliciting a triphasic (Deviant-Standard) tone ERP difference complex, here termed the auditory deviance response (ADR), comprised of a mid-frontal mismatch negativity (MMN), P3a positivity, and re-orienting negativity (RON) peak sequence. To identify its cortical sources and to assess possible relationships between their response contributions and clinical SZ measures, we applied independent component analysis to the continuous 68-channel EEG data and clustered the resulting independent components (ICs) across subjects on spectral, ERP, and topographic similarities. Six IC clusters centered in right superior temporal, right inferior frontal, ventral mid-cingulate, anterior cingulate, medial orbitofrontal, and dorsal mid-cingulate cortex each made triphasic response contributions. Although correlations between measures of SZ clinical, cognitive, and psychosocial functioning and standard (Fz) scalp-channel ADR peak measures were weak or absent, for at least four IC clusters one or more significant correlations emerged. In particular, differences in MMN peak amplitude in the right superior temporal IC cluster accounted for 48% of the variance in SZ-subject performance on tasks necessary for real-world functioning and medial orbitofrontal cluster P3a amplitude accounted for 40%/54% of SZ-subject variance in positive/negative symptoms. Thus, source-resolved auditory deviance response measures including MMN may be highly sensitive to SZ clinical, cognitive, and functional characteristics.},
  note = {PubMed query source: Scott Makeig}
}

@article{Shu201425150386,
  title = {Combat veterans with comorbid PTSD and mild TBI exhibit a greater inhibitory processing ERP from the dorsal anterior cingulate cortex.},
  author = {Shu, IW and Onton, JA and O'Connell, RM and Simmons, AN and Matthews, SC},
  journal = {Psychiatry research},
  year = {2014},
  doi = {10.1016/j.pscychresns.2014.07.010},
  pmid = {25150386},
  url = {https://pubmed.ncbi.nlm.nih.gov/25150386/},
  abstract = {Posttraumatic stress disorder (PTSD) is common among combat personnel with mild traumatic brain injury (mTBI). While patients with either PTSD or mTBI share abnormal activation of multiple frontal brain areas, anterior cingulate cortex (ACC) activity during inhibitory processing may be particularly affected by PTSD. To further test this hypothesis, we recorded electroencephalography from 32 combat veterans with mTBI-17 of whom were also comorbid for PTSD (mTBI+PTSD) and 15 without PTSD (mTBI-only). Subjects performed the Stop Task, a validated inhibitory control task requiring inhibition of initiated motor responses. We observed a larger inhibitory processing eventrelated potential (ERP) in veterans with mTBI+PTSD, including greater N200 negativity. Furthermore, greater N200 negativity correlated with greater PTSD severity. This correlation was most dependent on contributions from the dorsal ACC. Support vector machine analysis demonstrated that N200 and P300 amplitudes objectively classified veterans into mTBI-only or mTBI+PTSD groups with 79.4% accuracy. Our results support a model where, in combat veterans with mTBI, larger ERPs from cingulate areas are associated with greater PTSD severity and likely related to difficulty controlling ongoing brain processes, including trauma-related thoughts and feelings.},
  note = {PubMed query source: Julie Onton}
}

@article{Shu201424342149,
  title = {Combat veterans with PTSD after mild TBI exhibit greater ERPs from posterior-medial cortical areas while appraising facial features.},
  author = {Shu, IW and Onton, JA and Prabhakar, N and O'Connell, RM and Simmons, AN and Matthews, SC},
  journal = {Journal of affective disorders},
  year = {2014},
  doi = {10.1016/j.jad.2013.06.057},
  pmid = {24342149},
  url = {https://pubmed.ncbi.nlm.nih.gov/24342149/},
  abstract = {Posttraumatic stress disorder (PTSD) worsens prognosis following mild traumatic brain injury (mTBI). Combat personnel with histories of mTBI exhibit abnormal activation of distributed brain networks-including emotion processing and default mode networks. How developing PTSD further affects these abnormalities has not been directly examined. We recorded electroencephalography in combat veterans with histories of mTBI, but without active PTSD (mTBI only, n=16) and combat veterans who developed PTSD after mTBI (mTBI+PTSD, n=16)-during the Reading the Mind in the Eyes Test (RMET), a validated test of empathy requiring emotional appraisal of facial features. Task-related event related potentials (ERPs) were identified, decomposed using independent component analysis (ICA) and localized anatomically using dipole modeling. We observed larger emotional face processing ERPs in veterans with mTBI+PTSD, including greater N300 negativity. Furthermore, greater N300 negativity correlated with greater PTSD severity, especially avoidance/numbing and hyperarousal symptom clusters. This correlation was dependent on contributions from the precuneus and posterior cingulate cortex (PCC). Our results support a model where, in combat veterans with histories of mTBI, larger ERPs from over-active posterior-medial cortical areas may be specific to PTSD, and is likely related to negative self-referential activity.},
  note = {PubMed query source: Julie Onton}
}

@article{Wu201425282199,
  title = {Co-speech iconic gestures and visuo-spatial working memory.},
  author = {Wu, YC and Coulson, S},
  journal = {Acta psychologica},
  year = {2014},
  doi = {10.1016/j.actpsy.2014.09.002},
  pmid = {25282199},
  url = {https://pubmed.ncbi.nlm.nih.gov/25282199/},
  abstract = {Three experiments tested the role of verbal versus visuo-spatial working memory in the comprehension of co-speech iconic gestures. In Experiment 1, participants viewed congruent discourse primes in which the speaker's gestures matched the information conveyed by his speech, and incongruent ones in which the semantic content of the speaker's gestures diverged from that in his speech. Discourse primes were followed by picture probes that participants judged as being either related or unrelated to the preceding clip. Performance on this picture probe classification task was faster and more accurate after congruent than incongruent discourse primes. The effect of discourse congruency on response times was linearly related to measures of visuo-spatial, but not verbal, working memory capacity, as participants with greater visuo-spatial WM capacity benefited more from congruent gestures. In Experiments 2 and 3, participants performed the same picture probe classification task under conditions of high and low loads on concurrent visuo-spatial (Experiment 2) and verbal (Experiment 3) memory tasks. Effects of discourse congruency and verbal WM load were additive, while effects of discourse congruency and visuo-spatial WM load were interactive. Results suggest that congruent co-speech gestures facilitate multi-modal language comprehension, and indicate an important role for visuo-spatial WM in these speech-gesture integration processes.},
  note = {PubMed query source: Ying Wu}
}

@article{Broccard201424833254,
  title = {Closed-loop brain-machine-body interfaces for noninvasive rehabilitation of movement disorders.},
  author = {Broccard, FD and Mullen, T and Chi, YM and Peterson, D and Iversen, JR and Arnold, M and Kreutz-Delgado, K and Jung, TP and Makeig, S and Poizner, H and Sejnowski, T and Cauwenberghs, G},
  journal = {Annals of biomedical engineering},
  year = {2014},
  doi = {10.1007/s10439-014-1032-6},
  pmid = {24833254},
  url = {https://pubmed.ncbi.nlm.nih.gov/24833254/},
  abstract = {Traditional approaches for neurological rehabilitation of patients affected with movement disorders, such as Parkinson's disease (PD), dystonia, and essential tremor (ET) consist mainly of oral medication, physical therapy, and botulinum toxin injections. Recently, the more invasive method of deep brain stimulation (DBS) showed significant improvement of the physical symptoms associated with these disorders. In the past several years, the adoption of feedback control theory helped DBS protocols to take into account the progressive and dynamic nature of these neurological movement disorders that had largely been ignored so far. As a result, a more efficient and effective management of PD cardinal symptoms has emerged. In this paper, we review closed-loop systems for rehabilitation of movement disorders, focusing on PD, for which several invasive and noninvasive methods have been developed during the last decade, reducing the complications and side effects associated with traditional rehabilitation approaches and paving the way for tailored individual therapeutics. We then present a novel, transformative, noninvasive closed-loop framework based on force neurofeedback and discuss several future developments of closed-loop systems that might bring us closer to individualized solutions for neurological rehabilitation of movement disorders.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wisniewski201425538550,
  title = {Brain dynamics that correlate with effects of learning on auditory distance perception.},
  author = {Wisniewski, MG and Mercado, E and Church, BA and Gramann, K and Makeig, S},
  journal = {Frontiers in neuroscience},
  year = {2014},
  doi = {10.3389/fnins.2014.00396},
  pmid = {25538550},
  url = {https://pubmed.ncbi.nlm.nih.gov/25538550/},
  abstract = {Accuracy in auditory distance perception can improve with practice and varies for sounds differing in familiarity. Here, listeners were trained to judge the distances of English, Bengali, and backwards speech sources pre-recorded at near (2-m) and far (30-m) distances. Listeners' accuracy was tested before and after training. Improvements from pre-test to post-test were greater for forward speech, demonstrating a learning advantage for forward speech sounds. Independent component (IC) processes identified in electroencephalographic (EEG) data collected during pre- and post-testing revealed three clusters of ICs across subjects with stimulus-locked spectral perturbations related to learning and accuracy. One cluster exhibited a transient stimulus-locked increase in 4-8 Hz power (theta event-related synchronization; ERS) that was smaller after training and largest for backwards speech. For a left temporal cluster, 8-12 Hz decreases in power (alpha event-related desynchronization; ERD) were greatest for English speech and less prominent after training. In contrast, a cluster of IC processes centered at or near anterior portions of the medial frontal cortex showed learning-related enhancement of sustained increases in 10-16 Hz power (upper-alpha/low-beta ERS). The degree of this enhancement was positively correlated with the degree of behavioral improvements. Results suggest that neural dynamics in non-auditory cortical areas support distance judgments. Further, frontal cortical networks associated with attentional and/or working memory processes appear to play a role in perceptual learning for source distance.},
  note = {PubMed query source: Scott Makeig}
}

@article{Balkan201425571518,
  title = {Basis selection for maximally independent EEG sources.},
  author = {Balkan, O and Bigdely-Shamlo, N and Kreutz-Delgado, K and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6945150},
  pmid = {25571518},
  url = {https://pubmed.ncbi.nlm.nih.gov/25571518/},
  abstract = {We suggest a solution to the following problem: "Given multichannel linear source mixture data Y, and an overcomplete dictionary, A, of source projections, ai, how can we construct a complete basis, A0, by selecting columns from A such that the sources X = A0(-1)Y are as statistically independent as possible from each other?". While conventional independent component analysis (ICA) methods learn the mixing matrix A0 from scratch given Y, we restrict ourselves to selecting basis vectors from a known overcomplete dictionary. We develop two methods based on modifications of the maximum likelihood equivalent of the Infomax approach and the reconstruction-ICA (RICA) algorithm. We show that on realistic synthetic electroencephalographic (EEG) data our algorithms can find the true sources in the case of a highly coherent dictionary while requiring relatively fewer data points compared to other algorithms. On real EEG data, our algorithms obtain higher mutual information reduction.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lin201424744718,
  title = {Assessing the quality of steady-state visual-evoked potentials for moving humans using a mobile electroencephalogram headset.},
  author = {Lin, YP and Wang, Y and Wei, CS and Jung, TP},
  journal = {Frontiers in human neuroscience},
  year = {2014},
  doi = {10.3389/fnhum.2014.00182},
  pmid = {24744718},
  url = {https://pubmed.ncbi.nlm.nih.gov/24744718/},
  abstract = {Recent advances in mobile electroencephalogram (EEG) systems, featuring non-prep dry electrodes and wireless telemetry, have enabled and promoted the applications of mobile brain-computer interfaces (BCIs) in our daily life. Since the brain may behave differently while people are actively situated in ecologically-valid environments versus highly-controlled laboratory environments, it remains unclear how well the current laboratory-oriented BCI demonstrations can be translated into operational BCIs for users with naturalistic movements. Understanding inherent links between natural human behaviors and brain activities is the key to ensuring the applicability and stability of mobile BCIs. This study aims to assess the quality of steady-state visual-evoked potentials (SSVEPs), which is one of promising channels for functioning BCI systems, recorded using a mobile EEG system under challenging recording conditions, e.g., walking. To systematically explore the effects of walking locomotion on the SSVEPs, this study instructed subjects to stand or walk on a treadmill running at speeds of 1, 2, and 3 mile (s) per hour (MPH) while concurrently perceiving visual flickers (11 and 12 Hz). Empirical results of this study showed that the SSVEP amplitude tended to deteriorate when subjects switched from standing to walking. Such SSVEP suppression could be attributed to the walking locomotion, leading to distinctly deteriorated SSVEP detectability from standing (84.87 ± 13.55%) to walking (1 MPH: 83.03 ± 13.24%, 2 MPH: 79.47 ± 13.53%, and 3 MPH: 75.26 ± 17.89%). These findings not only demonstrated the applicability and limitations of SSVEPs recorded from freely behaving humans in realistic environments, but also provide useful methods and techniques for boosting the translation of the BCI technology from laboratory demonstrations to practical applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Lin201425108604,
  title = {Assessing the feasibility of online SSVEP decoding in human walking using a consumer EEG headset.},
  author = {Lin, YP and Wang, Y and Jung, TP},
  journal = {Journal of neuroengineering and rehabilitation},
  year = {2014},
  doi = {10.1186/1743-0003-11-119},
  pmid = {25108604},
  url = {https://pubmed.ncbi.nlm.nih.gov/25108604/},
  abstract = {Bridging the gap between laboratory brain-computer interface (BCI) demonstrations and real-life applications has gained increasing attention nowadays in translational neuroscience. An urgent need is to explore the feasibility of using a low-cost, ease-of-use electroencephalogram (EEG) headset for monitoring individuals' EEG signals in their natural head/body positions and movements. This study aimed to assess the feasibility of using a consumer-level EEG headset to realize an online steady-state visual-evoked potential (SSVEP)-based BCI during human walking. This study adopted a 14-channel Emotiv EEG headset to implement a four-target online SSVEP decoding system, and included treadmill walking at the speeds of 0.45, 0.89, and 1.34 meters per second (m/s) to initiate the walking locomotion. Seventeen participants were instructed to perform the online BCI tasks while standing or walking on the treadmill. To maintain a constant viewing distance to the visual targets, participants held the hand-grip of the treadmill during the experiment. Along with online BCI performance, the concurrent SSVEP signals were recorded for offline assessment. Despite walking-related attenuation of SSVEPs, the online BCI obtained an information transfer rate (ITR) over 12 bits/min during slow walking (below 0.89 m/s). SSVEP-based BCI systems are deployable to users in treadmill walking that mimics natural walking rather than in highly-controlled laboratory settings. This study considerably promotes the use of a consumer-level EEG headset towards the real-life BCI applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Fang201425570831,
  title = {An efficient ASIC implementation of 16-channel on-line recursive ICA processor for real-time EEG system.},
  author = {Fang, WC and Huang, KJ and Chou, CC and Chang, JC and Cauwenberghs, G and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2014},
  doi = {10.1109/EMBC.2014.6944463},
  pmid = {25570831},
  url = {https://pubmed.ncbi.nlm.nih.gov/25570831/},
  abstract = {This is a proposal for an efficient very-large-scale integration (VLSI) design, 16-channel on-line recursive independent component analysis (ORICA) processor ASIC for real-time EEG system, implemented with TSMC 40 nm CMOS technology. ORICA is appropriate to be used in real-time EEG system to separate artifacts because of its highly efficient and real-time process features. The proposed ORICA processor is composed of an ORICA processing unit and a singular value decomposition (SVD) processing unit. Compared with previous work [1], this proposed ORICA processor has enhanced effectiveness and reduced hardware complexity by utilizing a deeper pipeline architecture, shared arithmetic processing unit, and shared registers. The 16-channel random signals which contain 8-channel super-Gaussian and 8-channel sub-Gaussian components are used to analyze the dependence of the source components, and the average correlation coefficient is 0.95452 between the original source signals and extracted ORICA signals. Finally, the proposed ORICA processor ASIC is implemented with TSMC 40 nm CMOS technology, and it consumes 15.72 mW at 100 MHz operating frequency.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wu201424465437,
  title = {A psychometric measure of working memory capacity for configured body movement.},
  author = {Wu, YC and Coulson, S},
  journal = {PloS one},
  year = {2014},
  doi = {10.1371/journal.pone.0084834},
  pmid = {24465437},
  url = {https://pubmed.ncbi.nlm.nih.gov/24465437/},
  abstract = {Working memory (WM) models have traditionally assumed at least two domain-specific storage systems for verbal and visuo-spatial information. We review data that suggest the existence of an additional slave system devoted to the temporary storage of body movements, and present a novel instrument for its assessment: the movement span task. The movement span task assesses individuals' ability to remember and reproduce meaningless configurations of the body. During the encoding phase of a trial, participants watch short videos of meaningless movements presented in sets varying in size from one to five items. Immediately after encoding, they are prompted to reenact as many items as possible. The movement span task was administered to 90 participants along with standard tests of verbal WM, visuo-spatial WM, and a gesture classification test in which participants judged whether a speaker's gestures were congruent or incongruent with his accompanying speech. Performance on the gesture classification task was not related to standard measures of verbal or visuo-spatial working memory capacity, but was predicted by scores on the movement span task. Results suggest the movement span task can serve as an assessment of individual differences in WM capacity for body-centric information.},
  note = {PubMed query source: Ying Wu}
}

@article{Nakanishi201425081427,
  title = {A high-speed brain speller using steady-state visual evoked potentials.},
  author = {Nakanishi, M and Wang, Y and Wang, YT and Mitsukura, Y and Jung, TP},
  journal = {International journal of neural systems},
  year = {2014},
  doi = {10.1142/S0129065714500191},
  pmid = {25081427},
  url = {https://pubmed.ncbi.nlm.nih.gov/25081427/},
  abstract = {Implementing a complex spelling program using a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) remains a challenge due to difficulties in stimulus presentation and target identification. This study aims to explore the feasibility of mixed frequency and phase coding in building a high-speed SSVEP speller with a computer monitor. A frequency and phase approximation approach was developed to eliminate the limitation of the number of targets caused by the monitor refresh rate, resulting in a speller comprising 32 flickers specified by eight frequencies (8-15 Hz with a 1 Hz interval) and four phases (0°, 90°, 180°, and 270°). A multi-channel approach incorporating Canonical Correlation Analysis (CCA) and SSVEP training data was proposed for target identification. In a simulated online experiment, at a spelling rate of 40 characters per minute, the system obtained an averaged information transfer rate (ITR) of 166.91 bits/min across 13 subjects with a maximum individual ITR of 192.26 bits/min, the highest ITR ever reported in electroencephalogram (EEG)-based BCIs. The results of this study demonstrate great potential of a high-speed SSVEP-based BCI in real-life applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Fan201322997269,
  title = {What are we tracking: a unified approach of tracking and recognition.},
  author = {Fan, J and Shen, X and Wu, Y},
  journal = {IEEE transactions on image processing : a publication of the IEEE Signal Processing Society},
  year = {2013},
  doi = {10.1109/TIP.2012.2218827},
  pmid = {22997269},
  url = {https://pubmed.ncbi.nlm.nih.gov/22997269/},
  abstract = {Tracking is essentially a matching problem. While traditional tracking methods mostly focus on low-level image correspondences between frames, we argue that high-level semantic correspondences are indispensable to make tracking more reliable. Based on that, a unified approach of low-level object tracking and high-level recognition is proposed for single object tracking, in which the target category is actively recognized during tracking. High-level offline models corresponding to the recognized category are then adaptively selected and combined with low-level online tracking models so as to achieve better tracking performance. Extensive experimental results show that our approach outperforms state-of-the-art online models in many challenging tracking scenarios such as drastic view change, scale change, background clutter, and morphable objects.},
  note = {PubMed query source: Ying Wu}
}

@article{Cologan201323121471,
  title = {Sleep in the unresponsive wakefulness syndrome and minimally conscious state.},
  author = {Cologan, V and Drouot, X and Parapatics, S and Delorme, A and Gruber, G and Moonen, G and Laureys, S},
  journal = {Journal of neurotrauma},
  year = {2013},
  doi = {10.1089/neu.2012.2654},
  pmid = {23121471},
  url = {https://pubmed.ncbi.nlm.nih.gov/23121471/},
  abstract = {The goal of our study was to investigate different aspects of sleep, namely the sleep-wake cycle and sleep stages, in the vegetative state/unresponsive wakefulness syndrome (VS/UWS), and minimally conscious state (MCS). A 24-h polysomnography was performed in 20 patients who were in a UWS (n=10) or in a MCS (n=10) because of brain injury. The data were first tested for the presence of a sleep-wake cycle, and the observed sleep patterns were compared with standard scoring criteria. Sleep spindles, slow wave sleep, and rapid eye movement sleep were quantified and their clinical value was investigated. According to our results, an electrophysiological sleep-wake cycle was identified in five MCS and three VS/UWS patients. Sleep stages did not always match the standard scoring criteria, which therefore needed to be adapted. Sleep spindles were present more in patients who clinically improved within 6 months. Slow wave sleep was present in eight MCS and three VS/UWS patients but never in the ischemic etiology. Rapid eye movement sleep, and therefore dreaming that is a form of consciousness, was present in all MCS and three VS/UWS patients. In conclusion, the presence of alternating periods of eyes-open/eyes-closed cycles does not necessarily imply preserved electrophysiological sleep architecture in the UWS and MCS, contrary to previous definition. The investigation of sleep is a little studied yet simple and informative way to evaluate the integrity of residual brain function in patients with disorders of consciousness with possible clinical diagnostic and prognostic implications.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Mullen201324110155,
  title = {Real-time modeling and 3D visualization of source dynamics and connectivity using wearable EEG.},
  author = {Mullen, T and Kothe, C and Chi, YM and Ojeda, A and Kerth, T and Makeig, S and Cauwenberghs, G and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6609968},
  pmid = {24110155},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110155/},
  abstract = {This report summarizes our recent efforts to deliver real-time data extraction, preprocessing, artifact rejection, source reconstruction, multivariate dynamical system analysis (including spectral Granger causality) and 3D visualization as well as classification within the open-source SIFT and BCILAB toolboxes. We report the application of such a pipeline to simulated data and real EEG data obtained from a novel wearable high-density (64-channel) dry EEG system.},
  note = {PubMed query source: Scott Makeig}
}

@article{Braboszcz201324376429,
  title = {Plasticity of visual attention in Isha yoga meditation practitioners before and after a 3-month retreat.},
  author = {Braboszcz, C and Cahn, BR and Balakrishnan, B and Maturi, RK and Grandchamp, R and Delorme, A},
  journal = {Frontiers in psychology},
  year = {2013},
  doi = {10.3389/fpsyg.2013.00914},
  pmid = {24376429},
  url = {https://pubmed.ncbi.nlm.nih.gov/24376429/},
  abstract = {Meditation has lately received considerable interest from cognitive neuroscience. Studies suggest that daily meditation leads to long lasting attentional and neuronal plasticity. We present changes related to the attentional systems before and after a 3 month intensive meditation retreat. We used three behavioral psychophysical tests - a Stroop task, an attentional blink task, and a global-local letter task-to assess the effect of Isha yoga meditation on attentional resource allocation. 82 Isha yoga practitioners were tested at the beginning and at the end of the retreat. Our results showed an increase in correct responses specific to incongruent stimuli in the Stroop task. Congruently, a positive correlation between previous meditation experience and accuracy to incongruent Stroop stimuli was also observed at baseline. We also observed a reduction of the attentional blink. Unexpectedly, a negative correlation between previous meditation experience and attentional blink performance at baseline was observed. Regarding spatial attention orientation as assessed using the global-local letter task, participants showed a bias toward local processing. Only slight differences in performance were found pre- vs. post- meditation retreat. Biasing toward the local stimuli in the global-local task and negative correlation of previous meditation experience with attentional blink performance is consistent with Isha practices being focused-attention practices. Given the relatively small effect sizes and the absence of a control group, our results do not allow clear support nor rejection of the hypothesis of meditation-driven neuronal plasticity in the attentional system for Isha yoga practice.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Brandmeyer201324109463,
  title = {Meditation and neurofeedback.},
  author = {Brandmeyer, T and Delorme, A},
  journal = {Frontiers in psychology},
  year = {2013},
  doi = {10.3389/fpsyg.2013.00688},
  pmid = {24109463},
  url = {https://pubmed.ncbi.nlm.nih.gov/24109463/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{BigdelyShamlo201323370059,
  title = {Measure projection analysis: a probabilistic approach to EEG source comparison and multi-subject inference.},
  author = {Bigdely-Shamlo, N and Mullen, T and Kreutz-Delgado, K and Makeig, S},
  journal = {NeuroImage},
  year = {2013},
  doi = {10.1016/j.neuroimage.2013.01.040},
  pmid = {23370059},
  url = {https://pubmed.ncbi.nlm.nih.gov/23370059/},
  abstract = {A crucial question for the analysis of multi-subject and/or multi-session electroencephalographic (EEG) data is how to combine information across multiple recordings from different subjects and/or sessions, each associated with its own set of source processes and scalp projections. Here we introduce a novel statistical method for characterizing the spatial consistency of EEG dynamics across a set of data records. Measure Projection Analysis (MPA) first finds voxels in a common template brain space at which a given dynamic measure is consistent across nearby source locations, then computes local-mean EEG measure values for this voxel subspace using a statistical model of source localization error and between-subject anatomical variation. Finally, clustering the mean measure voxel values in this locally consistent brain subspace finds brain spatial domains exhibiting distinguishable measure features and provides 3-D maps plus statistical significance estimates for each EEG measure of interest. Applied to sufficient high-quality data, the scalp projections of many maximally independent component (IC) processes contributing to recorded high-density EEG data closely match the projection of a single equivalent dipole located in or near brain cortex. We demonstrate the application of MPA to a multi-subject EEG study decomposed using independent component analysis (ICA), compare the results to k-means IC clustering in EEGLAB (sccn.ucsd.edu/eeglab), and use surrogate data to test MPA robustness. A Measure Projection Toolbox (MPT) plug-in for EEGLAB is available for download (sccn.ucsd.edu/wiki/MPT). Together, MPA and ICA allow use of EEG as a 3-D cortical imaging modality with near-cm scale spatial resolution.},
  note = {PubMed query source: Scott Makeig}
}

@article{Sipp201323926037,
  title = {Loss of balance during balance beam walking elicits a multifocal theta band electrocortical response.},
  author = {Sipp, AR and Gwin, JT and Makeig, S and Ferris, DP},
  journal = {Journal of neurophysiology},
  year = {2013},
  doi = {10.1152/jn.00744.2012},
  pmid = {23926037},
  url = {https://pubmed.ncbi.nlm.nih.gov/23926037/},
  abstract = {Determining the neural correlates of loss of balance during walking could lead to improved clinical assessment and treatment for individuals predisposed to falls. We used high-density electroencephalography (EEG) combined with independent component analysis (ICA) to study loss of balance during human walking. We examined 26 healthy young subjects performing heel-to-toe walking on a treadmill-mounted balance beam as well as walking on the treadmill belt (both at 0.22 m/s). ICA identified clusters of electrocortical EEG sources located in or near anterior cingulate, anterior parietal, superior dorsolateral-prefrontal, and medial sensorimotor cortex that exhibited significantly larger mean spectral power in the theta band (4-7 Hz) during walking on the balance beam compared with treadmill walking. Left and right sensorimotor cortex clusters produced significantly less power in the beta band (12-30 Hz) during walking on the balance beam compared with treadmill walking. For each source cluster, we also computed a normalized mean time/frequency spectrogram time locked to the gait cycle during loss of balance (i.e., when subjects stepped off the balance beam). All clusters except the medial sensorimotor cluster exhibited a transient increase in theta band power during loss of balance. Cluster spectrograms demonstrated that the first electrocortical indication of impending loss of balance occurred in the left sensorimotor cortex at the transition from single support to double support prior to stepping off the beam. These findings provide new insight into the neural correlates of walking balance control and could aid future studies on elderly individuals and others with balance impairments.},
  note = {PubMed query source: Scott Makeig}
}

@article{Magnuski201323628290,
  title = {It's not only in the eyes: nonlinear relationship between face orientation and N170 amplitude irrespective of eye presence.},
  author = {Magnuski, M and Gola, M},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2013},
  doi = {10.1016/j.ijpsycho.2013.04.016},
  pmid = {23628290},
  url = {https://pubmed.ncbi.nlm.nih.gov/23628290/},
  abstract = {We have investigated the interplay between face orientation, eye presence, and N170 amplitude by recording Event Related Potentials. To clarify previous reports of nonlinearity in N170 amplitude changes along rotation angle changes, we adopted Itier et al.'s model (Itier et al., 2007) which links N170 face inversion effects with the presence of eyes. Comparison of N170 amplitude and latency for five stimulus categories (Faces-with-eyes, Faces-without-eyes, Eyes, Cars-with-lights, Cars-without-lights) in five different rotations (0, 45, 90, 135, 180) resulted in mixed conclusions. The main findings of this study are as follows: (1) a strong nonlinear relationship between N170 and angle of rotation that is specific to faces, distinguishing face from car category even when no significant differences were observed between these categories for upright and inverted orientations; and (2) the nonlinear relationship between N170 and angle of rotation does not depend on eye presence. We also propose an alternative model according to which N170 amplitude consists of two related aspects of face processing: (A) incompatibility (relative distance of the stimulus pattern from experience-based hypothetical prototype) and (B) integration (degree to which stimulus is integrated into holistic representation), with the former affecting the latter. Moreover, we suggest two possible neural events underlying these two aspects of face processing: neural population size activated by the stimulus, and synchronization within this population.},
  note = {PubMed query source: Mateusz Gola}
}

@article{He201324108705,
  title = {Grand challenges in mapping the human brain: NSF workshop report.},
  author = {He, B and Coleman, T and Genin, GM and Glover, G and Hu, X and Johnson, N and Liu, T and Makeig, S and Sajda, P and Ye, K},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2013},
  doi = {10.1109/TBME.2013.2283970},
  pmid = {24108705},
  url = {https://pubmed.ncbi.nlm.nih.gov/24108705/},
  abstract = {This report summarizes the outcomes of the NSF Workshop on Mapping and Engineering the Brain, held at Arlington, VA, during August 13-14, 2013. Three grand challenges were identified, including high spatiotemporal resolution neuroimaging, perturbation-based neuroimaging, and neuroimaging in naturalistic environments. It was highlighted that each grand challenge requires groundbreaking discoveries, enabling technologies, appropriate knowledge transfer, and multi- and transdisciplinary education and training for success.},
  note = {PubMed query source: Scott Makeig}
}

@article{BigdelyShamlo201324111068,
  title = {EyeCatch: data-mining over half a million EEG independent components to construct a fully-automated eye-component detector.},
  author = {Bigdely-Shamlo, N and Kreutz-Delgado, K and Kothe, C and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6610881},
  pmid = {24111068},
  url = {https://pubmed.ncbi.nlm.nih.gov/24111068/},
  abstract = {Independent component analysis (ICA) can find distinct sources of electroencephalographic (EEG) activity, both brain-based and artifactual, and has become a common pre-preprocessing step in analysis of EEG data. Distinction between brain and non-brain independent components (ICs) accounting for, e.g., eye or muscle activities is an important step in the analysis. Here we present a fully automated method to identify eye-movement related EEG components by analyzing the spatial distribution of their scalp projections (scalp maps). The EyeCatch method compares each input scalp map to a database of eye-related IC scalp maps obtained by data-mining over half a million IC scalp maps obtained from 80,006 EEG datasets associated with a diverse set of EEG studies and paradigms. To our knowledge this is the largest sample of IC scalp maps that has ever been analyzed. Our result show comparable performance to a previous state-of-art semi-automated method, CORRMAP, while eliminating the need for human intervention.},
  note = {PubMed query source: Scott Makeig}
}

@article{Cahn201322648958,
  title = {Event-related delta, theta, alpha and gamma correlates to auditory oddball processing during Vipassana meditation.},
  author = {Cahn, BR and Delorme, A and Polich, J},
  journal = {Social cognitive and affective neuroscience},
  year = {2013},
  doi = {10.1093/scan/nss060},
  pmid = {22648958},
  url = {https://pubmed.ncbi.nlm.nih.gov/22648958/},
  abstract = {Long-term Vipassana meditators sat in meditation vs. a control (instructed mind wandering) states for 25 min, electroencephalography (EEG) was recorded and condition order counterbalanced. For the last 4 min, a three-stimulus auditory oddball series was presented during both meditation and control periods through headphones and no task imposed. Time-frequency analysis demonstrated that meditation relative to the control condition evinced decreased evoked delta (2-4 Hz) power to distracter stimuli concomitantly with a greater event-related reduction of late (500-900 ms) alpha-1 (8-10 Hz) activity, which indexed altered dynamics of attentional engagement to distracters. Additionally, standard stimuli were associated with increased early event-related alpha phase synchrony (inter-trial coherence) and evoked theta (4-8 Hz) phase synchrony, suggesting enhanced processing of the habituated standard background stimuli. Finally, during meditation, there was a greater differential early-evoked gamma power to the different stimulus classes. Correlation analysis indicated that this effect stemmed from a meditation state-related increase in early distracter-evoked gamma power and phase synchrony specific to longer-term expert practitioners. The findings suggest that Vipassana meditation evokes a brain state of enhanced perceptual clarity and decreased automated reactivity.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Huang201324110584,
  title = {Empirical mode decomposition improves detection of SSVEP.},
  author = {Huang, L and Huang, X and Wang, YT and Wang, Y and Jung, TP and Cheng, CK},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6610397},
  pmid = {24110584},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110584/},
  abstract = {Steady State Visual Evoked Potentials (SSVEPs) have been used to quantify attention-related neural activity to visual targets. This study investigates how empirical mode decomposition (EMD) can improve detection accuracy and rate of SSVEPs. First, the scalp-recorded electroencephalogram (EEG) signals are decomposed into intrinsic mode functions (IMFs) by EMD. Then, IMF components accounting for SSVEPs are selected for target frequency detection. Finally, target frequency is identified by two methods: Gabor transform and Canonical Correlation Analysis (CCA). This study quantitatively explores the impact of EMD on the target frequency detection. Empirical results show that the EMD improves their recognition accuracy when Gabor transform is used, even in a shorter Gaussian window, but has little effects on the performance of the CCA. Further, this study finds that harmonic responses of the target frequency can be used to enhance the SSVEP detection both for the Gabor transform and CCA.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Delorme201324312063,
  title = {Electrocortical activity associated with subjective communication with the deceased.},
  author = {Delorme, A and Beischel, J and Michel, L and Boccuzzi, M and Radin, D and Mills, PJ},
  journal = {Frontiers in psychology},
  year = {2013},
  doi = {10.3389/fpsyg.2013.00834},
  pmid = {24312063},
  url = {https://pubmed.ncbi.nlm.nih.gov/24312063/},
  abstract = {During advanced meditative practices, unusual perceptions can arise including the sense of receiving information about unknown people who are deceased. As with meditation, this mental state of communication with the deceased involves calming mental chatter and becoming receptive to subtle feelings and sensations. Psychometric and brain electrophysiology data were collected from six individuals who had previously reported accurate information about deceased individuals under double-blind conditions. Each experimental participant performed two tasks with eyes closed. In the first task, the participant was given only the first name of a deceased person and asked 25 questions. After each question, the participant was asked to silently perceive information relevant to the question for 20 s and then respond verbally. Responses were transcribed and then scored for accuracy by individuals who knew the deceased persons. Of the four mediums whose accuracy could be evaluated, three scored significantly above chance (p < 0.03). The correlation between accuracy and brain activity during the 20 s of silent mediumship communication was significant in frontal theta for one participant (p < 0.01). In the second task, participants were asked to experience four mental states for 1 min each: (1) thinking about a known living person, (2) listening to a biography, (3) thinking about an imaginary person, and (4) interacting mentally with a known deceased person. Each mental state was repeated three times. Statistically significant differences at p < 0.01 after correction for multiple comparisons in electrocortical activity among the four conditions were obtained in all six participants, primarily in the gamma band (which might be due to muscular activity). These differences suggest that the impression of communicating with the deceased may be a distinct mental state distinct from ordinary thinking or imagination.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{AkalinAcar201323355112,
  title = {Effects of forward model errors on EEG source localization.},
  author = {Akalin Acar, Z and Makeig, S},
  journal = {Brain topography},
  year = {2013},
  doi = {10.1007/s10548-012-0274-6},
  pmid = {23355112},
  url = {https://pubmed.ncbi.nlm.nih.gov/23355112/},
  abstract = {Subject-specific four-layer boundary element method (BEM) electrical forward head models for four participants, generated from magnetic resonance (MR) head images using NFT ( www.sccn.ucsd.edu/wiki/NFT ), were used to simulate electroencephalographic (EEG) scalp potentials at 256 recorded electrode positions produced by single current dipoles of a 3-D grid in brain space. Locations of these dipoles were then estimated using gradient descent within five template head models fit to the electrode positions. These were: a spherical model, three-layer and four-layer BEM head models based on the Montreal Neurological Institute (MNI) template head image, and these BEM models warped to the recorded electrode positions. Smallest localization errors (4.1-6.2 mm, medians) were obtained using the electrode-position warped four-layer BEM models, with largest localization errors (~20 mm) for most basal brain locations. When we increased the brain-to-skull conductivity ratio assumed in the template model scalp projections from the simulated value (25:1) to a higher value (80:1) used in earlier studies, the estimated dipole locations moved outwards (12.4 mm, median). We also investigated the effects of errors in co-registering the electrode positions, of reducing electrode counts, and of adding a fifth, isotropic white matter layer to one individual head model. Results show that when individual subject MR head images are not available to construct subject-specific head models, accurate EEG source localization should employ a four- or five-layer BEM template head model incorporating an accurate skull conductivity estimate and warped to 64 or more accurately 3-D measured and co-registered electrode positions.},
  note = {PubMed query source: Scott Makeig}
}

@article{Brunner201324042816,
  title = {Eeglab - an Open Source Matlab Toolbox for Electrophysiological Research.},
  author = {Brunner, C and Delorme, A and Makeig, S},
  journal = {Biomedizinische Technik. Biomedical engineering},
  year = {2013},
  doi = {10.1515/bmt-2013-4182},
  pmid = {24042816},
  url = {https://pubmed.ncbi.nlm.nih.gov/24042816/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Gola201323688673,
  title = {EEG beta band activity is related to attention and attentional deficits in the visual performance of elderly subjects.},
  author = {Gola, M and Magnuski, M and Szumska, I and Wróbel, A},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2013},
  doi = {10.1016/j.ijpsycho.2013.05.007},
  pmid = {23688673},
  url = {https://pubmed.ncbi.nlm.nih.gov/23688673/},
  abstract = {We have previously shown that beta-band EEG activity is related to attentional modulation in the visual system of cats and humans. In a separate experiment we also observed that some elderly subjects expressed beta-band power decreases during a simple visual attention task, an effect which was accompanied by low behavioral accuracy in this subgroup. Here, we conducted a detailed examination of beta power deficits in elderly subjects in comparison to young controls. In order to do so, we equalized the subjective level of task difficulty by adjusting visual stimuli presentation duration in such a way that elderly and young subjects achieved similar behavioral results. We found that: (1) beta-band power of EEG signals recorded over occipital regions in elderly and young groups is related to visual attention, as judged from increases in beta power preceding correct responses and lack of beta activity change before erroneous responses; (2) despite forming a homogeneous group when screened for dementia (MMSE), age, education level, visual correction, and speed-accuracy trade-off strategy, elderly subjects could be assigned into one of the two subgroups: high performers, who did not differ from young performers in terms of beta-band power increases, and low performers, whose beta power decreased during the most difficult attentional conditions (shortest - 3s and longest - 11s cue-target delays). These findings posit that the beta-band activity decrease recorded in low performing elderly subjects reflects difficulty in activation and deficits in sustaining attentional processes.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Wang201324110925,
  title = {Developing stimulus presentation on mobile devices for a truly portable SSVEP-based BCI.},
  author = {Wang, YT and Wang, Y and Cheng, CK and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6610738},
  pmid = {24110925},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110925/},
  abstract = {This study integrates visual stimulus presentation and near real-time data processing on a mobile device (e.g. a Tablet or a cell-phone) to implement a steady-state visual evoked potentials (SSVEP)-based brain-computer interface (BCI). The goal of this study is to increase the practicability, portability and ubiquity of an SSVEP-based BCI for daily use. The accuracy of flickering frequencies on the mobile SSVEP BCI system was tested against that on a laptop/desktop used in our previous studies. This study then analyzed the power spectrum density of the electroencephalogram signals elicited by the visual stimuli rendered on the mobile BCIs. Finally, this study performed an online test with the Tablet-based BCI system and obtained an averaged information transfer rate of 33.87 bits/min in three subjects. The current integration leads to a truly practical and ubiquitous SSVEP BCI on mobile devices for real-life applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Wang201323159138,
  title = {Delirium assessment using Confusion Assessment Method for the Intensive Care Unit in Chinese critically ill patients.},
  author = {Wang, C and Wu, Y and Yue, P and Ely, EW and Huang, J and Yang, X and Liu, Y},
  journal = {Journal of critical care},
  year = {2013},
  doi = {10.1016/j.jcrc.2012.10.004},
  pmid = {23159138},
  url = {https://pubmed.ncbi.nlm.nih.gov/23159138/},
  abstract = {The aim of this study was to provide a method for delirium evaluation in simplified Chinese for patients speaking this language via validation of a translation of the Confusion Assessment Method for the Intensive Care Unit (CAM-ICU). Two phases were conducted including initial reliability testing (phase I) of the Attention Screening Exam (ASE) followed by reliability and validity testing of the CAM-ICU (phase II). To analyze the reliability of the ASE, each patient was assessed sequentially by ASE Visual and ASE Auditory. The patients were assessed by 2 nurse investigators using CAM-ICU and 1 neurologist using Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition separately within 2 hours in the second phase. We found that the agreement between ASE Visual and ASE Auditory was high (κ = 0.83, P < .01, respectively). The educational level of the patients influenced the results of the inattention assessment, with the lower educational level of the patient yielding lower agreement on ASE. Even still, the κ consistencies were all above 0.61. The sensitivities of CAM-ICU were 91.8% and 93.4%, and the specificities were 90.8%and 87.7%, respectively. The interrater reliability of 2 nurse investigators was very high, with κ coefficient of 0.92 (P < .001). This study affirmed the validity and reliability against reference raters using the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition of a brief nursing-conducted method of diagnosing delirium in ICU patients who speak simplified Chinese using the CAM-ICU.},
  note = {PubMed query source: Ying Wu}
}

@article{Zhang201322968206,
  title = {Compressed sensing of EEG for wireless telemonitoring with low energy consumption and inexpensive hardware.},
  author = {Zhang, Z and Jung, TP and Makeig, S and Rao, BD},
  journal = {IEEE transactions on bio-medical engineering},
  year = {2013},
  doi = {10.1109/TBME.2012.2217959},
  pmid = {22968206},
  url = {https://pubmed.ncbi.nlm.nih.gov/22968206/},
  abstract = {Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compression methodologies, although effective in data compression, consumes significant energy and cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints. However, EEG is nonsparse in the time domain and also nonsparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis and engineering applications. Recently, block sparse Bayesian learning (BSBL) was proposed as a new method to the CS problem. This study introduces the technique to the telemonitoring of EEG. Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG and other nonsparse physiological signals.},
  note = {PubMed query source: Scott Makeig}
}

@article{Burns201324110028,
  title = {Comparison of averaging and regression techniques for estimating Event Related Potentials.},
  author = {Burns, MD and Bigdely-Shamlo, N and Smith, NJ and Kreutz-Delgado, K and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6609841},
  pmid = {24110028},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110028/},
  abstract = {The traditional method of estimating an Event Related Potential (ERP) is to take the average of signal epochs time locked to a set of similar experimental events. This averaging method is useful as long as the experimental procedure can sufficiently isolate the brain or non-brain process of interest. However, if responses from multiple cognitive processes, time locked to multiple classes of closely spaced events, overlap in time with varying inter-event intervals, averaging will most likely fail to identify the individual response time courses. For this situation, we study estimation of responses to all recorded events in an experiment by a single model using standard linear regression (the rERP technique). Applied to data collected during a Rapid Serial Visual Presentation (RSVP) task, our analysis shows: (1) The rERP technique accounts for more variance in the data than averaging when individual event responses are highly overlapping; (2) the variance accounted for by the estimates is concentrated into a fewer ICA components than raw EEG channel signals.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lin201324060726,
  title = {Can arousing feedback rectify lapses in driving? Prediction from EEG power spectra.},
  author = {Lin, CT and Huang, KC and Chuang, CH and Ko, LW and Jung, TP},
  journal = {Journal of neural engineering},
  year = {2013},
  doi = {10.1088/1741-2560/10/5/056024},
  pmid = {24060726},
  url = {https://pubmed.ncbi.nlm.nih.gov/24060726/},
  abstract = {This study explores the neurophysiological changes, measured using an electroencephalogram (EEG), in response to an arousing warning signal delivered to drowsy drivers, and predicts the efficacy of the feedback based on changes in the EEG. Eleven healthy subjects participated in sustained-attention driving experiments. The driving task required participants to maintain their cruising position and compensate for randomly induced lane deviations using the steering wheel, while their EEG and driving performance were continuously monitored. The arousing warning signal was delivered to participants who experienced momentary behavioral lapses, failing to respond rapidly to lane-departure events (specifically the reaction time exceeded three times the alert reaction time). The results of our previous studies revealed that arousing feedback immediately reversed deteriorating driving performance, which was accompanied by concurrent EEG theta- and alpha-power suppression in the bilateral occipital areas. This study further proposes a feedback efficacy assessment system to accurately estimate the efficacy of arousing warning signals delivered to drowsy participants by monitoring the changes in their EEG power spectra immediately thereafter. The classification accuracy was up 77.8% for determining the need for triggering additional warning signals. The findings of this study, in conjunction with previous studies on EEG correlates of behavioral lapses, might lead to a practical closed-loop system to predict, monitor and rectify behavioral lapses of human operators in attention-critical settings.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Huang201323850831,
  title = {Brain oscillation and connectivity during a chemistry visual working memory task.},
  author = {Huang, LY and She, HC and Chou, WC and Chuang, MH and Duann, JR and Jung, TP},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2013},
  doi = {10.1016/j.ijpsycho.2013.07.001},
  pmid = {23850831},
  url = {https://pubmed.ncbi.nlm.nih.gov/23850831/},
  abstract = {Many studies have reported that frontal theta and posterior alpha activities are associated with working memory tasks. However, fewer studies have focused on examining whether or not the frontal alpha or posterior theta can play a role in the working memory task. This study investigates electroencephalography (EEG) dynamics and connectivity among different brain regions' theta and alpha oscillations. The EEG was collected from undergraduate students (n = 64) while they were performing a Sternberg-like working memory task involving chemistry concepts. The results showed that the frontal midline cluster exhibited sustained theta augmentation across the periods of stimulus presentations, maintenance, and probe presentation, suggesting that the frontal midline theta might associate with facilitating the central execute function to maintain information in the working memory. Study of the central parietal and the occipital clusters revealed a sequence of theta augmentation followed by alpha suppression at constant intervals after the onset of stimulus and probe presentations, suggesting that the posterior theta might be associated with sensory processing, theta gating, or stimulus selection. It further suggests that the posterior alpha event-related de-synchronization (ERD) might be linked to direct information flow into and out of the long-term memory (LTM) and precede stimulus recognition. An alternating phasic alpha event-related synchronization (ERS) and ERD following the 1st stimulus and probe presentations were observed at the occipital cluster, in which alpha ERS might be linked to the inhibition of irrelevant information.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Kothe201323985960,
  title = {BCILAB: a platform for brain-computer interface development.},
  author = {Kothe, CA and Makeig, S},
  journal = {Journal of neural engineering},
  year = {2013},
  doi = {10.1088/1741-2560/10/5/056014},
  pmid = {23985960},
  url = {https://pubmed.ncbi.nlm.nih.gov/23985960/},
  abstract = {The past two decades have seen dramatic progress in our ability to model brain signals recorded by electroencephalography, functional near-infrared spectroscopy, etc., and to derive real-time estimates of user cognitive state, response, or intent for a variety of purposes: to restore communication by the severely disabled, to effect brain-actuated control and, more recently, to augment human-computer interaction. Continuing these advances, largely achieved through increases in computational power and methods, requires software tools to streamline the creation, testing, evaluation and deployment of new data analysis methods. Here we present BCILAB, an open-source MATLAB-based toolbox built to address the need for the development and testing of brain-computer interface (BCI) methods by providing an organized collection of over 100 pre-implemented methods and method variants, an easily extensible framework for the rapid prototyping of new methods, and a highly automated framework for systematic testing and evaluation of new implementations. To validate and illustrate the use of the framework, we present two sample analyses of publicly available data sets from recent BCI competitions and from a rapid serial visual presentation task. We demonstrate the straightforward use of BCILAB to obtain results compatible with the current BCI literature. The aim of the BCILAB toolbox is to provide the BCI community a powerful toolkit for methods research and evaluation, thereby helping to accelerate the pace of innovation in the field, while complementing the existing spectrum of tools for real-time BCI experimentation, deployment and use.},
  note = {PubMed query source: Scott Makeig}
}

@article{Chuang201324110154,
  title = {Automatic design for independent component analysis based brain-computer interfacing.},
  author = {Chuang, CH and Lin, YP and Ko, LW and Jung, TP and Lin, CT},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6609967},
  pmid = {24110154},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110154/},
  abstract = {This study proposes a new framework, independent component ensemble, to leverage the acquired knowledge into a truly automatic and on-line EEG-based brain-computer interfacing (BCI). The envisioned design includes: (1) independent source recover using independent component analysis (ICA) (2) automatic selection of the independent components of interest (ICi) associated with human behaviors; (3) multiple classifiers with a parallel constructing and processing structure; and (4) a simple fusion scheme to combine the decisions from multiple classifiers. Its implications in BCI are demonstrated through a sample application: cognitive-state monitoring of participants performing a realistic sustained-attention driving task. Empirical results showed the proposed ensemble design could provide an improvement of 7% ~ 15% in overall accuracy for the classification of the arousal state and the driving performance. In summary, constructing ICi-ensemble classifiers and combining their outputs demonstrates a practical option for ICA-based BCIs to reduce the risk of not obtaining any desired independent source or selecting an inadequate component. Most importantly, the ensemble design for integrating information across multiple brain areas creates potentials for developing more complicated BCIs for real world applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Miyakoshi201324110429,
  title = {Automated detection of cross-frequency coupling in the electrocorticogram for clinical inspection.},
  author = {Miyakoshi, M and Delorme, A and Mullen, T and Kojima, K and Makeig, S and Asano, E},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6610242},
  pmid = {24110429},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110429/},
  abstract = {We developed a toolbox for detecting high-frequency oscillations and evaluating cross-frequency phase-amplitude coupling in electrocorticographic (ECoG) data with optimal parameters. Here we demonstrate use of the toolbox using simulated and realistic ECoG data. The results confirmed its potential usefulness for clinical research or practice. The tools have been released as a Phase-Amplitude Coupling Toolbox (PACT) plug-in for EEGLAB, an open software environment for electrophysiological data analysis (sccn.ucsd.edu/eeglab).},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Kunert201323487290,
  title = {Assessment of long-term results of intracranial aneurysm clipping by means of computed tomography angiography.},
  author = {Kunert, P and Prokopienko, M and Gola, M and Dziedzic, T and Jaworski, M and Marchel, A},
  journal = {Neurologia i neurochirurgia polska},
  year = {2013},
  doi = {10.5114/ninp.2012.31549},
  pmid = {23487290},
  url = {https://pubmed.ncbi.nlm.nih.gov/23487290/},
  abstract = {The aim of this retrospective study was to assess the effectiveness of aneurysm clipping by computed tomography angiography (CTA) in a long-term follow-up. The CTA examination was performed in 119 patients who had 143 aneurysms clipped. The examinations were performed 3 to 11 years (mean 6 years) after clipping using a GE Lightspeed PRO16 scanner. In all cases but one, good quality CTA images, suitable for evaluation of the arteries around the clip site, were obtained. Complete aneurysm closure without neck remnant or regrowth was confirmed in 137 (96%) aneurysms. In 4 (3%) cases, neck remnants were detected (2 on the anterior communicating artery [AComA] and 2 on the middle cerebral artery [MCA]). A total clip slippage from the aneurysm dome was revealed in 1 case. One case of aneurysm re-rupture was noted, 11 years after clipping. The rebleeding was caused by AComA aneurysm regrowth. Among these 6 patients with unsatisfactory clipping, 2 required further treatment and 4 remain under observation. Nineteen 'de novo' aneurysms in other locations were found in 14 (12%) patients. Summing up all of the pathological findings in the study group, there were 18 (15%) patients who needed further management including close surveillance or re-treatment. Computed tomography angiography is a simple and reliable method of aneurysm clipping evaluation. The long- term follow-up CTA confirmed the permanent and complete obliteration of 96% of the aneurysms. The rate of unsatisfactory aneurysm closure was 4%, but only 1.4% needed re-treatment during a mean follow-up of 6 years. The annual risk of aneurysm re-rupture was 0.1%.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Shih201324111307,
  title = {An efficient VLSI implementation of on-line recursive ICA processor for real-time multi-channel EEG signal separation.},
  author = {Shih, WY and Liao, JC and Huang, KJ and Fang, WC and Cauwenberghs, G and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6611120},
  pmid = {24111307},
  url = {https://pubmed.ncbi.nlm.nih.gov/24111307/},
  abstract = {This paper presents an efficient VLSI implementation of on-line recursive ICA (ORICA) processor for real-time multi-channel EEG signal separation. The proposed design contains a system control unit, a whitening unit, a singular value decomposition unit, a floating matrix multiply unit and, and an ORICA weight training unit. Because the input sample rate of the ORICA processor is 128 Hz, the ORICA processor should produce independent components before the next sample is input in 1/128 s. Under the timing constraints of commutating multi-channel ORICA in real time, the design of the ORICA processor is a mixed architecture, which is designed as different hardware parallelism according to the complexity of processing units. The shared arithmetic processing unit and shared register can reduce hardware complexity and power consumption. The proposed design is implemented used TSMC 90 nm CMOS technology with 8-channel EEG processing in 128 Hz sample rate of raw data and consumes 2.827 mW at 50 MHz clock rate. The performance of the proposed design is also shown to reach 0.0078125 s latency after each EEG sample time, and the average correlation coefficient between the original source signals and extracted ORICA signals for each 1 s frame is 0.9763.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Nakanishi201324110153,
  title = {An approximation approach for rendering visual flickers in SSVEP-based BCI using monitor refresh rate.},
  author = {Nakanishi, M and Wang, Y and Wang, YT and Mitsukura, Y and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6609966},
  pmid = {24110153},
  url = {https://pubmed.ncbi.nlm.nih.gov/24110153/},
  abstract = {Steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) have potential to realize a direct communication between the human brain and the external environment in practical situations. In the conventional stimulus presentation approach, which requires a constant period of stimulation, the number of frequencies that can be presented on a computer monitor is always limited by the refresh rate of a monitor. Although an alternative approach that uses a variable on/off frame number to approximate a target flickering stimulus has been proposed in our recent study, a direct comparison between SSVEPs elicited by the conventional constant period approach and the approximation approach is still missing. This study aims to compare the amplitude, signal-to-noise ratio (SNR) and target identification accuracy of SSVEPs elicited using these two approaches with a monitor at two refresh rates (75Hz and 120Hz). Results of this study suggest that the SSVEPs elicited by the approximation approach are mostly comparable with those elicited by the constant period approach.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{He201324368763,
  title = {Abstracts of Presentations at the International Conference on Basic and Clinical Multimodal Imaging (BaCI), a Joint Conference of the International Society for Neuroimaging in Psychiatry (ISNIP), the International Society for Functional Source Imaging (ISFSI), the International Society for Bioelectromagnetism (ISBEM), the International Society for Brain Electromagnetic Topography (ISBET), and the EEG and Clinical Neuroscience Society (ECNS), in Geneva, Switzerland, September 5-8, 2013.},
  author = {He, BJ and Nolte, G and Nagata, K and Takano, D and Yamazaki, T and Fujimaki, Y and Maeda, T and Satoh, Y and Heckers, S and George, MS and Lopes da Silva, F and de Munck, JC and Van Houdt, PJ and Verdaasdonk, RM and Ossenblok, P and Mullinger, K and Bowtell, R and Bagshaw, AP and Keeser, D and Karch, S and Segmiller, F and Hantschk, I and Berman, A and Padberg, F and Pogarell, O and Scharnowski, F and Karch, S and Hümmer, S and Keeser, D and Paolini, M and Kirsch, V and Koller, G and Rauchmann, B and Kupka, M and Blautzik, J and Pogarell, O and Razavi, N and Jann, K and Koenig, T and Kottlow, M and Hauf, M and Strik, W and Dierks, T and Gotman, J and Vulliemoz, S and Lu, Y and Zhang, H and Yang, L and Worrell, G and He, B and Gruber, O and Piguet, C and Hubl, D and Homan, P and Kindler, J and Dierks, T and Kim, K and Steinhoff, U and Wakai, R and Koenig, T and Kottlow, M and Melie-García, L and Mucci, A and Volpe, U and Prinster, A and Salvatore, M and Galderisi, S and Linden, DE and Brandeis, D and Schroeder, CE and Kayser, C and Panzeri, S and Kleinschmidt, A and Ritter, P and Walther, S and Haueisen, J and Lau, S and Flemming, L and Sonntag, H and Maess, B and Knösche, TR and Lanfer, B and Dannhauer, M and Wolters, CH and Stenroos, M and Haueisen, J and Wolters, C and Aydin, U and Lanfer, B and Lew, S and Lucka, F and Ruthotto, L and Vorwerk, J and Wagner, S and Ramon, C and Guan, C and Ang, KK and Chua, SG and Kuah, WK and Phua, KS and Chew, E and Zhou, H and Chuang, KH and Ang, BT and Wang, C and Zhang, H and Yang, H and Chin, ZY and Yu, H and Pan, Y and Collins, L and Mainsah, B and Colwell, K and Morton, K and Ryan, D and Sellers, E and Caves, K and Throckmorton, S and Kübler, A and Holz, EM and Zickler, C and Sellers, E and Ryan, D and Brown, K and Colwell, K and Mainsah, B and Caves, K and Throckmorton, S and Collins, L and Wennberg, R and Ahlfors, SP and Grova, C and Chowdhury, R and Hedrich, T and Heers, M and Zelmann, R and Hall, JA and Lina, JM and Kobayashi, E and Oostendorp, T and van Dam, P and Oosterhof, P and Linnenbank, A and Coronel, R and van Dessel, P and de Bakker, J and Rossion, B and Jacques, C and Witthoft, N and Weiner, KS and Foster, BL and Miller, KJ and Hermes, D and Parvizi, J and Grill-Spector, K and Recanzone, GH and Murray, MM and Haynes, JD and Richiardi, J and Greicius, M and De Lucia, M and Müller, KR and Formisano, E and Smieskova, R and Schmidt, A and Bendfeldt, K and Walter, A and Riecher-Rössler, A and Borgwardt, S and Fusar-Poli, P and Eliez, S and Schmidt, A and Sekihara, K and Nagarajan, SS and Schoffelen, JM and Guggisberg, AG and Nolte, G and Balazs, S and Kermanshahi, K and Kiesenhofer, W and Binder, H and Rattay, F and Antal, A and Chaieb, L and Paulus, W and Bodis-Wollner, I and Maurer, K and Fein, G and Camchong, J and Johnstone, J and Cardenas-Nicolson, V and Fiederer, LD and Lucka, F and Yang, S and Vorwerk, J and Dümpelmann, M and Cosandier-Rimélé, D and Schulze-Bonhage, A and Aertsen, A and Speck, O and Wolters, CH and Ball, T and Fuchs, M and Wagner, M and Kastner, J and Tech, R and Dinh, C and Haueisen, J and Baumgarten, D and Hämäläinen, MS and Lau, S and Vogrin, SJ and D'Souza, W and Haueisen, J and Cook, MJ and Custo, A and Van De Ville, D and Vulliemoz, S and Grouiller, F and Michel, CM and Malmivuo, J and Aydin, U and Vorwerk, J and Küpper, P and Heers, M and Kugel, H and Wellmer, J and Kellinghaus, C and Scherg, M and Rampp, S and Wolters, C and Storti, SF and Boscolo Galazzo, I and Del Felice, A and Pizzini, FB and Arcaro, C and Formaggio, E and Mai, R and Manganotti, P and Koessler, L and Vignal, J and Cecchin, T and Colnat-Coulbois, S and Vespignani, H and Ramantani, G and Maillard, L and Rektor, I and Kuba, R and Brázdil, M and Chrastina, J and Rektorova, I and van Mierlo, P and Carrette, E and Strobbe, G and Montes-Restrepo, V and Vonck, K and Vandenberghe, S and Ahmed, B and Brodely, C and Carlson, C and Kuzniecky, R and Devinsky, O and French, J and Thesen, T and Bénis, D and David, O and Lachaux, JP and Seigneuret, E and Krack, P and Fraix, V and Chabardès, S and Bastin, J and Jann, K and Gee, D and Kilroy, E and Cannon, T and Wang, DJ and Hale, JR and Mayhew, SD and Przezdzik, I and Arvanitis, TN and Bagshaw, AP and Plomp, G and Quairiaux, C and Astolfi, L and Michel, CM and Mayhew, SD and Mullinger, KJ and Bagshaw, AP and Bowtell, R and Francis, ST and Schouten, AC and Campfens, SF and van der Kooij, H and Koles, Z and Lind, J and Flor-Henry, P and Wirth, M and Haase, CM and Villeneuve, S and Vogel, J and Jagust, WJ and Kambeitz-Ilankovic, L and Simon-Vermot, L and Gesierich, B and Duering, M and Ewers, M and the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and Rektorova, I and Krajcovicova, L and Marecek, R and Mikl, M and Bracht, T and Horn, H and Strik, W and Federspiel, A and Schnell, S and Höfle, O and Stegmayer, K and Wiest, R and Dierks, T and Müller, TJ and Walther, S and Surmeli, T and Ertem, A and Eralp, E and Kos, IH and Skrandies, W and Flüggen, S and Klein, A and Britz, J and Díaz Hernàndez, L and Ro, T and Michel, CM and Lenartowicz, A and Lau, E and Rodriguez, C and Cohen, MS and Loo, SK and Di Lorenzo, G and Pagani, M and Monaco, L and Daverio, A and Giannoudas, I and La Porta, P and Verardo, AR and Niolu, C and Fernandez, I and Siracusano, A and Flor-Henry, P and Lind, J and Koles, Z and Bollmann, S and Ghisleni, C and O'Gorman, R and Poil, SS and Klaver, P and Michels, L and Martin, E and Ball, J and Eich-Höchli, D and Brandeis, D and Salisbury, DF and Murphy, TK and Butera, CD and Mathalon, DH and Fryer, SL and Kiehl, KA and Calhoun, VC and Pearlson, GD and Roach, BJ and Ford, JM and McGlashan, TH and Woods, SW and Volpe, U and Merlotti, E and Vignapiano, A and Montefusco, V and Plescia, GM and Gallo, O and Romano, P and Mucci, A and Galderisi, S and Mingoia, G and Langbein, K and Dietzek, M and Wagner, G and Smesny and Scherpiet, S and Maitra, R and Gaser, C and Sauer, H and Nenadic, I and Gonzalez Andino, S and Grave de Peralta Menendez, R and Grave de Peralta Menendez, R and Sanchez Vives, M and Rebollo, B and Gonzalez Andino, S and Frølich, L and Andersen, TS and Mørup, M and Belfiore, P and Gargiulo, P and Ramon, C and Vanhatalo, S and Cho, JH and Vorwerk, J and Wolters, CH and Knösche, TR and Watanabe, T and Kawabata, Y and Ukegawa, D and Kawabata, S and Adachi, Y and Sekihara, K and Sekihara, K and Nagarajan, SS and Wagner, S and Aydin, U and Vorwerk, J and Herrmann, C and Burger, M and Wolters, C and Lucka, F and Aydin, U and Vorwerk, J and Burger, M and Wolters, C and Bauer, M and Trahms, L and Sander, T and Faber, PL and Lehmann, D and Gianotti, LR and Pascual-Marqui, RD and Milz, P and Kochi, K and Kaneko, S and Yamashita, S and Yana, K and Kalogianni, K and Vardy, AN and Schouten, AC and van der Helm, FC and Sorrentino, A and Luria, G and Aramini, R and Hunold, A and Funke, M and Eichardt, R and Haueisen, J and Gómez-Aguilar, F and Vázquez-Olvera, S and Cordova-Fraga, T and Castro-López, J and Hernández-Gonzalez, MA and Solorio-Meza, S and Sosa-Aquino, M and Bernal-Alvarado, JJ and Vargas-Luna, M and Vorwerk, J and Magyari, L and Ludewig, J and Oostenveld, R and Wolters, CH and Vorwerk, J and Engwer, C and Ludewig, J and Wolters, C and Sato, K and Nishibe, T and Furuya, M and Yamashiro, K and Yana, K and Ono, T and Puthanmadam Subramaniyam, N and Hyttinen, J and Lau, S and Güllmar, D and Flemming, L and Haueisen, J and Sonntag, H and Vorwerk, J and Wolters, CH and Grasedyck, L and Haueisen, J and Maeß, B and Freitag, S and Graichen, U and Fiedler, P and Strohmeier, D and Haueisen, J and Stenroos, M and Hauk, O and Grigutsch, M and Felber, M and Maess, B and Herrmann, B and Strobbe, G and van Mierlo, P and Vandenberghe, S and Strobbe, G and Cárdenas-Peña, D and Montes-Restrepo, V and van Mierlo, P and Castellanos-Dominguez, G and Vandenberghe, S and Lanfer, B and Paul-Jordanov, I and Scherg, M and Wolters, CH and Ito, Y and Sato, D and Kamada, K and Kobayashi, T and Dalal, SS and Rampp, S and Willomitzer, F and Arold, O and Fouladi-Movahed, S and Häusler, G and Stefan, H and Ettl, S and Zhang, S and Zhang, Y and Li, H and Kong, X and Montes-Restrepo, V and Strobbe, G and van Mierlo, P and Vandenberghe, S and Wong, DD and Bidet-Caulet, A and Knight, RT and Crone, NE and Dalal, SS and Birot, G and Spinelli, L and Vulliémoz, S and Seeck, M and Michel, CM and Emory, H and Wells, C and Mizrahi, N and Vogrin, SJ and Lau, S and Cook, MJ and Karahanoglu, FI and Grouiller, F and Caballero-Gaudes, C and Seeck, M and Vulliemoz, S and Van De Ville, D and Spinelli, L and Megevand, P and Genetti, M and Schaller, K and Michel, C and Vulliemoz, S and Seeck, M and Genetti, M and Tyrand, R and Grouiller, F and Vulliemoz, S and Spinelli, L and Seeck, M and Schaller, K and Michel, CM and Grouiller, F and Heinzer, S and Delattre, B and Lazeyras, F and Spinelli, L and Pittau, F and Seeck, M and Ratib, O and Vargas, M and Garibotto, V and Vulliemoz, S and Vogrin, SJ and Bailey, CA and Kean, M and Warren, AE and Davidson, A and Seal, M and Harvey, AS and Archer, JS and Papadopoulou, M and Leite, M and van Mierlo, P and Vonck, K and Boon, P and Friston, K and Marinazzo, D and Ramon, C and Holmes, M and Koessler, L and Rikir, E and Gavaret, M and Bartolomei, F and Vignal, JP and Vespignani, H and Maillard, L and Centeno, M and Perani, S and Pier, K and Lemieux, L and Clayden, J and Clark, C and Pressler, R and Cross, H and Carmichael, DW and Spring, A and Bessemer, R and Pittman, D and Aghakhani, Y and Federico, P and Pittau, F and Grouiller, F and Vulliémoz, S and Gotman, J and Badier, JM and Bénar, CG and Bartolomei, F and Cruto, C and Chauvel, P and Gavaret, M and Brodbeck, V and van Leeuwen, T and Tagliazzuchi, E and Melloni, L and Laufs, H and Griskova-Bulanova, I and Dapsys, K and Klein, C and Hänggi, J and Jäncke, L and Ehinger, BV and Fischer, P and Gert, AL and Kaufhold, L and Weber, F and Marchante Fernandez, M and Pipa, G and König, P and Sekihara, K and Hiyama, E and Koga, R and Iannilli, E and Michel, CM and Bartmuss, AL and Gupta, N and Hummel, T and Boecker, R and Holz, N and Buchmann, AF and Blomeyer, D and Plichta, MM and Wolf, I and Baumeister, S and Meyer-Lindenberg, A and Banaschewski, T and Brandeis, D and Laucht, M and Natahara, S and Ueno, M and Kobayashi, T and Kottlow, M and Bänninger, A and Koenig, T and Schwab, S and Koenig, T and Federspiel, A and Dierks, T and Jann, K and Natsukawa, H and Kobayashi, T and Tüshaus, L and Koenig, T and Kottlow, M and Achermann, P and Wilson, RS and Mayhew, SD and Assecondi, S and Arvanitis, TN and Bagshaw, AP and Darque, A and Rihs, TA and Grouiller, F and Lazeyras, F and Ha-Vinh Leuchter, R and Caballero, C and Michel, CM and Hüppi, PS and Hauser, TU and Hunt, LT and Iannaccone, R and Stämpfli, P and Brandeis, D and Dolan, RJ and Walitza, S and Brem, S and Graichen, U and Eichardt, R and Fiedler, P and Strohmeier, D and Freitag, S and Zanow, F and Haueisen, J and Lordier, L and Grouiller, F and Van de Ville, D and Sancho Rossignol, A and Cordero, I and Lazeyras, F and Ansermet, F and Hüppi, P and Schläpfer, A and Rubia, K and Brandeis, D and Di Lorenzo, G and Pagani, M and Monaco, L and Daverio, A and Giannoudas, I and Verardo, AR and La Porta, P and Niolu, C and Fernandez, I and Siracusano, A and Tamura, K and Karube, C and Mizuba, T and Matsufuji, M and Takashima, S and Iramina, K and Assecondi, S and Ostwald, D and Bagshaw, AP and Marecek, R and Brazdil, M and Lamos, M and Slavícek, T and Marecek, R and Jan, J and Meier, NM and Perrig, W and Koenig, T and Minami, T and Noritake, Y and Nakauchi, S and Azuma, K and Minami, T and Nakauchi, S and Rodriguez, C and Lenartowicz, A and Cohen, MS and Rodriguez, C and Lenartowicz, A and Cohen, MS and Iramina, K and Kinoshita, H and Tamura, K and Karube, C and Kaneko, M and Ide, J and Noguchi, Y and Cohen, MS and Douglas, PK and Rodriguez, CM and Xia, HJ and Zimmerman, EM and Konopka, CJ and Epstein, PS and Konopka, LM and Giezendanner, S and Fisler, M and Soravia, L and Andreotti, J and Wiest, R and Dierks, T and Federspiel, A and Razavi, N and Federspiel, A and Dierks, T and Hauf, M and Jann, K and Kamada, K and Sato, D and Ito, Y and Okano, K and Mizutani, N and Kobayashi, T and Thelen, A and Murray, M and Pastena, L and Formaggio, E and Storti, SF and Faralli, F and Melucci, M and Gagliardi, R and Ricciardi, L and Ruffino, G and Coito, A and Macku, P and Tyrand, R and Astolfi, L and He, B and Wiest, R and Seeck, M and Michel, C and Plomp, G and Vulliemoz, S and Fischmeister, FP and Glaser, J and Schöpf, V and Bauer, H and Beisteiner, R and Deligianni, F and Centeno, M and Carmichael, DW and Clayden, J and Mingoia, G and Langbein, K and Dietzek, M and Wagner, G and Smesny, S and Scherpiet, S and Maitra, R and Gaser, C and Sauer, H and Nenadic, I and Dürschmid, S and Zaehle, T and Pannek, H and Chang, HF and Voges, J and Rieger, J and Knight, RT and Heinze, HJ and Hinrichs, H and Tsatsishvili, V and Cong, F and Puoliväli, T and Alluri, V and Toiviainen, P and Nandi, AK and Brattico, E and Ristaniemi, T and Grieder, M and Crinelli, RM and Jann, K and Federspiel, A and Wirth, M and Koenig, T and Stein, M and Wahlund, LO and Dierks, T and Atsumori, H and Yamaguchi, R and Okano, Y and Sato, H and Funane, T and Sakamoto, K and Kiguchi, M and Tränkner, A and Schindler, S and Schmidt, F and Strauß, M and Trampel, R and Hegerl, U and Turner, R and Geyer, S and Schönknecht, P and Kebets, V and van Assche, M and Goldstein, R and van der Meulen, M and Vuilleumier, P and Richiardi, J and Van De Ville, D and Assal, F and Wozniak-Kwasniewska, A and Szekely, D and Harquel, S and Bougerol, T and David, O and Bracht, T and Jones, DK and Horn, H and Müller, TJ and Walther, S and Sos, P and Klirova, M and Novak, T and Brunovsky, M and Horacek, J and Bares, M and Hoschl C, C and Fellhauer, I and Zöllner, FG and Schröder, J and Kong, L and Essig, M and Schad, LR and Arrubla, J and Neuner, I and Hahn, D and Boers, F and Shah, NJ and Neuner, I and Arrubla, J and Hahn, D and Boers, F and Jon Shah, N and Suriya Prakash, M and Sharma, R and Kawaguchi, H and Kobayashi, T and Fiedler, P and Griebel, S and Biller, S and Fonseca, C and Vaz, F and Zentner, L and Zanow, F and Haueisen, J and Rochas, V and Rihs, T and Thut, G and Rosenberg, N and Landis, T and Michel, C and Moliadze, V and Schmanke, T and Lyzhko, E and Bassüner, S and Freitag, C and Siniatchkin, M and Thézé, R and Guggisberg, AG and Nahum, L and Schnider, A and Meier, L and Friedrich, H and Jann, K and Landis, B and Wiest, R and Federspiel, A and Strik, W and Dierks, T and Witte, M and Kober, SE and Neuper, C and Wood, G and König, R and Matysiak, A and Kordecki, W and Sieluzycki, C and Zacharias, N and Heil, P and Wyss, C and Boers, F and Arrubla, J and Dammers, J and Kawohl, W and Neuner, I and Shah, NJ and Braboszcz, C and Cahn, RB and Levy, J and Fernandez, M and Delorme, A and Rosas-Martinez, L and Milne, E and Zheng, Y and Urakami, Y and Kawamura, K and Washizawa, Y and Hiyoshi, K and Cichocki, A and Giroud, N and Dellwo, V and Meyer, M and Rufener, KS and Liem, F and Dellwo, V and Meyer, M and Jones-Rounds, JD and Raizada, R and Staljanssens, W and Strobbe, G and van Mierlo, P and Van Holen, R and Vandenberghe, S and Pefkou, M and Becker, R and Michel, C and Hervais-Adelman, A and He, W and Brock, J and Johnson, B and Ohla, K and Hitz, K and Heekeren, K and Obermann, C and Huber, T and Juckel, G and Kawohl, W and Gabriel, D and Comte, A and Henriques, J and Magnin, E and Grigoryeva, L and Ortega, JP and Haffen, E and Moulin, T and Pazart, L and Aubry, R and Kukleta, M and Baris Turak, B and Louvel, J and Crespo-Garcia, M and Cantero, JL and Atienza, M and Connell, S and Kilborn, K and Damborská, A and Brázdil, M and Rektor, I and Kukleta, M and Koberda, JL and Bienkiewicz, A and Koberda, I and Koberda, P and Moses, A and Tomescu, M and Rihs, T and Britz, J and Custo, A and Grouiller, F and Schneider, M and Debbané, M and Eliez, S and Michel, C and Wang, GY and Kydd, R and Wouldes, TA and Jensen, M and Russell, BR and Dissanayaka, N and Au, T and Angwin, A and O'Sullivan, J and Byrne, G and Silburn, P and Marsh, R and Mellic, G and Copland, D and Bänninger, A and Kottlow, M and Díaz Hernàndez, L and Koenig, T and Díaz Hernàndez, L and Bänninger, A and Koenig, T and Hauser, TU and Iannaccone, R and Mathys, C and Ball, J and Drechsler, R and Brandeis, D and Walitza, S and Brem, S and Boeijinga, PH and Pang, EW and Valica, T and Macdonald, MJ and Oh, A and Lerch, JP and Anagnostou, E and Di Lorenzo, G and Pagani, M and Monaco, L and Daverio, A and Verardo, AR and Giannoudas, I and La Porta, P and Niolu, C and Fernandez, I and Siracusano, A and Shimada, T and Matsuda, Y and Monkawa, A and Monkawa, T and Hashimoto, R and Watanabe, K and Kawasaki, Y and Matsuda, Y and Shimada, T and Monkawa, T and Monkawa, A and Watanabe, K and Kawasaki, Y and Stegmayer, K and Horn, H and Federspiel, A and Razavi, N and Bracht, T and Laimböck, K and Strik, W and Dierks, T and Wiest, R and Müller, TJ and Walther, S and Koorenhof, LJ and Swithenby, SJ and Martins-Mourao, A and Rihs, TA and Tomescu, M and Song, KW and Custo, A and Knebel, JF and Murray, M and Eliez, S and Michel, CM and Volpe, U and Merlotti, E and Vignapiano, A and Montefusco, V and Plescia, GM and Gallo, O and Romano, P and Mucci, A and Galderisi, S and Laimboeck, K and Jann, K and Walther, S and Federspiel, A and Wiest, R and Strik, W and Horn, H},
  journal = {Clinical EEG and neuroscience},
  year = {2013},
  doi = {10.1177/1550059413507209},
  pmid = {24368763},
  url = {https://pubmed.ncbi.nlm.nih.gov/24368763/},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Lin201324109946,
  title = {A mobile SSVEP-based brain-computer interface for freely moving humans: the robustness of canonical correlation analysis to motion artifacts.},
  author = {Lin, YP and Wang, Y and Jung, TP},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2013},
  doi = {10.1109/EMBC.2013.6609759},
  pmid = {24109946},
  url = {https://pubmed.ncbi.nlm.nih.gov/24109946/},
  abstract = {Recently, translating a steady-state visual-evoked potential (SSVEP)-based brain-computer interface (BCI) from laboratory settings to real-life applications has gained increasing attention. This study systematically tests the signal quality of SSVEP acquired by a mobile electroencephalogram (EEG) system, which features dry electrodes and wireless telemetry, under challenging (e.g. walking) recording conditions. Empirical results of this study demonstrated the robustness of canonical correlation analysis (CCA) to movement artifacts for SSVEP detection. This demonstration considerably improves the practicality of real-life applications of mobile and wireless BCI systems for users actively behaving in and interacting with their environments.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Li201222248583,
  title = {β1 integrin gene excision in the adult murine cardiac myocyte causes defective mechanical and signaling responses.},
  author = {Li, R and Wu, Y and Manso, AM and Gu, Y and Liao, P and Israeli, S and Yajima, T and Nguyen, U and Huang, MS and Dalton, ND and Peterson, KL and Ross, RS},
  journal = {The American journal of pathology},
  year = {2012},
  doi = {10.1016/j.ajpath.2011.12.007},
  pmid = {22248583},
  url = {https://pubmed.ncbi.nlm.nih.gov/22248583/},
  abstract = {How mechanical signals are transmitted in the cardiac myocyte is poorly understood. In this study, we produced a tamoxifen-inducible mouse model in which β1 integrin could be reduced specifically in the adult cardiomyocyte, so that the function of this integrin could be assessed in the postnatal and mechanically stressed heart. The expression of β1 integrin was reduced to 35% of control levels, but function remained normal at baseline. With aortic constriction, the knockout mice survived but had a blunted hypertrophic response. Integrin knockout myocytes, in contrast to controls, showed reduced integrin-linked kinase expression both at baseline and after hemodynamic stress; focal adhesion kinase expression was reduced after stress. Alterations in multiple signaling pathways were detected in the integrin knockout group after acute and chronic hemodynamic stress. Most remarkably, when we challenged the knockout mice with short-term loading, the robust responses of several kinases (extracellular signal-regulated kinase 1/2, p38, and Akt) evident in control mice were essentially abolished in the knockout mice. We also found that reduction of myocyte β1 integrin expression modified adrenergic-mediated signaling through extracellular signal-regulated kinase, p38, and Akt. Reduction of β1 integrin expression in the mature cardiac myocyte leads to a varied response compared with when this protein is reduced during either the embryonic or perinatal period. These results show that β1 integrin expression is required for proper mechanotransductive and adrenergic responses of the adult heart.},
  note = {PubMed query source: Ying Wu}
}

@article{Kamiski201222155528,
  title = {β band oscillations engagement in human alertness process.},
  author = {Kamiński, J and Brzezicka, A and Gola, M and Wróbel, A},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2012},
  doi = {10.1016/j.ijpsycho.2011.11.006},
  pmid = {22155528},
  url = {https://pubmed.ncbi.nlm.nih.gov/22155528/},
  abstract = {We previously showed that neuronal activity in beta frequency might serve as a carrier for attentional arousal within the visual system of cat. In the present study, we adopted the animal paradigm for anticipatory attention to study alertness-related changes of beta activity in human subjects. The results indicated that increased alertness, manifested by faster responses to target visual stimuli, is accompanied by higher EEG activation in beta band.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Gola201221925215,
  title = {β band oscillations as a correlate of alertness--changes in aging.},
  author = {Gola, M and Kamiński, J and Brzezicka, A and Wróbel, A},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2012},
  doi = {10.1016/j.ijpsycho.2011.09.001},
  pmid = {21925215},
  url = {https://pubmed.ncbi.nlm.nih.gov/21925215/},
  abstract = {Older adults (>60 years) show attentional deficits in comparison to younger people (18-30 years). As beta-band EEG activity has been previously postulated to indicate attentional modulation in the visual system, we searched for possible deficits in beta power in elderly subjects performing an attentional task with spatial differentiation between visual stimuli. We found that in older adults a lower level of beta activity correlated with decreased behavioral performance. As compared to young subjects, older adults expressed decreased activation in beta band during an attentional task, which displayed two different dynamics during the anticipatory period. Those dynamics were accompanied by one of two different behavioral pattern deficits. We hypothesize that one group of elderly participants suffered from difficulty in the activation of attentional processes (alertness deficits), while the other--from difficulty in sustaining those processes (vigilance deficits).},
  note = {PubMed query source: Mateusz Gola}
}

@article{Grandchamp201223367475,
  title = {Stability of ICA decomposition across within-subject EEG datasets.},
  author = {Grandchamp, R and Braboszcz, C and Makeig, S and Delorme, A},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6347540},
  pmid = {23367475},
  url = {https://pubmed.ncbi.nlm.nih.gov/23367475/},
  abstract = {Independent Component Analysis (ICA) has been successfully used to identify brain related signals and artifacts from multi-channel electroencephalographic (EEG) data. However the stability of ICA decompositions across sessions from a single subject has not been investigated. The goal of this study was to isolate EEG independent components (ICs) across sessions for each subject so as to assess whether ICs are reproducible across sessions. We used 64-channel EEG data recorded from two subjects during a simple mind-wandering experiment. Each subject participated in 11 twenty-minute sessions over a period of five weeks. Extended Infomax ICA decomposition was performed on the continuous data of each session. We used a simple IC clustering technique based on correlation of scalp topographies. Several clusters of homogenous components were identified for each subject. Typical component clusters accounting for eye movement and eye blink artifacts were identified. Both clusters included one component from each recording session. In addition, several clusters corresponding to brain electrical sources, among them clusters exhibiting prominent alpha, beta and Mu band activities, included components from most sessions. These results present evidence that ICA can provide relatively stable solutions across sessions, with important implications for Brain Computer Interface research.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Mullen201223366536,
  title = {Multivariate principal oscillation pattern analysis of ICA sources during seizure.},
  author = {Mullen, T and Worrell, G and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6346575},
  pmid = {23366536},
  url = {https://pubmed.ncbi.nlm.nih.gov/23366536/},
  abstract = {Mapping the dynamics of neural source processes critically involved in initiating and propagating seizure activity is important for effective epilepsy diagnosis, intervention, and treatment. Tracking time-varying shifts in the oscillation modes of an evolving seizure may be useful for both seizure onset detection as well as for improved non-surgical interventions such as microstimulation. In this report we apply a multivariate eigendecomposition method to analyze the time-varying principal oscillation patterns (POPs, or eigenmodes) of maximally-independent (ICA) sources of intracranial EEG data recorded from subdural electrodes implanted in a human patient for evaluation of surgery for epilepsy. Our analysis of a subset of the most dynamically important eigenmodes reveals distinct shifts in characteristic frequency and damping time before, throughout, and following seizures providing insight into the dynamical structure of the system throughout seizure evolution.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme201222355308,
  title = {Independent EEG sources are dipolar.},
  author = {Delorme, A and Palmer, J and Onton, J and Oostenveld, R and Makeig, S},
  journal = {PloS one},
  year = {2012},
  doi = {10.1371/journal.pone.0030135},
  pmid = {22355308},
  url = {https://pubmed.ncbi.nlm.nih.gov/22355308/},
  abstract = {Independent component analysis (ICA) and blind source separation (BSS) methods are increasingly used to separate individual brain and non-brain source signals mixed by volume conduction in electroencephalographic (EEG) and other electrophysiological recordings. We compared results of decomposing thirteen 71-channel human scalp EEG datasets by 22 ICA and BSS algorithms, assessing the pairwise mutual information (PMI) in scalp channel pairs, the remaining PMI in component pairs, the overall mutual information reduction (MIR) effected by each decomposition, and decomposition 'dipolarity' defined as the number of component scalp maps matching the projection of a single equivalent dipole with less than a given residual variance. The least well-performing algorithm was principal component analysis (PCA); best performing were AMICA and other likelihood/mutual information based ICA methods. Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. To encourage further method comparisons, the data and software used to prepare the results have been made available (http://sccn.ucsd.edu/wiki/BSSComparison).},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wisniewski201222911734,
  title = {Familiarity with speech affects cortical processing of auditory distance cues and increases acuity.},
  author = {Wisniewski, MG and Mercado, E and Gramann, K and Makeig, S},
  journal = {PloS one},
  year = {2012},
  doi = {10.1371/journal.pone.0041025},
  pmid = {22911734},
  url = {https://pubmed.ncbi.nlm.nih.gov/22911734/},
  abstract = {Several acoustic cues contribute to auditory distance estimation. Nonacoustic cues, including familiarity, may also play a role. We tested participants' ability to distinguish the distances of acoustically similar sounds that differed in familiarity. Participants were better able to judge the distances of familiar sounds. Electroencephalographic (EEG) recordings collected while participants performed this auditory distance judgment task revealed that several cortical regions responded in different ways depending on sound familiarity. Surprisingly, these differences were observed in auditory cortical regions as well as other cortical regions distributed throughout both hemispheres. These data suggest that learning about subtle, distance-dependent variations in complex speech sounds involves processing in a broad cortical network that contributes both to speech recognition and to how spatial information is extracted from speech.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lin201222348883,
  title = {EEG correlates of haptic feedback in a visuomotor tracking task.},
  author = {Lin, CL and Shaw, FZ and Young, KY and Lin, CT and Jung, TP},
  journal = {NeuroImage},
  year = {2012},
  doi = {10.1016/j.neuroimage.2012.02.008},
  pmid = {22348883},
  url = {https://pubmed.ncbi.nlm.nih.gov/22348883/},
  abstract = {This study investigates the temporal brain dynamics associated with haptic feedback in a visuomotor tracking task. Haptic feedback with deviation-related forces was used throughout tracking experiments in which subjects' behavioral responses and electroencephalogram (EEG) data were simultaneously measured. Independent component analysis was employed to decompose the acquired EEG signals into temporally independent time courses arising from distinct brain sources. Clustering analysis was used to extract independent components that were comparable across participants. The resultant independent brain processes were further analyzed via time-frequency analysis (event-related spectral perturbation) and event-related coherence (ERCOH) to contrast brain activity during tracking experiments with or without haptic feedback. Across subjects, in epochs with haptic feedback, components with equivalent dipoles in or near the right motor region exhibited greater alpha band power suppression. Components with equivalent dipoles in or near the left frontal, central, left motor, right motor, and parietal regions exhibited greater beta-band power suppression, while components with equivalent dipoles in or near the left frontal, left motor, and right motor regions showed greater gamma-band power suppression relative to non-haptic conditions. In contrast, the right occipital component cluster exhibited less beta-band power suppression in epochs with haptic feedback compared to non-haptic conditions. The results of ERCOH analysis of the six component clusters showed that there were significant increases in coherence between different brain networks in response to haptic feedback relative to the coherence observed when haptic feedback was not present. The results of this study provide novel insight into the effects of haptic feedback on the brain and may aid the development of new tools to facilitate the learning of motor skills.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chi201222180514,
  title = {Dry and noncontact EEG sensors for mobile brain-computer interfaces.},
  author = {Chi, YM and Wang, YT and Wang, Y and Maier, C and Jung, TP and Cauwenberghs, G},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2012},
  doi = {10.1109/TNSRE.2011.2174652},
  pmid = {22180514},
  url = {https://pubmed.ncbi.nlm.nih.gov/22180514/},
  abstract = {Dry and noncontact electroencephalographic (EEG) electrodes, which do not require gel or even direct scalp coupling, have been considered as an enabler of practical, real-world, brain-computer interface (BCI) platforms. This study compares wet electrodes to dry and through hair, noncontact electrodes within a steady state visual evoked potential (SSVEP) BCI paradigm. The construction of a dry contact electrode, featuring fingered contact posts and active buffering circuitry is presented. Additionally, the development of a new, noncontact, capacitive electrode that utilizes a custom integrated, high-impedance analog front-end is introduced. Offline tests on 10 subjects characterize the signal quality from the different electrodes and demonstrate that acquisition of small amplitude, SSVEP signals is possible, even through hair using the new integrated noncontact sensor. Online BCI experiments demonstrate that the information transfer rate (ITR) with the dry electrodes is comparable to that of wet electrodes, completely without the need for gel or other conductive media. In addition, data from the noncontact electrode, operating on the top of hair, show a maximum ITR in excess of 19 bits/min at 100% accuracy (versus 29.2 bits/min for wet electrodes and 34.4 bits/min for dry electrodes), a level that has never been demonstrated before. The results of these experiments show that both dry and noncontact electrodes, with further development, may become a viable tool for both future mobile BCI and general EEG applications.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Chuang201222634852,
  title = {Co-modulatory spectral changes in independent brain processes are correlated with task performance.},
  author = {Chuang, SW and Ko, LW and Lin, YP and Huang, RS and Jung, TP and Lin, CT},
  journal = {NeuroImage},
  year = {2012},
  doi = {10.1016/j.neuroimage.2012.05.035},
  pmid = {22634852},
  url = {https://pubmed.ncbi.nlm.nih.gov/22634852/},
  abstract = {This study investigates the independent modulators that mediate the power spectra of electrophysiological processes, measured by electroencephalogram (EEG), in a sustained-attention experiment. EEG and behavioral data were collected during 1-2 hour virtual-reality based driving experiments in which subjects were instructed to maintain their cruising position and compensate for randomly induced drift using the steering wheel. Independent component analysis (ICA) applied to 30-channel EEG data separated the recorded EEG signals into a sum of maximally temporally independent components (ICs) for each of 30 subjects. Logarithmic spectra of resultant IC activities were then decomposed by principal component analysis, followed by ICA, to find spectrally fixed and temporally independent modulators (IM). Across subjects, the spectral ICA consistently found four performance-related independent modulators: delta, delta-theta, alpha, and beta modulators that multiplicatively affected the spectra of spatially distinct IC processes when the participants experienced waves of alternating alertness and drowsiness during long-hour simulated driving. The activation of the delta-theta modulator increased monotonically as subjects' task performances decreased. Furthermore, the time courses of the theta-beta modulator were highly correlated with concurrent changes in driving errors across subjects (r=0.77±0.13).},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Loo201222814935,
  title = {Clinical utility of EEG in attention-deficit/hyperactivity disorder: a research update.},
  author = {Loo, SK and Makeig, S},
  journal = {Neurotherapeutics : the journal of the American Society for Experimental NeuroTherapeutics},
  year = {2012},
  doi = {10.1007/s13311-012-0131-z},
  pmid = {22814935},
  url = {https://pubmed.ncbi.nlm.nih.gov/22814935/},
  abstract = {Psychiatric research applications of electroencephalography (EEG), the earliest approach to imaging human cortical brain activity, are attracting increasing scientific and clinical interest. For more than 40 years, EEG research has attempted to characterize and quantify the neurophysiology of attention-deficit/hyperactivity disorder (ADHD), most consistently associating it with increased frontocentral theta band activity and increased theta to beta (θ/β) power ratio during rest compared to non-ADHD controls. Recent reports suggest that while these EEG measures demonstrate strong discriminant validity for ADHD, significant EEG heterogeneity also exists across ADHD-diagnosed individuals. In particular, additional studies validating the use of the θ/β power ratio measure appear to be needed before it can be used for clinical diagnosis. In recent years, the number and the scientific quality of research reports on EEG-based neurofeedback (NF) for ADHD have grown considerably, although the studies reviewed here do not yet support NF training as a first-line, stand-alone treatment modality. In particular, more research is needed comparing NF to placebo control and other effective treatments for ADHD. Currently, after a long period of relative stasis, the neurophysiological specificity of measures used in EEG research is rapidly increasing. It is likely, therefore, that new EEG studies of ADHD using higher density recordings and new measures drawn from viewing EEG as a 3-dimensional functional imaging modality, as well as intensive re-analyses of existing EEG study data, can better characterize the neurophysiological differences between and within ADHD and non-ADHD subjects, and lead to more precise diagnostic measures and effective NF approaches.},
  note = {PubMed query source: Scott Makeig}
}

@article{Meng201223028544,
  title = {Characterization and robust classification of EEG signal from image RSVP events with independent time-frequency features.},
  author = {Meng, J and Meriño, LM and Bigdely Shamlo, N and Makeig, S and Robbins, K and Huang, Y},
  journal = {PloS one},
  year = {2012},
  doi = {10.1371/journal.pone.0044464},
  pmid = {23028544},
  url = {https://pubmed.ncbi.nlm.nih.gov/23028544/},
  abstract = {This paper considers the problem of automatic characterization and detection of target images in a rapid serial visual presentation (RSVP) task based on EEG data. A novel method that aims to identify single-trial event-related potentials (ERPs) in time-frequency is proposed, and a robust classifier with feature clustering is developed to better utilize the correlated ERP features. The method is applied to EEG recordings of a RSVP experiment with multiple sessions and subjects.The results show that the target image events are mainly characterized by 3 distinct patterns in the time-frequency domain, i.e., a theta band (4.3 Hz) power boosting 300-700 ms after the target image onset, an alpha band (12 Hz) power boosting 500-1000 ms after the stimulus onset, and a delta band (2 Hz) power boosting after 500 ms. The most discriminant time-frequency features are power boosting and are relatively consistent among multiple sessions and subjects.Since the original discriminant time-frequency features are highly correlated, we constructed the uncorrelated features using hierarchical clustering for better classification of target and non-target images. With feature clustering, performance (area under ROC) improved from 0.85 to 0.89 on within-session tests, and from 0.76 to 0.84 on cross-subject tests. The constructed uncorrelated features were more robust than the original discriminant features and corresponded to a number of local regions on the time-frequency plane. The data and code are available at: http://compgenomics.cbi.utsa.edu/rsvp/index.html.},
  note = {PubMed query source: Scott Makeig}
}

@article{Rapela201223365902,
  title = {Brain oscillations in switching vs. focusing audio-visual attention.},
  author = {Rapela, J and Gramann, K and Westerfield, M and Townsend, J and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6345941},
  pmid = {23365902},
  url = {https://pubmed.ncbi.nlm.nih.gov/23365902/},
  abstract = {Selective attention contributes to perceptual efficiency by modulating cortical activity according to task demands. The majority of attentional research has focused on the effects of attention to a single modality, and little is known about the role of attention in multimodal sensory processing. Here we employ a novel experimental design to examine the electrophysiological basis of audio-visual attention shifting. We use electroencephalography (EEG) to study differences in brain dynamics between quickly shifting attention between modalities and focusing attention on a single modality for extended periods of time. We also address interactions between attentional effects generated by the attention-shifting cue and those generated by subsequent stimuli. The conclusions from these examinations address key issues in attentional research, including the supramodal theory of attention, or the role of attention in foveal vision. The experimental design and analysis methods used here may suggest new directions in the study of the physiological basis of attention.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lin201223366994,
  title = {Brain dynamics of mathematical problem solving.},
  author = {Lin, CL and Jung, M and Wu, YC and Lin, CT and She, HC},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6347033},
  pmid = {23366994},
  url = {https://pubmed.ncbi.nlm.nih.gov/23366994/},
  abstract = {The purpose of this study is to examine brain activities of participants solving mental math problems. The research investigated how problem difficulty affected the subjects' responses and electroencephalogram (EEG) in different brain regions. In general, it was found that solution latencies (SL) to the math problems increased with difficulty. The EEG results showed that across subjects, the right-central beta, left-parietal theta, left-occipital theta and alpha, right-parietal alpha and beta, medial-frontal beta and medial central theta power decreased as task difficulty increased. This study further explored the effects of problem-solving performance on the EEG. Slow solvers exhibited greater frontal theta activities in the right hemisphere, whereas an inverse pattern of hemispheric asymmetry was found in fast solvers. Furthermore, analyses of spatio-temporal brain dynamics during problem solving show progressively stronger alpha- and beta-power suppression and theta-power augmentation as subjects were reaching a solution. These findings provide a better understanding of cortical activities mediating math-based problem solving and knowledge acquisition that can ultimately benefit math learning and education.},
  note = {PubMed query source: Ying Wu}
}

@article{Rapela201223366682,
  title = {Assisting autistic children with wireless EOG technology.},
  author = {Rapela, J and Lin, TY and Westerfield, M and Jung, TP and Townsend, J},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6346721},
  pmid = {23366682},
  url = {https://pubmed.ncbi.nlm.nih.gov/23366682/},
  abstract = {We propose a novel intervention to train the speed and accuracy of attention orienting and eye movements in Autism Spectrum Disorder (ASD). Training eye movements and attention could not only affect those important functions directly, but could also result in broader improvement of social communication skills. To this end we describe a system that would allow ASD children to improve their fixation skills while playing a computer game controlled by an eye tracker. Because this intervention will probably be time consuming, this system should be designed to be used at homes. To make this possible, we propose an implementation based on wireless and dry electrooculography (EOG) technology. If successful, this system would develop an approach to therapy that would improve clinical and behavioral function in children and adults with ASD. As our initial steps in this direction, here we describe the design of a computer game to be used in this system, and the predictions of gaze position from EOG data recorded while a subject played this game.},
  note = {PubMed query source: Tzyy-Ping Jung}
}

@article{Cao201223366198,
  title = {A physiologically motivated sparse, compact, and smooth (SCS) approach to EEG source localization.},
  author = {Cao, C and Akalin Acar, Z and Kreutz-Delgado, K and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2012},
  doi = {10.1109/EMBC.2012.6346237},
  pmid = {23366198},
  url = {https://pubmed.ncbi.nlm.nih.gov/23366198/},
  abstract = {Here, we introduce a novel approach to the EEG inverse problem based on the assumption that principal cortical sources of multi-channel EEG recordings may be assumed to be spatially sparse, compact, and smooth (SCS). To enforce these characteristics of solutions to the EEG inverse problem, we propose a correlation-variance model which factors a cortical source space covariance matrix into the multiplication of a pre-given correlation coefficient matrix and the square root of the diagonal variance matrix learned from the data under a Bayesian learning framework. We tested the SCS method using simulated EEG data with various SNR and applied it to a real ECOG data set. We compare the results of SCS to those of an established SBL algorithm.},
  note = {PubMed query source: Scott Makeig}
}

@article{Grandchamp201121994498,
  title = {Single-trial normalization for event-related spectral decomposition reduces sensitivity to noisy trials.},
  author = {Grandchamp, R and Delorme, A},
  journal = {Frontiers in psychology},
  year = {2011},
  doi = {10.3389/fpsyg.2011.00236},
  pmid = {21994498},
  url = {https://pubmed.ncbi.nlm.nih.gov/21994498/},
  abstract = {In electroencephalography, the classical event-related potential model often proves to be a limited method to study complex brain dynamics. For this reason, spectral techniques adapted from signal processing such as event-related spectral perturbation (ERSP) - and its variant event-related synchronization and event-related desynchronization - have been used over the past 20 years. They represent average spectral changes in response to a stimulus. These spectral methods do not have strong consensus for comparing pre- and post-stimulus activity. When computing ERSP, pre-stimulus baseline removal is usually performed after averaging the spectral estimate of multiple trials. Correcting the baseline of each single-trial prior to averaging spectral estimates is an alternative baseline correction method. However, we show that this method leads to positively skewed post-stimulus ERSP values. We eventually present new single-trial-based ERSP baseline correction methods that perform trial normalization or centering prior to applying classical baseline correction methods. We show that single-trial correction methods minimize the contribution of artifactual data trials with high-amplitude spectral estimates and are robust to outliers when performing statistical inference testing. We then characterize these methods in terms of their time-frequency responses and behavior compared to classical ERSP methods.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Mullen201122254582,
  title = {Modeling cortical source dynamics and interactions during seizure.},
  author = {Mullen, T and Acar, ZA and Worrell, G and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2011},
  doi = {10.1109/IEMBS.2011.6090332},
  pmid = {22254582},
  url = {https://pubmed.ncbi.nlm.nih.gov/22254582/},
  abstract = {Mapping the dynamics and spatial topography of brain source processes critically involved in initiating and propagating seizure activity is critical for effective epilepsy diagnosis, intervention, and treatment. In this report we analyze neuronal dynamics before and during epileptic seizures using adaptive multivariate autoregressive (VAR) models applied to maximally-independent (ICA) sources of intracranial EEG (iEEG, ECoG) data recorded from subdural electrodes implanted in a human patient for evaluation of surgery for epilepsy. We visualize the spatial distribution of causal sources and sinks of ictal activity on the cortical surface (gyral and sulcal) using a novel combination of multivariate Granger-causal and graph-theoretic metrics combined with distributed source localization by Sparse Bayesian Learning applied to a multi-scale patch basis. This analysis reveals and visualizes distinct, seizure stage-dependent shifts in inter-component spatiotemporal dynamics and connectivity including the clinically-identified epileptic foci.},
  note = {PubMed query source: Scott Makeig}
}

@article{Braboszcz201120946963,
  title = {Lost in thoughts: neural markers of low alertness during mind wandering.},
  author = {Braboszcz, C and Delorme, A},
  journal = {NeuroImage},
  year = {2011},
  doi = {10.1016/j.neuroimage.2010.10.008},
  pmid = {20946963},
  url = {https://pubmed.ncbi.nlm.nih.gov/20946963/},
  abstract = {During concentration tasks, spontaneous attention shifts occurs towards self-centered matters. Little is known about the brain oscillatory activity underlying these mental phenomena. We recorded 128-channels electroencephalographic activity from 12 subjects performing a breath-counting task. Subjects were instructed to press a button whenever, based on their introspective experience, they realized their attention had drifted away from the task. Theta (4-7 Hz) and delta (2-3.5 Hz) EEG activity increased during mind wandering whereas alpha (9-11 Hz) and beta (15-30 Hz) decreased. A passive auditory oddball protocol was presented to the subjects to test brain-evoked responses to perceptual stimuli during mind wandering. Mismatch negativity evoked at 100 ms after oddball stimuli onset decreased during mind wandering whereas the brain-evoked responses at 200 ms after stimuli onset increased. Spectral analyses and evoked related potential results suggest decreased alertness and sensory processing during mind wandering. To our knowledge, our experiment is one of the first neuro-imaging studies that relies purely on subjects' introspective judgment, and shows that such judgment may be used to contrast different brain activity patterns.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Kothe201122255839,
  title = {Estimation of task workload from EEG data: new and current tools and perspectives.},
  author = {Kothe, CA and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2011},
  doi = {10.1109/IEMBS.2011.6091615},
  pmid = {22255839},
  url = {https://pubmed.ncbi.nlm.nih.gov/22255839/},
  abstract = {We report, as part of the EMBC meeting Cognitive State Assessment (CSA) competition 2011, an empirical comparison using robust cross-validation of the performance of eleven computational approaches to real-time electroencephalography (EEG) based mental workload monitoring on Multi-Attribute Task Battery data from eight subjects. We propose a new approach, Overcomplete Spectral Regression, that combines several potentially advantageous attributes and empirically demonstrate its superior performance on these data compared to the ten other CSA methods tested. We discuss results from computational, neuroscience and experimentation points of view.},
  note = {PubMed query source: Scott Makeig}
}

@article{Acar201122255194,
  title = {Electrocortical source imaging of intracranial EEG data in epilepsy.},
  author = {Acar, ZA and Palmer, J and Worrell, G and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2011},
  doi = {10.1109/IEMBS.2011.6090971},
  pmid = {22255194},
  url = {https://pubmed.ncbi.nlm.nih.gov/22255194/},
  abstract = {Here we report first results of numerical methods for modeling the dynamic structure and evolution of epileptic seizure activity in an intracranial subdural electrode recording from a patient with partial refractory epilepsy. A 16-min dataset containing two seizures was decomposed using up to five competing adaptive mixture independent component analysis (AMICA) models. Multiple models modeled early or late ictal, or pre- or post-ictal periods in the data, respectively. To localize sources, a realistic Boundary Element Method (BEM) head model was constructed for the patient with custom open skull and plastic (non-conductive) electrode holder features. Source localization was performed using Sparse Bayesian Learning (SBL) on a dictionary of overlapping multi-scale cortical patches constructed from 80,130 dipoles in gray matter perpendicular to the cortical surface. Remaining mutual information among seizure-model AMICA components was dominated by two dependent component subspaces with largely contiguous source domains localized to superior frontal gyrus and precentral gyrus; these accounted for most of the ictal activity. Similar though much weaker dependent subspaces were also revealed in pre-ictal data by the associated AMICA model. Electrocortical source imaging appears promising both for clinical epilepsy research and for basic cognitive neuroscience research using volunteer patients who must undergo invasive monitoring for medical purposes.},
  note = {PubMed query source: Scott Makeig}
}

@article{Radin201121907152,
  title = {Electrocortical activity prior to unpredictable stimuli in meditators and nonmeditators.},
  author = {Radin, DI and Vieten, C and Michel, L and Delorme, A},
  journal = {Explore (New York, N.Y.)},
  year = {2011},
  doi = {10.1016/j.explore.2011.06.004},
  pmid = {21907152},
  url = {https://pubmed.ncbi.nlm.nih.gov/21907152/},
  abstract = {Advanced meditators occasionally report experiences of timelessness, or states of awareness that seem to transcend the usual boundaries of the subjective present. This type of experience was investigated in eight experienced meditators and eight matched controls by measuring 32 channels of EEG before, during, and after exposure to unpredictable light and sound stimuli. The experiment postulated that if some aspect of consciousness extends beyond the present moment, then prestimulus electrocortical signals should differ depending on stimuli that were about to be selected by a truly random process, and that if such experiences were catalyzed through meditation practice, then prestimulus differences should be more apparent in meditators than in nonmeditators. Each of the 32 EEG channels was baseline adjusted on each trial by the electrical potential averaged between two- and one-second prestimulus, then for each channel the average potential was determined from one-second prestimulus to stimulus onset. The resulting means across subjects in each group were compared by stimulus type using randomized permutation procedures and corrected for multiple comparisons. Within the control group, no EEG channels showed significant prestimulus differences between light versus sound stimulus conditions, but within the meditator group five of 32 channels resulted in significant differences (P < .05, two tailed). Comparisons between control and meditator groups showed significant prestimulus differences prior to audio tone stimuli in 14 of 32 channels (P < .05, two tailed, of which eight channels were P < .005, two tailed). This outcome successfully replicates effects reported in earlier experiments, suggesting that sometimes the subjective sense of awareness extending into the future may be ontologically accurate.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Gwin201120832484,
  title = {Electrocortical activity is coupled to gait cycle phase during treadmill walking.},
  author = {Gwin, JT and Gramann, K and Makeig, S and Ferris, DP},
  journal = {NeuroImage},
  year = {2011},
  doi = {10.1016/j.neuroimage.2010.08.066},
  pmid = {20832484},
  url = {https://pubmed.ncbi.nlm.nih.gov/20832484/},
  abstract = {Recent findings suggest that human cortex is more active during steady-speed unperturbed locomotion than previously thought. However, techniques that have been used to image the brain during locomotion lack the temporal resolution necessary to assess intra-stride cortical dynamics. Our aim was to determine if electrocortical activity is coupled to gait cycle phase during steady-speed human walking. We used electroencephalography (EEG), motion capture, and a force-measuring treadmill to record brain and body dynamics while eight healthy young adult subjects walked on a treadmill. Infomax independent component analysis (ICA) parsed EEG signals into maximally independent component (IC) processes representing electrocortical sources, muscle sources, and artifacts. We calculated a spatially fixed equivalent current dipole for each IC using an inverse modeling approach, and clustered electrocortical sources across subjects by similarities in dipole locations and power spectra. We then computed spectrograms for each electrocortical source that were time-locked to the gait cycle. Electrocortical sources in the anterior cingulate, posterior parietal, and sensorimotor cortex exhibited significant (p<0.05) intra-stride changes in spectral power. During the end of stance, as the leading foot was contacting the ground and the trailing foot was pushing off, alpha- and beta-band spectral power increased in or near the left/right sensorimotor and dorsal anterior cingulate cortex. Power increases in the left/right sensorimotor cortex were more pronounced for contralateral limb push-off (ipsilateral heel-strike) than for ipsilateral limb push-off (contralateral heel-strike). Intra-stride high-gamma spectral power changes were evident in anterior cingulate, posterior parietal, and sensorimotor cortex. These data confirm cortical involvement in steady-speed human locomotion. Future applications of these techniques could provide critical insight into the neural mechanisms of movement disorders and gait rehabilitation.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme201121687590,
  title = {EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing.},
  author = {Delorme, A and Mullen, T and Kothe, C and Akalin Acar, Z and Bigdely-Shamlo, N and Vankov, A and Makeig, S},
  journal = {Computational intelligence and neuroscience},
  year = {2011},
  doi = {10.1155/2011/130714},
  pmid = {21687590},
  url = {https://pubmed.ncbi.nlm.nih.gov/21687590/},
  abstract = {We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLAB software environment, a freely available and readily extensible processing environment running under Matlab. The new tools include (1) a new and flexible EEGLAB STUDY design facility for framing and performing statistical analyses on data from multiple subjects; (2) a neuroelectromagnetic forward head modeling toolbox (NFT) for building realistic electrical head models from available data; (3) a source information flow toolbox (SIFT) for modeling ongoing or event-related effective connectivity between cortical areas; (4) a BCILAB toolbox for building online brain-computer interface (BCI) models from available data, and (5) an experimental real-time interactive control and analysis (ERICA) environment for real-time production and coordination of interactive, multimodal experiments.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Mueller201122049425,
  title = {Dopamine effects on human error processing depend on catechol-O-methyltransferase VAL158MET genotype.},
  author = {Mueller, EM and Makeig, S and Stemmler, G and Hennig, J and Wacker, J},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2011},
  doi = {10.1523/JNEUROSCI.2103-11.2011},
  pmid = {22049425},
  url = {https://pubmed.ncbi.nlm.nih.gov/22049425/},
  abstract = {Brain dopamine (DA) has been linked to error processing. Because high and low (vs medium) prefrontal cortex (PFC) DA levels may facilitate D2-receptor-related modulations of PFC neural activation patterns, we hypothesized that high and low DA predicts increased error-specific transitions of PFC activity. Male human participants (n = 169) were genotyped for the catechol-O-methyltransferase (COMT) Val158Met polymorphism, associated with low (Val) and medium (Met) PFC DA levels. In addition, DRD2TaqIa and 5-HTTLPR, associated with striatal D(2) receptor density and serotonin uptake, respectively, were assessed. Participants received placebo or a selective DA-D(2) receptor blocker (sulpiride, 200 mg) and performed a Flanker task. EEG was recorded and decomposed into independent brain components (ICs) using independent component analysis. After errors, participants displayed (1) a negative deflection in ICs source-localized to the proximity of the anterior midcingulate cortex [IC-error-related negativity (IC-ERN)], (2) increased midcingulate cortex IC power in the delta/theta frequency range, and (3) slowing in the subsequent trial [posterror slowing (PES)]. Importantly, all, IC-ERN, delta/theta power, and PES were modulated by COMT × Substance interactions such that the Val allele predicted elevated IC-ERN, delta/theta power, and PES after placebo; this association was reversed under sulpiride. Because low doses of sulpiride presumably increase PFC DA levels, the COMT × Substance interaction supports the hypothesis that low (Val, placebo) and high (Met, sulpiride) versus medium (Val, sulpiride; Met, placebo) DA levels elevate reactivity to errors. Consistent with an influence of serotonin on PFC DA, the COMT × Substance interaction was modulated by 5-HTTLPR.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gramann201122070621,
  title = {Cognition in action: imaging brain/body dynamics in mobile humans.},
  author = {Gramann, K and Gwin, JT and Ferris, DP and Oie, K and Jung, TP and Lin, CT and Liao, LD and Makeig, S},
  journal = {Reviews in the neurosciences},
  year = {2011},
  doi = {10.1515/RNS.2011.047},
  pmid = {22070621},
  url = {https://pubmed.ncbi.nlm.nih.gov/22070621/},
  abstract = {We have recently developed a mobile brain imaging method (MoBI), that allows for simultaneous recording of brain and body dynamics of humans actively behaving in and interacting with their environment. A mobile imaging approach was needed to study cognitive processes that are inherently based on the use of human physical structure to obtain behavioral goals. This review gives examples of the tight coupling between human physical structure with cognitive processing and the role of supraspinal activity during control of human stance and locomotion. Existing brain imaging methods for actively behaving participants are described and new sensor technology allowing for mobile recordings of different behavioral states in humans is introduced. Finally, we review recent work demonstrating the feasibility of a MoBI system that was developed at the Swartz Center for Computational Neuroscience at the University of California, San Diego, demonstrating the range of behavior that can be investigated with this method.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wu201121864890,
  title = {Are depictive gestures like pictures? commonalities and differences in semantic processing.},
  author = {Wu, YC and Coulson, S},
  journal = {Brain and language},
  year = {2011},
  doi = {10.1016/j.bandl.2011.07.002},
  pmid = {21864890},
  url = {https://pubmed.ncbi.nlm.nih.gov/21864890/},
  abstract = {Conversation is multi-modal, involving both talk and gesture. Does understanding depictive gestures engage processes similar to those recruited in the comprehension of drawings or photographs? Event-related brain potentials (ERPs) were recorded from neurotypical adults as they viewed spontaneously produced depictive gestures preceded by congruent and incongruent contexts. Gestures were presented either dynamically in short, soundless video-clips, or statically as freeze frames extracted from gesture videos. In a separate ERP experiment, the same participants viewed related or unrelated pairs of photographs depicting common real-world objects. Both object photos and gesture stimuli elicited less negative ERPs from 400 to 600ms post-stimulus when preceded by matching versus mismatching contexts (dN450). Object photos and static gesture stills also elicited less negative ERPs between 300 and 400ms post-stimulus (dN300). Findings demonstrate commonalities between the conceptual integration processes underlying the interpretation of iconic gestures and other types of image-based representations of the visual world.},
  note = {PubMed query source: Ying Wu}
}

@article{Brzezicka201122237494,
  title = {A role for the right prefrontal and bilateral parietal cortex in four-term transitive reasoning: an fMRI study with abstract linear syllogism tasks.},
  author = {Brzezicka, A and Sedek, G and Marchewka, A and Gola, M and Jednoróg, K and Królicki, L and Wróbel, A},
  journal = {Acta neurobiologiae experimentalis},
  year = {2011},
  doi = {10.55782/ane-2011-1865},
  pmid = {22237494},
  url = {https://pubmed.ncbi.nlm.nih.gov/22237494/},
  abstract = {Previous imaging studies have identified many brain regions activated during reasoning, but there are differences among the findings concerning specific regions engaged in reasoning and the contribution of language areas. Also, little is known about the relation between task complexity and neural activation during reasoning. The present fMRI study investigated brain activity during complex four-term transitive reasoning with abstract material (determinate or partially indeterminate) and compared the resulting images to those obtained during a memorization task. The memory condition required subjects to memorize unrelated elements whereas the reasoning conditions required them to integrate information from premises and to infer relations between elements. After contrasting the two kinds of reasoning conditions with the memory condition we found that right prefrontal and bilateral parietal regions are specifically activated during reasoning. We also demonstrated that different reasoning requirements--the possibility of constructing one (determined reasoning) versus several (undetermined reasoning) models of a situation during task solving--lead to different patterns of brain activity, with higher prefrontal (PFC) activity accompanying undetermined reasoning. We interpret the PFC activity as a reflection of simultaneous maintenance and manipulation of information in reasoning. These findings provide new evidence that specific forms of reasoning (abstract and undetermined) demand recruitment of right PFC and hemispheric coordination and lend new support to the mental model theory of relational reasoning.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Gramann201021267424,
  title = {Visual evoked responses during standing and walking.},
  author = {Gramann, K and Gwin, JT and Bigdely-Shamlo, N and Ferris, DP and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2010},
  doi = {10.3389/fnhum.2010.00202},
  pmid = {21267424},
  url = {https://pubmed.ncbi.nlm.nih.gov/21267424/},
  abstract = {Human cognition has been shaped both by our body structure and by its complex interactions with its environment. Our cognition is thus inextricably linked to our own and others' motor behavior. To model brain activity associated with natural cognition, we propose recording the concurrent brain dynamics and body movements of human subjects performing normal actions. Here we tested the feasibility of such a mobile brain/body (MoBI) imaging approach by recording high-density electroencephalographic (EEG) activity and body movements of subjects standing or walking on a treadmill while performing a visual oddball response task. Independent component analysis of the EEG data revealed visual event-related potentials that during standing, slow walking, and fast walking did not differ across movement conditions, demonstrating the viability of recording brain activity accompanying cognitive processes during whole body movement. Non-invasive and relatively low-cost MoBI studies of normal, motivated actions might improve understanding of interactions between brain and body dynamics leading to more complete biological models of cognition.},
  note = {PubMed query source: Scott Makeig}
}

@article{Whitmer201021152349,
  title = {Utility of independent component analysis for interpretation of intracranial EEG.},
  author = {Whitmer, D and Worrell, G and Stead, M and Lee, IK and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2010},
  doi = {10.3389/fnhum.2010.00184},
  pmid = {21152349},
  url = {https://pubmed.ncbi.nlm.nih.gov/21152349/},
  abstract = {Electrode arrays are sometimes implanted in the brains of patients with intractable epilepsy to better localize seizure foci before epilepsy surgery. Analysis of intracranial EEG (iEEG) recordings is typically performed in the electrode channel domain without explicit separation of the sources that generate the signals. However, intracranial EEG signals, like scalp EEG signals, could be linear mixtures of local activity and volume-conducted activity arising in multiple source areas. Independent component analysis (ICA) has recently been applied to scalp EEG data, and shown to separate the signal mixtures into independently generated brain and non-brain source signals. Here, we applied ICA to unmix source signals from intracranial EEG recordings from four epilepsy patients during a visually cued finger movement task in the presence of background pathological brain activity. This ICA decomposition demonstrated that the iEEG recordings were not maximally independent, but rather are linear mixtures of activity from multiple sources. Many of the independent component (IC) projections to the iEEG recording grid were consistent with sources from single brain regions, including components exhibiting classic movement-related dynamics. Notably, the largest IC projection to each channel accounted for no more than 20-80% of the channel signal variance, implying that in general intracranial recordings cannot be accurately interpreted as recordings of independent brain sources. These results suggest that ICA can be used to identify and monitor major field sources of local and distributed functional networks generating iEEG data. ICA decomposition methods are useful for improving the fidelity of source signals of interest, likely including distinguishing the sources of pathological brain activity.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gwin201020410364,
  title = {Removal of movement artifact from high-density EEG recorded during walking and running.},
  author = {Gwin, JT and Gramann, K and Makeig, S and Ferris, DP},
  journal = {Journal of neurophysiology},
  year = {2010},
  doi = {10.1152/jn.00105.2010},
  pmid = {20410364},
  url = {https://pubmed.ncbi.nlm.nih.gov/20410364/},
  abstract = {Although human cognition often occurs during dynamic motor actions, most studies of human brain dynamics examine subjects in static seated or prone conditions. EEG signals have historically been considered to be too noise prone to allow recording of brain dynamics during human locomotion. Here we applied a channel-based artifact template regression procedure and a subsequent spatial filtering approach to remove gait-related movement artifact from EEG signals recorded during walking and running. We first used stride time warping to remove gait artifact from high-density EEG recorded during a visual oddball discrimination task performed while walking and running. Next, we applied infomax independent component analysis (ICA) to parse the channel-based noise reduced EEG signals into maximally independent components (ICs) and then performed component-based template regression. Applying channel-based or channel-based plus component-based artifact rejection significantly reduced EEG spectral power in the 1.5- to 8.5-Hz frequency range during walking and running. In walking conditions, gait-related artifact was insubstantial: event-related potentials (ERPs), which were nearly identical to visual oddball discrimination events while standing, were visible before and after applying noise reduction. In the running condition, gait-related artifact severely compromised the EEG signals: stable average ERP time-courses of IC processes were only detectable after artifact removal. These findings show that high-density EEG can be used to study brain dynamics during whole body movements and that mechanical artifact from rhythmic gait events may be minimized using a template regression procedure.},
  note = {PubMed query source: Scott Makeig}
}

@article{Cahn201020013298,
  title = {Occipital gamma activation during Vipassana meditation.},
  author = {Cahn, BR and Delorme, A and Polich, J},
  journal = {Cognitive processing},
  year = {2010},
  doi = {10.1007/s10339-009-0352-1},
  pmid = {20013298},
  url = {https://pubmed.ncbi.nlm.nih.gov/20013298/},
  abstract = {Long-term Vipassana meditators sat in meditation vs. a control rest (mind-wandering) state for 21 min in a counterbalanced design with spontaneous EEG recorded. Meditation state dynamics were measured with spectral decomposition of the last 6 min of the eyes-closed silent meditation compared to control state. Meditation was associated with a decrease in frontal delta (1-4 Hz) power, especially pronounced in those participants not reporting drowsiness during meditation. Relative increase in frontal theta (4-8 Hz) power was observed during meditation, as well as significantly increased parieto-occipital gamma (35-45 Hz) power, but no other state effects were found for the theta (4-8 Hz), alpha (8-12 Hz), or beta (12-25 Hz) bands. Alpha power was sensitive to condition order, and more experienced meditators exhibited no tendency toward enhanced alpha during meditation relative to the control task. All participants tended to exhibit decreased alpha in association with reported drowsiness. Cross-experimental session occipital gamma power was the greatest in meditators with a daily practice of 10+ years, and the meditation-related gamma power increase was similarly the strongest in such advanced practitioners. The findings suggest that long-term Vipassana meditation contributes to increased occipital gamma power related to long-term meditational expertise and enhanced sensory awareness.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Rissling201020857348,
  title = {Neurophysiologic markers of abnormal brain activity in schizophrenia.},
  author = {Rissling, AJ and Makeig, S and Braff, DL and Light, GA},
  journal = {Current psychiatry reports},
  year = {2010},
  doi = {10.1007/s11920-010-0149-z},
  pmid = {20857348},
  url = {https://pubmed.ncbi.nlm.nih.gov/20857348/},
  abstract = {Cortical electrophysiologic event-related potentials are multidimensional measures of information processing that are well-suited for efficiently parsing automatic and controlled components of cognition that span the range of deficits evidenced in schizophrenia patients. These information processes are key cognitive measures that are recognized as informative and valid targets for understanding the neurobiology of schizophrenia. These measures may be used in concert with the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) neurocognitive measures in the development of novel treatments for schizophrenia and related neuropsychiatric disorders. The employment of novel event-related potential paradigms designed to carefully characterize the early spectrum of perceptual and cognitive information processing allows investigators to identify the neurophysiologic basis of cognitive dysfunction in schizophrenia and to examine the associated clinical and functional impairments.},
  note = {PubMed query source: Scott Makeig}
}

@article{Acar201020457183,
  title = {Neuroelectromagnetic forward head modeling toolbox.},
  author = {Acar, ZA and Makeig, S},
  journal = {Journal of neuroscience methods},
  year = {2010},
  doi = {10.1016/j.jneumeth.2010.04.031},
  pmid = {20457183},
  url = {https://pubmed.ncbi.nlm.nih.gov/20457183/},
  abstract = {This paper introduces a Neuroelectromagnetic Forward Head Modeling Toolbox (NFT) running under MATLAB (The Mathworks, Inc.) for generating realistic head models from available data (MRI and/or electrode locations) and for computing numerical solutions for the forward problem of electromagnetic source imaging. The NFT includes tools for segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic resonance (MR) images. The Boundary Element Method (BEM) is used for the numerical solution of the forward problem. After extracting segmented tissue volumes, surface BEM meshes can be generated. When a subject MR image is not available, a template head model can be warped to measured electrode locations to obtain an individualized head model. Toolbox functions may be called either from a graphic user interface compatible with EEGLAB (http://sccn.ucsd.edu/eeglab), or from the MATLAB command line. Function help messages and a user tutorial are included. The toolbox is freely available under the GNU Public License for noncommercial use and open source development.},
  note = {PubMed query source: Scott Makeig}
}

@article{Gramann201019925183,
  title = {Human brain dynamics accompanying use of egocentric and allocentric reference frames during navigation.},
  author = {Gramann, K and Onton, J and Riccobon, D and Mueller, HJ and Bardins, S and Makeig, S},
  journal = {Journal of cognitive neuroscience},
  year = {2010},
  doi = {10.1162/jocn.2009.21369},
  pmid = {19925183},
  url = {https://pubmed.ncbi.nlm.nih.gov/19925183/},
  abstract = {Maintaining spatial orientation while travelling requires integrating spatial information encountered from an egocentric viewpoint with accumulated information represented within egocentric and/or allocentric reference frames. Here, we report changes in high-density EEG activity during a virtual tunnel passage task in which subjects respond to a postnavigation homing challenge in distinctly different ways--either compatible with a continued experience of the virtual environment from a solely egocentric perspective or as if also maintaining their original entrance orientation, indicating use of a parallel allocentric reference frame. By spatially filtering the EEG data using independent component analysis, we found that these two equal subject subgroups exhibited differences in EEG power spectral modulation during tunnel passages in only a few cortical areas. During tunnel turns, stronger alpha blocking occurred only in or near right primary visual cortex of subjects whose homing responses were compatible with continued use of an egocentric reference frame. In contrast, approaching and during tunnel turns, subjects who responded in a way compatible with use of an allocentric reference frame exhibited stronger alpha blocking of occipito-temporal, bilateral inferior parietal, and retrosplenial cortical areas, all areas implicated by hemodynamic imaging and neuropsychological observation in construction and maintenance of an allocentric reference frame. We conclude that in these subjects, stronger activation of retrosplenial and related cortical areas during turns support a continuous translation of egocentrically experienced visual flow into an allocentric model of their virtual position and movement.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wu201020375745,
  title = {Gestures modulate speech processing early in utterances.},
  author = {Wu, YC and Coulson, S},
  journal = {Neuroreport},
  year = {2010},
  doi = {10.1097/WNR.0b013e32833904bb},
  pmid = {20375745},
  url = {https://pubmed.ncbi.nlm.nih.gov/20375745/},
  abstract = {Electroencephalogram was recorded as healthy adults viewed short videos of spontaneous discourse in which a speaker used depictive gestures to complement information expressed through speech. Event-related potentials were computed time-locked to content words in the speech stream and to subsequent related and unrelated picture probes. Gestures modulated event-related potentials to content words co-timed with the first gesture in a discourse segment, relative to the same words presented with static freeze frames of the speaker. Effects were observed 200-550 ms after speech onset, a time interval associated with semantic processing. Gestures also increased sensitivity to picture probe relatedness. Effects of gestures on picture probe and spoken word analysis were inversely correlated, suggesting that gestures differentially impact verbal and image-based processes.},
  note = {PubMed query source: Ying Wu}
}

@article{Miller201021119778,
  title = {Dynamic modulation of local population activity by rhythm phase in human occipital cortex during a visual search task.},
  author = {Miller, KJ and Hermes, D and Honey, CJ and Sharma, M and Rao, RP and den Nijs, M and Fetz, EE and Sejnowski, TJ and Hebb, AO and Ojemann, JG and Makeig, S and Leuthardt, EC},
  journal = {Frontiers in human neuroscience},
  year = {2010},
  doi = {10.3389/fnhum.2010.00197},
  pmid = {21119778},
  url = {https://pubmed.ncbi.nlm.nih.gov/21119778/},
  abstract = {Brain rhythms are more than just passive phenomena in visual cortex. For the first time, we show that the physiology underlying brain rhythms actively suppresses and releases cortical areas on a second-to-second basis during visual processing. Furthermore, their influence is specific at the scale of individual gyri. We quantified the interaction between broadband spectral change and brain rhythms on a second-to-second basis in electrocorticographic (ECoG) measurement of brain surface potentials in five human subjects during a visual search task. Comparison of visual search epochs with a blank screen baseline revealed changes in the raw potential, the amplitude of rhythmic activity, and in the decoupled broadband spectral amplitude. We present new methods to characterize the intensity and preferred phase of coupling between broadband power and band-limited rhythms, and to estimate the magnitude of rhythm-to-broadband modulation on a trial-by-trial basis. These tools revealed numerous coupling motifs between the phase of low-frequency (δ, θ, α, β, and γ band) rhythms and the amplitude of broadband spectral change. In the θ and β ranges, the coupling of phase to broadband change is dynamic during visual processing, decreasing in some occipital areas and increasing in others, in a gyrally specific pattern. Finally, we demonstrate that the rhythms interact with one another across frequency ranges, and across cortical sites.},
  note = {PubMed query source: Scott Makeig}
}

@article{Peterson200919628022,
  title = {Probabilistic reversal learning is impaired in Parkinson's disease.},
  author = {Peterson, DA and Elliott, C and Song, DD and Makeig, S and Sejnowski, TJ and Poizner, H},
  journal = {Neuroscience},
  year = {2009},
  doi = {10.1016/j.neuroscience.2009.07.033},
  pmid = {19628022},
  url = {https://pubmed.ncbi.nlm.nih.gov/19628022/},
  abstract = {In many everyday settings, the relationship between our choices and their potentially rewarding outcomes is probabilistic and dynamic. In addition, the difficulty of the choices can vary widely. Although a large body of theoretical and empirical evidence suggests that dopamine mediates rewarded learning, the influence of dopamine in probabilistic and dynamic rewarded learning remains unclear. We adapted a probabilistic rewarded learning task originally used to study firing rates of dopamine cells in primate substantia nigra pars compacta [Morris G, Nevet A, Arkadir D, Vaadia E, Bergman H (2006) Midbrain dopamine neurons encode decisions for future action. Nat Neurosci 9:1057-1063] for use as a reversal learning task with humans. We sought to investigate how the dopamine depletion in Parkinson's disease (PD) affects probabilistic reward learning and adaptation to a reversal in reward contingencies. Over the course of 256 trials subjects learned to choose the more favorable from among pairs of images with small or large differences in reward probabilities. During a subsequent otherwise identical reversal phase, the reward probability contingencies for the stimuli were reversed. Seventeen PD patients of mild to moderate severity were studied off of their dopaminergic medications and compared to 15 age-matched controls. Compared to controls, PD patients had distinct pre- and post-reversal deficiencies depending upon the difficulty of the choices they had to learn. The patients also exhibited compromised adaptability to the reversal. A computational model of the subjects' trial-by-trial choices demonstrated that the adaptability was sensitive to the gain with which patients weighted pre-reversal feedback. Collectively, the results implicate the nigral dopaminergic system in learning to make choices in environments with probabilistic and dynamic reward contingencies.},
  note = {PubMed query source: Scott Makeig}
}

@article{Acar200919964603,
  title = {Patch-basis electrocortical source imaging in epilepsy.},
  author = {Acar, ZA and Worrell, G and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2009},
  doi = {10.1109/IEMBS.2009.5333992},
  pmid = {19964603},
  url = {https://pubmed.ncbi.nlm.nih.gov/19964603/},
  abstract = {In this study, we developed numerical methods for investigating the sources of epileptic activity from intracranial EEG recordings acquired from intracranial subdural electrodes (iEEG) in patients undergoing pre-surgical evaluation at the epilepsy center of the Mayo Clinic (Rochester, MN). The data were analyzed using independent component analysis (ICA), which identifies and isolates maximally independent signal components in multi-channel recordings. A realistic individual head model was constructed for a patient undergoing pre-surgical evaluation. Structural models of gray matter, white matter, CSF, skull, and scalp were extracted from pre-surgical MR and post-surgical CT images. The electromagnetic source localization forward problem was solved using the Boundary Element Method (BEM). Source localization was performed using the Sparse Bayesian Learning (SBL) algorithm. The multiscale patch-basis source space constructed for this purpose includes a large number of dipole elements on the cortical layer oriented perpendicular to the local cortical surface. These source dipoles are combined into overlapping multi-scalepatches. Using this approach, we were able to detect seizure activity on sulcal walls and on gyrus of the cortex.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200919414039,
  title = {Linking brain, mind and behavior.},
  author = {Makeig, S and Gramann, K and Jung, TP and Sejnowski, TJ and Poizner, H},
  journal = {International journal of psychophysiology : official journal of the International Organization of Psychophysiology},
  year = {2009},
  doi = {10.1016/j.ijpsycho.2008.11.008},
  pmid = {19414039},
  url = {https://pubmed.ncbi.nlm.nih.gov/19414039/},
  abstract = {Cortical brain areas and dynamics evolved to organize motor behavior in our three-dimensional environment also support more general human cognitive processes. Yet traditional brain imaging paradigms typically allow and record only minimal participant behavior, then reduce the recorded data to single map features of averaged responses. To more fully investigate the complex links between distributed brain dynamics and motivated natural behavior, we propose the development of wearable mobile brain/body imaging (MoBI) systems that continuously capture the wearer's high-density electrical brain and muscle signals, three-dimensional body movements, audiovisual scene and point of regard, plus new data-driven analysis methods to model their interrelationships. The new imaging modality should allow new insights into how spatially distributed brain dynamics support natural human cognition and agency.},
  note = {PubMed query source: Scott Makeig}
}

@article{Cortez200919190545,
  title = {Infantile spasms and Down syndrome: a new animal model.},
  author = {Cortez, MA and Shen, L and Wu, Y and Aleem, IS and Trepanier, CH and Sadeghnia, HR and Ashraf, A and Kanawaty, A and Liu, CC and Stewart, L and Snead, OC},
  journal = {Pediatric research},
  year = {2009},
  doi = {10.1203/PDR.0b013e31819d9076},
  pmid = {19190545},
  url = {https://pubmed.ncbi.nlm.nih.gov/19190545/},
  abstract = {Infantile spasms is a catastrophic childhood seizure disorder for which few animal models exist. Children with Down syndrome are highly susceptible to infantile spasms. The Ts65Dn mouse is a valid model for Down syndrome; therefore, we tested the hypothesis that the Ts65Dn mouse represents a substrate for an animal model of infantile spasms. The baseline of naïve Ts65Dn mice showed spontaneous spike-and-wave discharges, a pattern that worsened with baclofen and gamma-butyrolactone, which induced acute epileptic extensor spasms (AEES) associated with epileptiform polyspike bursts and an electrodecremental response on the EEG. GABABR-agonist-induced AEES were significantly reduced with vigabatrin, rodent ACTH fragment, valproic acid, ethosuximide, and CGP 35348. Porcine ACTH had no effect. GABABR protein expression was significantly increased in the thalamus and medulla oblongata of Ts65D mice in comparison with wild-type controls. The GABABR agonist-treated Ts65Dn mouse shows the unique clinical, electrographic, and pharmacologic signature of infantile spasms and represents a valid, acute model of this disorder. GABABR-mediated mechanisms may contribute to the increased susceptibility of children with Down syndrome to infantile spasms.},
  note = {PubMed query source: Ying Wu}
}

@article{Milne200918774554,
  title = {Independent component analysis reveals atypical electroencephalographic activity during visual perception in individuals with autism.},
  author = {Milne, E and Scope, A and Pascalis, O and Buckley, D and Makeig, S},
  journal = {Biological psychiatry},
  year = {2009},
  doi = {10.1016/j.biopsych.2008.07.017},
  pmid = {18774554},
  url = {https://pubmed.ncbi.nlm.nih.gov/18774554/},
  abstract = {Individuals with autistic spectrum disorder (ASD) experience atypical visual perception, yet the etiology of this remains unknown. The aim of this study was to investigate the neural correlates of visual perception in individuals with and without ASD by carrying out a detailed analysis of the dynamic brain processes elicited by perception of a simple visual stimulus. We investigated perception in 20 individuals with ASD and 20 control subjects with electroencephalography (EEG). Visual evoked potentials elicited by Gabor patches of varying spatial frequency and stimulus-induced changes in alpha- and gamma-frequency bands of independent components were compared in those with and without ASD. By decomposing the EEG data into independent components, we identified several processes that contributed to the average event related potential recorded at the scalp. Differences between the ASD and control groups were found only in some of these processes. Specifically, in those components that were in or near the striate or extrastriate cortex, stimulus spatial frequency exerted a smaller effect on induced increases in alpha- and gamma-band power, and time to peak alpha-band power was reduced, in the participants with ASD. Induced alpha-band power of components that were in or near the cingulate gyrus was increased in the participants with ASD, and the components that were in or near the parietal cortex did not differ between the two groups. Atypical processing is evident in individuals with ASD during perception of simple visual stimuli. The implications of these data for existing theories of atypical perception in ASD are discussed.},
  note = {PubMed query source: Scott Makeig}
}

@article{Lew200919117275,
  title = {Improved EEG source analysis using low-resolution conductivity estimation in a four-compartment finite element head model.},
  author = {Lew, S and Wolters, CH and Anwander, A and Makeig, S and MacLeod, RS},
  journal = {Human brain mapping},
  year = {2009},
  doi = {10.1002/hbm.20714},
  pmid = {19117275},
  url = {https://pubmed.ncbi.nlm.nih.gov/19117275/},
  abstract = {Bioelectric source analysis in the human brain from scalp electroencephalography (EEG) signals is sensitive to geometry and conductivity properties of the different head tissues. We propose a low-resolution conductivity estimation (LRCE) method using simulated annealing optimization on high-resolution finite element models that individually optimizes a realistically shaped four-layer volume conductor with regard to the brain and skull compartment conductivities. As input data, the method needs T1- and PD-weighted magnetic resonance images for an improved modeling of the skull and the cerebrospinal fluid compartment and evoked potential data with high signal-to-noise ratio (SNR). Our simulation studies showed that for EEG data with realistic SNR, the LRCE method was able to simultaneously reconstruct both the brain and the skull conductivity together with the underlying dipole source and provided an improved source analysis result. We have also demonstrated the feasibility and applicability of the new method to simultaneously estimate brain and skull conductivity and a somatosensory source from measured tactile somatosensory-evoked potentials of a human subject. Our results show the viability of an approach that computes its own conductivity values and thus reduces the dependence on assigning values from the literature and likely produces a more robust estimate of current sources. Using the LRCE method, the individually optimized four-compartment volume conductor model can, in a second step, be used for the analysis of clinical or cognitive data acquired from the same subject.},
  note = {PubMed query source: Scott Makeig}
}

@article{Groppe200919162199,
  title = {Identifying reliable independent components via split-half comparisons.},
  author = {Groppe, DM and Makeig, S and Kutas, M},
  journal = {NeuroImage},
  year = {2009},
  doi = {10.1016/j.neuroimage.2008.12.038},
  pmid = {19162199},
  url = {https://pubmed.ncbi.nlm.nih.gov/19162199/},
  abstract = {Independent component analysis (ICA) is a family of unsupervised learning algorithms that have proven useful for the analysis of the electroencephalogram (EEG) and magnetoencephalogram (MEG). ICA decomposes an EEG/MEG data set into a basis of maximally temporally independent components (ICs) that are learned from the data. As with any statistic, a concern with using ICA is the degree to which the estimated ICs are reliable. An IC may not be reliable if ICA was trained on insufficient data, if ICA training was stopped prematurely or at a local minimum (for some algorithms), or if multiple global minima were present. Consequently, evidence of ICA reliability is critical for the credibility of ICA results. In this paper, we present a new algorithm for assessing the reliability of ICs based on applying ICA separately to split-halves of a data set. This algorithm improves upon existing methods in that it considers both IC scalp topographies and activations, uses a probabilistically interpretable threshold for accepting ICs as reliable, and requires applying ICA only three times per data set. As evidence of the method's validity, we show that the method can perform comparably to more time intensive bootstrap resampling and depends in a reasonable manner on the amount of training data. Finally, using the method we illustrate the importance of checking the reliability of ICs by demonstrating that IC reliability is dramatically increased by removing the mean EEG at each channel for each epoch of data rather than the mean EEG in a prestimulus baseline.},
  note = {PubMed query source: Scott Makeig}
}

@article{Onton200920076775,
  title = {High-frequency Broadband Modulations of Electroencephalographic Spectra.},
  author = {Onton, J and Makeig, S},
  journal = {Frontiers in human neuroscience},
  year = {2009},
  doi = {10.3389/neuro.09.061.2009},
  pmid = {20076775},
  url = {https://pubmed.ncbi.nlm.nih.gov/20076775/},
  abstract = {High-frequency cortical potentials in electroencephalographic (EEG) scalp recordings have low amplitudes and may be confounded with scalp muscle activities. EEG data from an eyes-closed emotion imagination task were linearly decomposed using independent component analysis (ICA) into maximally independent component (IC) processes. Joint decomposition of IC log spectrograms into source- and frequency-independent modulator (IM) processes revealed three distinct classes of IMs that separately modulated broadband high-frequency ( approximately 15-200 Hz) power of brain, scalp muscle, and likely ocular motor IC processes. Multi-dimensional scaling revealed significant but spatially complex relationships between mean broadband brain IM effects and the valence of the imagined emotions. Thus, contrary to prevalent assumption, unitary modes of spectral modulation of frequencies encompassing the beta, gamma, and high gamma frequency ranges can be isolated from scalp-recorded EEG data and may be differentially associated with brain sources and cognitive activities.},
  note = {PubMed query source: Scott Makeig}
}

@article{Garvin200919818111,
  title = {DNA preparation from sexual assault cases by selective degradation of contaminating DNA from the victim.},
  author = {Garvin, AM and Bottinelli, M and Gola, M and Conti, A and Soldati, G},
  journal = {Journal of forensic sciences},
  year = {2009},
  doi = {10.1111/j.1556-4029.2009.01180.x},
  pmid = {19818111},
  url = {https://pubmed.ncbi.nlm.nih.gov/19818111/},
  abstract = {The standard method to purify sperm DNA from vaginal swabs taken from rape victims is to selectively digest the victim's epithelial cells to solubilize the victim's DNA, and then separate the soluble DNA from the intact sperm by centrifugation. A different approach to removing the soluble victim's DNA is to selectively degrade it using a nuclease, DNase I. DNase I reduces the amount of soluble DNA by over 1000-fold, while having virtually no effect on the sperm DNA remaining in the sperm head and inaccessible to the enzyme. Nuclease inactivation and sperm lysis then yield a soluble, pure male DNA fraction. An aliquot of soluble DNA is removed prior to nuclease addition to provide the victim's fraction. Vaginal swabs taken at defined time points following consensual sex and taken from rape victims were processed using the nuclease method or the standard method and the nuclease method gave superior short tandem repeat profiles.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Tomaszewski200918639879,
  title = {Association between lipid profile and circulating concentrations of estrogens in young men.},
  author = {Tomaszewski, M and Charchar, FJ and Maric, C and Kuzniewicz, R and Gola, M and Grzeszczak, W and Samani, NJ and Zukowska-Szczechowska, E},
  journal = {Atherosclerosis},
  year = {2009},
  doi = {10.1016/j.atherosclerosis.2008.06.002},
  pmid = {18639879},
  url = {https://pubmed.ncbi.nlm.nih.gov/18639879/},
  abstract = {Men show higher rates of cardiovascular morbidity and mortality than pre-menopausal women and this sexual dimorphism may be related to sex-specific effects of sex steroids on cardiovascular risk factors. Unlike androgens, estrogens were not extensively investigated in relation to cardiovascular phenotypes in men. We examined associations of estradiol and estrone and their precursors (total testosterone and androstenedione) with traditional cardiovascular risk factors (lipids, blood pressure, body mass) in 933 young (median age: 19 years), apparently healthy Polish men. Total estradiol was associated with total cholesterol (p=0.006) and high-density lipoprotein cholesterol (HDL-C) (p<0.001) and estrone showed the strongest associations with both total cholesterol (p<0.001) and low-density lipoprotein cholesterol (LDL-C) (p<0.001) in the unadjusted ANOVA analysis. In the multivariable adjusted models in which other independent variables were held as constant one standard deviation increase in estradiol level was associated with 6%-standard deviation increase in total cholesterol (standardized beta=0.06, p=0.038) and 6%-standard deviation decrease in HDL-cholesterol (standardized beta=-0.06, p=0.036). An increase in estrone levels by one standard deviation was associated with respective 12%- and 13%-standard deviation increases in total cholesterol (standardized beta=0.12, p<0.001) and LDL-cholesterol levels (standardized beta=0.12, p<0.001) after controlling for other predictors of lipids. Estrone correlated linearly with androstenedione (r=0.28, p<0.001) but there was no correlation between estradiol and testosterone. Estrogens retained their independent associations with lipids after adjustment for their biochemical precursors in the multivariable analysis. Increased levels of estrogens are associated with unfavourable lipid profile in men and this association is present early in life, before apparent manifestations of cardiovascular disease.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Huang200818083601,
  title = {Tonic and phasic electroencephalographic dynamics during continuous compensatory tracking.},
  author = {Huang, RS and Jung, TP and Delorme, A and Makeig, S},
  journal = {NeuroImage},
  year = {2008},
  doi = {10.1016/j.neuroimage.2007.10.036},
  pmid = {18083601},
  url = {https://pubmed.ncbi.nlm.nih.gov/18083601/},
  abstract = {Tonic and phasic dynamics of electroencephalographic (EEG) activities during a continuous compensatory tracking task (CTT) were analyzed using time-frequency analysis of EEG sources identified by independent component analysis (ICA). In 1-hour sessions, 70-channel EEG data were recorded while participants attempted to use frequent compensatory trackball movements to maintain a drifting disc close to a bulls-eye at screen center. Disc trajectories were converted into two moving-average performance measures, root mean square distance of the disc from screen center in 4-s ('local') and in 20-s ('global') moving time windows. Maximally independent EEG processes and their equivalent dipole source locations were obtained using the EEGLAB toolbox (http://sccn.ucsd.edu/eeglab). Across subjects and sessions, independent EEG processes in occipital, somatomotor, and supplementary motor cortices exhibited tonic power increases during periods of high tracking error, plus additional phasic power increases in several frequency bands before and after trackball movements following disc 'perigees' (moments at which the disc began to drift away from the bulls-eye). These phasic activity increases, which were larger during high-error periods, reveal an intimate relation between EEG dynamics and top-down recognition of responding to threatening events. Thus during a continuous tracking task without impulsive stimulus onsets, sub-second scale EEG dynamics related to visuomotor task could be dissociated from slower spectral modulations linked to changes in performance and arousal. We tentatively interpret the observed EEG signal increases as indexing tonic and phasic modulations of the levels of task attention and engagement required to maintain visuomotor performance during sustained performance.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{AkalinAcar200819163587,
  title = {Neuroelectromagnetic forward modeling toolbox.},
  author = {Akalin Acar, Z and Makeig, S},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2008},
  doi = {10.1109/IEMBS.2008.4650084},
  pmid = {19163587},
  url = {https://pubmed.ncbi.nlm.nih.gov/19163587/},
  abstract = {This paper introduces a Neuroelectromagnetic Forward Modeling Toolbox running under MATLAB (The Mathworks, Inc.) for generating realistic head models from available data (MRI and/or electrode locations) and for solving the forward problem of electro-magnetic source imaging numerically. The toolbox includes tools for segmenting scalp, skull, cerebrospinal fluid (CSF) and brain tissues from T1-weighted magnetic resonance (MR) images. After extracting the segmented tissue volumes, mesh generation can be performed using deformable models. When MR images are not available, it is possible to warp a template head model to measured electrode locations to obtain a better-fitting realistic model. The Boundary Element Method (BEM) is used for the numerical solution of the forward problem. Toolbox functions can be called from either a graphic user interface or from the command line. Function help messages and a tutorial are included. The toolbox is freely available under the GNU Public License for noncommercial use and open source development.},
  note = {PubMed query source: Scott Makeig}
}

@article{Acar200819163530,
  title = {Head modeling and cortical source localization in epilepsy.},
  author = {Acar, ZA and Makeig, S and Worrell, G},
  journal = {Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference},
  year = {2008},
  doi = {10.1109/IEMBS.2008.4650027},
  pmid = {19163530},
  url = {https://pubmed.ncbi.nlm.nih.gov/19163530/},
  abstract = {In this study, we developed numerical methods for investigating the dynamics of epilepsy from multi-scale EEG recordings acquired simultaneously from the scalp (sEEG) and intracranial subdural and/or depth electrodes (iEEG) in patients undergoing pre-surgical evaluation at the epilepsy center of the Mayo Clinic (Rochester, MN). The data are analyzed using independent component analysis (ICA), which identifies and isolates independent signal components from multi-channel recordings. A realistic individual head model was constructed for a patient undergoing pre-surgical evaluation. The forward problem of electro-magnetic source localization was solved using the Boundary Element Method (BEM). Using this approach, we investigated the relationships between noninvasive and invasive source localization of human electrical brain data sources. A difference of about 1 cm was observed between sources estimated from sEEG and iEEG measurements.},
  note = {PubMed query source: Scott Makeig}
}

@article{BigdelyShamlo200818990647,
  title = {Brain activity-based image classification from rapid serial visual presentation.},
  author = {Bigdely-Shamlo, N and Vankov, A and Ramirez, RR and Makeig, S},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2008},
  doi = {10.1109/TNSRE.2008.2003381},
  pmid = {18990647},
  url = {https://pubmed.ncbi.nlm.nih.gov/18990647/},
  abstract = {We report the design and performance of a brain-computer interface (BCI) system for real-time single-trial binary classification of viewed images based on participant-specific dynamic brain response signatures in high-density (128-channel) electroencephalographic (EEG) data acquired during a rapid serial visual presentation (RSVP) task. Image clips were selected from a broad area image and presented in rapid succession (12/s) in 4.1-s bursts. Participants indicated by subsequent button press whether or not each burst of images included a target airplane feature. Image clip creation and search path selection were designed to maximize user comfort and maintain user awareness of spatial context. Independent component analysis (ICA) was used to extract a set of independent source time-courses and their minimally-redundant low-dimensional informative features in the time and time-frequency amplitude domains from 128-channel EEG data recorded during clip burst presentations in a training session. The naive Bayes fusion of two Fisher discriminant classifiers, computed from the 100 most discriminative time and time-frequency features, respectively, was used to estimate the likelihood that each clip contained a target feature. This estimator was applied online in a subsequent test session. Across eight training/test session pairs from seven participants, median area under the receiver operator characteristic curve, by tenfold cross validation, was 0.97 for within-session and 0.87 for between-session estimates, and was nearly as high (0.83) for targets presented in bursts that participants mistakenly reported to include no target features.},
  note = {PubMed query source: Scott Makeig}
}

@article{Hsu200717437108,
  title = {Regional CBF changes in Parkinson's disease: a correlation with motor dysfunction.},
  author = {Hsu, JL and Jung, TP and Hsu, CY and Hsu, WC and Chen, YK and Duann, JR and Wang, HC and Makeig, S},
  journal = {European journal of nuclear medicine and molecular imaging},
  year = {2007},
  doi = {10.1007/s00259-006-0360-7},
  pmid = {17437108},
  url = {https://pubmed.ncbi.nlm.nih.gov/17437108/},
  abstract = {The purpose of this study was to further localize cerebral perfusion abnormalities, and to better correlate these abnormalities with the clinical severity of Parkinson's disease (PD). A single-photon emission computed tomography (SPECT) study was performed on 27 patients with PD and 24 age-matched controls. SPECT images were spatially normalized, concatenated, and then decomposed using Infomax independent component analysis (ICA). The resulting image components were separated by logistic regression into two subspaces: "disease-related" components whose subject weights differed between groups, and "disease-unrelated" components. The resultant regional cerebral blood flow (rCBF) subspace images were normalized to global CBF for each subject, and then processed using statistical parametric mapping to compare rCBF values between PD and control subjects. In the disease-related image subspace, patients with PD exhibited significantly higher adjusted rCBF in the putamen, globus pallidum, thalamus, brainstem, and the anterior lobe of the cerebellum, and significant hypoperfusion in the parieto-temporo-occipital cortex, the dorsolateral prefrontal cortex, the insula, and the cingulate gyrus. The motor Unified Parkinson's Disease Rating Scale scores correlated negatively with rCBF in the insula and cingulate gyrus. In the disease-unrelated image subspace, no brain voxels exhibited a significant group difference. ICA-based separation of normalized images into disease-related and disease-unrelated subspaces revealed many disease-related group blood flow differences. The regions revealed by ICA are consistent with the current model of PD. These rCBF changes in PD have not been fully demonstrated in any single functional imaging study previously.},
  note = {PubMed query source: Scott Makeig}
}

@article{Dyrholm200717348768,
  title = {Model selection for convolutive ICA with an application to spatiotemporal analysis of EEG.},
  author = {Dyrholm, M and Makeig, S and Hansen, LK},
  journal = {Neural computation},
  year = {2007},
  doi = {10.1162/neco.2007.19.4.934},
  pmid = {17348768},
  url = {https://pubmed.ncbi.nlm.nih.gov/17348768/},
  abstract = {We present a new algorithm for maximum likelihood convolutive independent component analysis (ICA) in which components are unmixed using stable autoregressive filters determined implicitly by estimating a convolutive model of the mixing process. By introducing a convolutive mixing model for the components, we show how the order of the filters in the model can be correctly detected using Bayesian model selection. We demonstrate a framework for deconvolving a subspace of independent components in electroencephalography (EEG). Initial results suggest that in some cases, convolutive mixing may be a more realistic model for EEG signals than the instantaneous ICA model.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme200717978035,
  title = {Medial prefrontal theta bursts precede rapid motor responses during visual selective attention.},
  author = {Delorme, A and Westerfield, M and Makeig, S},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2007},
  doi = {10.1523/JNEUROSCI.3477-07.2007},
  pmid = {17978035},
  url = {https://pubmed.ncbi.nlm.nih.gov/17978035/},
  abstract = {After visual target stimuli presented infrequently at a covertly attended location, quicker speeded button presses immediately followed a larger positive (P3f) ramp in averaged electroencephalographic (EEG) recordings from the forehead. We show this peak in the mean response time locked to the button press to be principally composed of triphasic, primarily low-theta band (4.5 Hz) complexes preceding but only partially phase-locked to the button press, with larger complexes preceding quicker motor responses. For 10 of 15 subjects, independent component analysis of the unaveraged 31-channel data identified a temporally independent medial frontal EEG process contributing to these phenomena. Low-resolution tomographic modeling localized related components of two 253-channel data sets to medial frontal polar cortex (BA32/10). The far-frontal low-theta complexes and concomitant mean P3f positivity may index cortical activity induced by paralimbic processes involved in disinhibiting impulsive motor responses to rewarding or goal-fulfilling stimuli or events.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Wu200717546731,
  title = {Iconic gestures prime related concepts: an ERP study.},
  author = {Wu, YC and Coulson, S},
  journal = {Psychonomic bulletin & review},
  year = {2007},
  doi = {10.3758/bf03194028},
  pmid = {17546731},
  url = {https://pubmed.ncbi.nlm.nih.gov/17546731/},
  abstract = {To assess priming by iconic gestures, we recorded EEG (at 29 scalp sites) in two experiments while adults watched short, soundless videos of spontaneously produced, cospeech iconic gestures followed by related or unrelated probe words. In Experiment 1, participants classified the relatedness between gestures and words. In Experiment 2, they attended to stimuli, and performed an incidental recognition memory test on words presented during the EEG recording session. Event-related potentials (ERPs) time-locked to the onset of probe words were measured, along with response latencies and word recognition rates. Although word relatedness did not affect reaction times or recognition rates, contextually related probe words elicited less-negative ERPs than did unrelated ones between 300 and 500 msec after stimulus onset (N400) in both experiments. These findings demonstrate sensitivity to semantic relations between iconic gestures and words in brain activity engendered during word comprehension.},
  note = {PubMed query source: Ying Wu}
}

@article{Wu200717222897,
  title = {How iconic gestures enhance communication: an ERP study.},
  author = {Wu, YC and Coulson, S},
  journal = {Brain and language},
  year = {2007},
  doi = {10.1016/j.bandl.2006.12.003},
  pmid = {17222897},
  url = {https://pubmed.ncbi.nlm.nih.gov/17222897/},
  abstract = {EEG was recorded as adults watched short segments of spontaneous discourse in which the speaker's gestures and utterances contained complementary information. Videos were followed by one of four types of picture probes: cross-modal related probes were congruent with both speech and gestures; speech-only related probes were congruent with information in the speech, but not the gesture; and two sorts of unrelated probes were created by pairing each related probe with a different discourse prime. Event-related potentials (ERPs) elicited by picture probes were measured within the time windows of the N300 (250-350 ms post-stimulus) and N400 (350-550 ms post-stimulus). Cross-modal related probes elicited smaller N300 and N400 than speech-only related ones, indicating that pictures were easier to interpret when they corresponded with gestures. N300 and N400 effects were not due to differences in the visual complexity of each probe type, since the same cross-modal and speech-only picture probes elicited N300 and N400 with similar amplitudes when they appeared as unrelated items. These findings extend previous research on gesture comprehension by revealing how iconic co-speech gestures modulate conceptualization, enabling listeners to better represent visuo-spatial aspects of the speaker's meaning.},
  note = {PubMed query source: Ying Wu}
}

@article{Delorme200717188898,
  title = {Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis.},
  author = {Delorme, A and Sejnowski, T and Makeig, S},
  journal = {NeuroImage},
  year = {2007},
  doi = {10.1016/j.neuroimage.2006.11.004},
  pmid = {17188898},
  url = {https://pubmed.ncbi.nlm.nih.gov/17188898/},
  abstract = {Detecting artifacts produced in EEG data by muscle activity, eye blinks and electrical noise is a common and important problem in EEG research. It is now widely accepted that independent component analysis (ICA) may be a useful tool for isolating artifacts and/or cortical processes from electroencephalographic (EEG) data. We present results of simulations demonstrating that ICA decomposition, here tested using three popular ICA algorithms, Infomax, SOBI, and FastICA, can allow more sensitive automated detection of small non-brain artifacts than applying the same detection methods directly to the scalp channel data. We tested the upper bound performance of five methods for detecting various types of artifacts by separately optimizing and then applying them to artifact-free EEG data into which we had added simulated artifacts of several types, ranging in size from thirty times smaller (-50 dB) to the size of the EEG data themselves (0 dB). Of the methods tested, those involving spectral thresholding were most sensitive. Except for muscle artifact detection where we found no gain of using ICA, all methods proved more sensitive when applied to the ICA-decomposed data than applied to the raw scalp data: the mean performance for ICA was higher and situated at about two standard deviations away from the performance distribution obtained on raw data. We note that ICA decomposition also allows simple subtraction of artifacts accounted for by single independent components, and/or separate and direct examination of the decomposed non-artifact processes themselves.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Miller200717343918,
  title = {Cortical electrode localization from X-rays and simple mapping for electrocorticographic research: The "Location on Cortex" (LOC) package for MATLAB.},
  author = {Miller, KJ and Makeig, S and Hebb, AO and Rao, RP and denNijs, M and Ojemann, JG},
  journal = {Journal of neuroscience methods},
  year = {2007},
  doi = {10.1016/j.jneumeth.2007.01.019},
  pmid = {17343918},
  url = {https://pubmed.ncbi.nlm.nih.gov/17343918/},
  abstract = {Medically refractory epilepsy accounts for more than 30% of the epilepsy population. Scalp EEG electrodes have limited ability to localize seizure onset from deep structures and implantation of subdural electrodes with long term monitoring provides additional information. Apart from clinical application, this patient population provides a unique opportunity for acquiring electrocorticography data in research paradigms. We present a method for rapid localization of electrodes using lateral and anterior-posterior X-rays. Skull landmarks and proportions are used for co-registration with the standardized Talairach coordinate system. This MATLAB-based "Location on Cortex" (LOC) package facilitates rapid visualization of clinical and experimental data in a user-friendly manner.},
  note = {PubMed query source: Scott Makeig}
}

@article{Anemller200620689619,
  title = {Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis.},
  author = {Anemüller, J and Duann, JR and Sejnowski, TJ and Makeig, S},
  journal = {Neurocomputing},
  year = {2006},
  doi = {10.1016/j.neucom.2005.12.029},
  pmid = {20689619},
  url = {https://pubmed.ncbi.nlm.nih.gov/20689619/},
  abstract = {Independent component analysis (ICA) of functional magnetic resonance imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation, which leads to the instantaneous mixing model. To allow modeling patterns of spatio-temporal dynamics, in particular, the flow of oxygenated blood, we have developed a convolutive ICA approach: spatial complex ICA applied to frequency-domain fMRI data. In several frequency-bands, we identify components pertaining to activity in primary visual cortex (V1) and blood supply vessels. One such component, obtained in the 0.10 Hz band, is analyzed in detail and found to likely reflect flow of oxygenated blood in V1.},
  note = {PubMed query source: Scott Makeig}
}

@article{Tsai200616730194,
  title = {Mapping single-trial EEG records on the cortical surface through a spatiotemporal modality.},
  author = {Tsai, AC and Liou, M and Jung, TP and Onton, JA and Cheng, PE and Huang, CC and Duann, JR and Makeig, S},
  journal = {NeuroImage},
  year = {2006},
  doi = {10.1016/j.neuroimage.2006.02.044},
  pmid = {16730194},
  url = {https://pubmed.ncbi.nlm.nih.gov/16730194/},
  abstract = {Event-related potentials (ERPs) induced by visual perception and cognitive tasks have been extensively studied in neuropsychological experiments. ERP activities time-locked to stimulus presentation and task performance are often observed separately at individual scalp channels based on averaged time series across epochs and experimental subjects. An analysis using averaged EEG dynamics could discount information regarding interdependency between ongoing EEG and salient ERP features. Advanced tools such as independent component analysis (ICA) have been developed for decomposing collections of single-trial EEG records into separate features. Those features (or independent components) can then be mapped onto the cortical surface using source localization algorithms to visualize brain activation maps and to study between-subject consistency. In this study, we propose a statistical framework for estimating the time course of spatiotemporally independent EEG components simultaneously with their cortical distributions. Within this framework, we implemented Bayesian spatiotemporal analysis for imaging the sources of EEG features on the cortical surface. The framework allows researchers to include prior knowledge regarding spatial locations as well as spatiotemporal independence of different EEG sources. The use of the Electromagnetic Spatiotemporal ICA (EMSICA) method is illustrated by mapping event-related EEG dynamics induced by events in a visual two-back continuous performance task. The proposed method successfully identified several interesting components with plausible corresponding cortical activation topographies, including processes contributing to the late positive complex (LPC) located in central parietal, frontal midline, and anterior cingulate cortex, to atypical mu rhythms associated with the precentral gyrus, and to the central posterior alpha activity in the precuneus.},
  note = {PubMed query source: Scott Makeig}
}

@article{Onton200617071226,
  title = {Information-based modeling of event-related brain dynamics.},
  author = {Onton, J and Makeig, S},
  journal = {Progress in brain research},
  year = {2006},
  doi = {10.1016/S0079-6123(06)59007-7},
  pmid = {17071226},
  url = {https://pubmed.ncbi.nlm.nih.gov/17071226/},
  abstract = {We discuss the theory and practice of applying independent component analysis (ICA) to electroencephalographic (EEG) data. ICA blindly decomposes multi-channel EEG data into maximally independent component processes (ICs) that typically express either particularly brain generated EEG activities or some type of non-brain artifacts (line or other environmental noise, eye blinks and other eye movements, or scalp or heart muscle activity). Each brain and non-brain IC is identified with an activity time course (its 'activation') and a set of relative strengths of its projections (by volume conduction) to the recording electrodes (its 'scalp map'). Many non-articraft IC scalp maps strongly resemble the projection of a single dipole, allowing the location and orientation of the best-fitting equivalent dipole (or other source model) to be easily determined. In favorable circumstances, ICA decomposition of high-density scalp EEG data appears to allow concurrent monitoring, with high time resolution, of separate EEG activities in twenty or more separate cortical EEG source areas. We illustrate the differences between ICA and traditional approaches to EEG analysis by comparing time courses and mean event related spectral perturbations (ERSPs) of scalp channel and IC data. Comparing IC activities across subjects necessitates clustering of similar Ics based on common dynamic and/or spatial features. We discuss and illustrate such a component clustering strategy. In sum, continued application of ICA methods in EEG research should continue to yield new insights into the nature and role of the complex macroscopic cortical dynamics captured by scalp electrode recordings.},
  note = {PubMed query source: Scott Makeig}
}

@article{Onton200616904745,
  title = {Imaging human EEG dynamics using independent component analysis.},
  author = {Onton, J and Westerfield, M and Townsend, J and Makeig, S},
  journal = {Neuroscience and biobehavioral reviews},
  year = {2006},
  doi = {10.1016/j.neubiorev.2006.06.007},
  pmid = {16904745},
  url = {https://pubmed.ncbi.nlm.nih.gov/16904745/},
  abstract = {This review discusses the theory and practical application of independent component analysis (ICA) to multi-channel EEG data. We use examples from an audiovisual attention-shifting task performed by young and old subjects to illustrate the power of ICA to resolve subtle differences between evoked responses in the two age groups. Preliminary analysis of these data using ICA suggests a loss of task specificity in independent component (IC) processes in frontal and somatomotor cortex during post-response periods in older as compared to younger subjects, trends not detected during examination of scalp-channel event-related potential (ERP) averages. We discuss possible approaches to component clustering across subjects and new ways to visualize mean and trial-by-trial variations in the data, including ERP-image plots of dynamics within and across trials as well as plots of event-related spectral perturbations in component power, phase locking, and coherence. We believe that widespread application of these and related analysis methods should bring EEG once again to the forefront of brain imaging, merging its high time and frequency resolution with enhanced cm-scale spatial resolution of its cortical sources.},
  note = {PubMed query source: Scott Makeig}
}

@article{Debener200515722203,
  title = {What is novel in the novelty oddball paradigm? Functional significance of the novelty P3 event-related potential as revealed by independent component analysis.},
  author = {Debener, S and Makeig, S and Delorme, A and Engel, AK},
  journal = {Brain research. Cognitive brain research},
  year = {2005},
  doi = {10.1016/j.cogbrainres.2004.09.006},
  pmid = {15722203},
  url = {https://pubmed.ncbi.nlm.nih.gov/15722203/},
  abstract = {To better understand whether voluntary attention affects how the brain processes novel events, variants of the auditory novelty oddball paradigm were presented to two different groups of human volunteers. One group of subjects (n=16) silently counted rarely presented 'infrequent' tones (p=0.10), interspersed with 'novel' task-irrelevant unique environmental sounds (p=0.10) and frequently presented 'standard' tones (p=0.80). A second group of subjects (n=17) silently counted the 'novel' environmental sounds, the 'infrequent' tones now serving as the task-irrelevant deviant events. Analysis of event-related potentials (ERPs) recorded from 63 scalp channels suggested a spatiotemporal overlap of fronto-central novelty P3 and centro-parietal P3 (P3b) ERP features in both groups. Application of independent component analysis (ICA) to concatenated single trials revealed two independent component clusters that accounted for portions of the novelty P3 and P3b response features, respectively. The P3b-related ICA cluster contributed to the novelty P3 amplitude response to novel environmental sounds. In contrast to the scalp ERPs, the amplitude of the novelty P3 related cluster was not affected by voluntary attention, that is, by the target/nontarget distinction. This result demonstrates the usefulness of ICA for disentangling spatiotemporally overlapping ERP processes and provides evidence that task irrelevance is not a necessary feature of novelty processing.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Kimball200516343026,
  title = {The psychosocial burden of psoriasis.},
  author = {Kimball, AB and Jacobson, C and Weiss, S and Vreeland, MG and Wu, Y},
  journal = {American journal of clinical dermatology},
  year = {2005},
  doi = {10.2165/00128071-200506060-00005},
  pmid = {16343026},
  url = {https://pubmed.ncbi.nlm.nih.gov/16343026/},
  abstract = {Skin diseases such as psoriasis can profoundly influence a patient's self-image, self-esteem, and sense of well-being. Psoriasis is a multifactorial inflammatory condition with a disease burden that extends beyond the physical symptoms experienced by patients. Psoriasis affects all aspects of quality of life, including physical, psychologic, social, sexual, and occupational elements. The goal of this article was to review the published literature on the impact of psoriasis on quality of life. Relevant studies were identified through a comprehensive search of MEDLINE, EMBASE, and the Derwent Drug File databases of English-language articles published between 1993 and 2005 using the terms psoriasis in combination with quality of life, cost, cost-benefit analysis, economic, employment, days lost, healthcare, hospitalization, managed care, outcomes research, occupation, payers, and psychosocial. The reference lists of identified articles were checked for additional studies that might have been missed in the original searches. Data suggest that social stigmatization, high stress levels, physical limitations, depression, employment problems and other psychosocial co-morbidities experienced by patients with psoriasis are not always proportional to, or predicted by, other measurements of disease severity such as body surface area involvement or plaque severity. It is essential to include measures of psychosocial morbidity when assessing psoriasis severity and treatment efficacy because of the substantial role that psychosocial burden plays in patient perception of disease severity, quality of life, and disease course.},
  note = {PubMed query source: Ying Wu}
}

@article{Coulson200515814008,
  title = {Right hemisphere activation of joke-related information: an event-related brain potential study.},
  author = {Coulson, S and Wu, YC},
  journal = {Journal of cognitive neuroscience},
  year = {2005},
  doi = {10.1162/0898929053279568},
  pmid = {15814008},
  url = {https://pubmed.ncbi.nlm.nih.gov/15814008/},
  abstract = {Two studies tested the hypothesis that the right hemisphere engages in relatively coarse semantic coding that aids high-level language tasks such as joke comprehension. Scalprecorded event-related brain potentials (ERPs) were collected as healthy adults read probe words (CRAZY) preceded either by jokes or nonfunny controls ("Everyone had so much fun jumping into the swimming pool, we decided to put in a little water/platform"). Probes were related to the meaning of the jokes, but not the controls. In Experiment 1a, with central presentation, probes following jokes (related) elicited less negative ERPs 300-700 msec postonset (N400) than did probes following nonfunny controls (unrelated). This finding suggests related probes were primed by the jokes. In addition, unrelated probes elicited a larger anterior positivity 700-900 msec than did related, as irrelevant stimuli impacted control processes invoked by task demands. In Experiment 1b, probes (CRAZY) were preceded only by sentence-final words from jokes (water) or controls (platform). No ERP effects were observed in Experiment 1b, suggesting the N400 priming effect and the anterior positivity observed in Experiment 1a ref lect semantic activations at the discourse level. To assess hemispheric differences in semantic activations, in Experiment 2, ERPs were recorded as participants read probe words presented in their left and right visual fields (LVF and RVF, respectively). Probes elicited a smaller N400 component when preceded by jokes than controls. This N400 priming effect was larger with presentation to the LVF, suggesting joke-relevant information was more active in the right hemisphere. The anterior positivity was observed with RVF but not LVF presentation, suggesting an important role for the left hemisphere in controlled retrieval in language comprehension.},
  note = {PubMed query source: Ying Wu}
}

@article{Duann200517281453,
  title = {Repeated decompositions reveal the stability of infomax decomposition of fMRI data.},
  author = {Duann, JR and Jung, TP and Makeig, S and Sejnowski, T},
  journal = {Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference},
  year = {2005},
  doi = {10.1109/IEMBS.2005.1615683},
  pmid = {17281453},
  url = {https://pubmed.ncbi.nlm.nih.gov/17281453/},
  abstract = {In this study, we decomposed 12 fMRI data sets from six subjects each 101 times using the infomax algorithm. The first decomposition was taken as a reference decomposition; the others were used to form a component matrix of 100 by 100 components. Equivalence relations between components in this matrix, defined as maximum spatial correlations to the components of the reference decomposition, were found by the Hungarian sorting method and used to form 100 equivalence classes for each data set. We then tested the reproducibility of the matched components in the equivalence classes using uncertainty measures based on component distributions, time courses, and ROC curves. Infomax ICA rarely failed to derive nearly the same components in different decompositions. Very few components per data set were poorly reproduced, even using vector angle uncertainty measures stricter than correlation and detection theory measures.},
  note = {PubMed query source: Scott Makeig}
}

@article{Wu200516364061,
  title = {Meaningful gestures: electrophysiological indices of iconic gesture comprehension.},
  author = {Wu, YC and Coulson, S},
  journal = {Psychophysiology},
  year = {2005},
  doi = {10.1111/j.1469-8986.2005.00356.x},
  pmid = {16364061},
  url = {https://pubmed.ncbi.nlm.nih.gov/16364061/},
  abstract = {To assess semantic processing of iconic gestures, EEG (29 scalp sites) was recorded as adults watched cartoon segments paired with soundless videos of congruous and incongruous gestures followed by probe words. Event-related potentials time-locked to the onset of gestures and probe words were measured in two experiments. In Experiment 1, participants judged the congruency between gestures and cartoons. Gestures elicited an N400-like component (gesture N450) that was larger for incongruent than congruent items, as well as a late positivity that was larger for congruent items. In Experiment 2, participants assessed the relatedness between probe words and preceding cartoon-gesture pairs. N450 effects to gestures were observed without overlapping positivity. These findings suggest that iconic gestures are subject to semantic processes analogous to those evoked by other meaningful representations, such as pictures and words.},
  note = {PubMed query source: Ying Wu}
}

@article{Tanji200515800183,
  title = {High-frequency gamma-band activity in the basal temporal cortex during picture-naming and lexical-decision tasks.},
  author = {Tanji, K and Suzuki, K and Delorme, A and Shamoto, H and Nakasato, N},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {2005},
  doi = {10.1523/JNEUROSCI.4948-04.2005},
  pmid = {15800183},
  url = {https://pubmed.ncbi.nlm.nih.gov/15800183/},
  abstract = {Gamma-band activity (GBA) in electroencephalograms (EEGs) has been shown to reflect various cognitive processes. GBA has typically been recorded in the 30-60 Hz range in scalp EEGs. Recently, task-related "high GBA" (HGBA) with frequencies up to 100 Hz has been observed in studies with invasive electrocorticograms (ECoGs). In the present study, we recorded ECoGs from the bilateral basal temporal cortices in a patient with epilepsy and evaluated the task-related HGBA (most prominently in the 80-120 Hz range) accompanying picture-naming and lexical-decision tasks. We examined picture naming using two categories (line drawings of animals and tools). The lexical-decision task was performed using words and pseudowords of two distinct Japanese writing forms, kanji (morphograms) and kana (syllabograms). Task-related HGBA was observed bilaterally during the naming task. Recordings from some electrodes revealed significant differences in HGBA between animal and tool pictures. In contrast to the naming task, there was apparent left dominance in the lexical-decision task. Furthermore, significant differences in HGBA were observed between the Japanese kanji and kana words and between the kanji words and kanji pseudowords. A number of differences in the HGBA observed in the recordings from the basal temporal area were consistent with previous findings from neuroimaging and patient studies and suggest that HGBA is a good correlate of visual cognitive functions.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Onton200515927487,
  title = {Frontal midline EEG dynamics during working memory.},
  author = {Onton, J and Delorme, A and Makeig, S},
  journal = {NeuroImage},
  year = {2005},
  doi = {10.1016/j.neuroimage.2005.04.014},
  pmid = {15927487},
  url = {https://pubmed.ncbi.nlm.nih.gov/15927487/},
  abstract = {We show that during visual working memory, the electroencephalographic (EEG) process producing 5-7 Hz frontal midline theta (fmtheta) activity exhibits multiple spectral modes involving at least three frequency bands and a wide range of amplitudes. The process accounting for the fmtheta increase during working memory was separated from 71-channel data by clustering on time/frequency transforms of components returned by independent component analysis (ICA). Dipole models of fmtheta component scalp maps were consistent with their generation in or near dorsal anterior cingulate cortex. From trial to trial, theta power of fmtheta components varied widely but correlated moderately with theta power in other frontal and left temporal processes. The weak mean increase in frontal midline theta power with increasing memory load, produced entirely by the fmtheta components, largely reflected progressively stronger theta activity in a relatively small proportion of trials. During presentations of letter series to be memorized or ignored, fmtheta components also exhibited 12-15 Hz low-beta activity that was stronger during memorized than during ignored letter trials, independent of letter duration. The same components produced a brief 3-Hz burst 500 ms after onset of the Probe letter following each letter sequence. A new decomposition method, log spectral ICA, applied to normalized log time/frequency transforms of fmtheta component Memorize-letter trials, showed that their low-beta activity reflected harmonic energy in continuous, sharp-peaked theta wave trains as well as independent low-beta bursts. Possibly, the observed fmtheta process variability may index dynamic adjustments in medial frontal cortex to trial-specific behavioral context and task demands.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Sornborger200515661304,
  title = {Extraction of the average and differential dynamical response in stimulus-locked experimental data.},
  author = {Sornborger, A and Yokoo, T and Delorme, A and Sailstad, C and Sirovich, L},
  journal = {Journal of neuroscience methods},
  year = {2005},
  doi = {10.1016/j.jneumeth.2004.06.012},
  pmid = {15661304},
  url = {https://pubmed.ncbi.nlm.nih.gov/15661304/},
  abstract = {In optical imaging experiments of primary visual cortex, visual stimuli evoke a complicated dynamics. Typically, any stimulus with sufficient contrast evokes a response. Much of the response is the same regardless of which stimulus is presented. For instance, when oriented drifting gratings are presented to the visual system, over 90% of the response is the same from orientation to orientation. Small differences may be seen, however, between the responses to different orientations. A problem in the analysis of optical measurements of the response to stimulus in cortical tissue is the distinction of the 'global' or 'non-specific' response from the 'differential' or 'stimulus-specific' response. This problem arises whenever the signal of interest is the difference in response to various stimuli and is evident in many kinds of uni- and multivariate data. To this end, we present enhancements to a frequency-based method that we previously introduced called the periodic stacking method. These enhancements allow us to separately estimate the dynamics of both the average signal across all stimuli (the 'global' response) and deviations from the average amongst the various stimuli (the 'stimulus-specific' response) evoked in response to a set of stimuli. We also discuss improvements in the signal-to-noise ratio, relative to standard trial averaging methods, that result from the data-adaptive smoothing in our method.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Huang200517281564,
  title = {Analyzing event-related brain dynamics in continuous compensatory tracking tasks.},
  author = {Huang, RS and Jung, TP and Makeig, S},
  journal = {Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference},
  year = {2005},
  doi = {10.1109/IEMBS.2005.1615794},
  pmid = {17281564},
  url = {https://pubmed.ncbi.nlm.nih.gov/17281564/},
  abstract = {The dynamics of electroencephalographic (EEG) activity in continuous compensatory tracking tasks were analyzed by independent component analysis (ICA) and time-frequency techniques. In one-hour sessions, 72-channel EEG was recorded while a healthy volunteer attempted to use a trackball to keep a drifting disc in a bulls-eye in the center of screen. Disc trajectory was converted into a moving measure of disc error. Local minima (perigees) indicated moments when the disc started to drift away from the center. Subject performance was indexed by root mean square disc error in a 20s epoch centered on each perigee, high error generally indicating drowsiness. Maximally independent EEG processes and their equivalent dipole source locations were obtained using the EEGLAB toolbox (http://sccn.ucsd.edu/eeglab). Component activations were epoched in 5s time intervals time locked to perigees. Following disk perigees during (drowsy) periods of high disk error, significant spectral changes were observed. One of the 70 independent components was located in or near primary visual cortex. During periods of poor (drowsy) performance, it had increased mean tonic alpha/theta activity, with a further phasic alpha/theta increase following perigees [1,2]. At the same time, low alpha activity of a second component located in or near cingulate gyrus increased, and 10-30 Hz EEG activity of a third component in the left somatomotor cortex increased briefly. The alpha activity of the somatomotor component persisted through the following distance maximum. These spatiotemporal phenomena were consistently observed across three sessions within subjects. Thus, event-related EEG brain dynamics can be detected and modeled in a continuous behavioral task without impulsive event onsets.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200415120678,
  title = {Mining event-related brain dynamics.},
  author = {Makeig, S and Debener, S and Onton, J and Delorme, A},
  journal = {Trends in cognitive sciences},
  year = {2004},
  doi = {10.1016/j.tics.2004.03.008},
  pmid = {15120678},
  url = {https://pubmed.ncbi.nlm.nih.gov/15120678/},
  abstract = {This article provides a new, more comprehensive view of event-related brain dynamics founded on an information-based approach to modeling electroencephalographic (EEG) dynamics. Most EEG research focuses either on peaks 'evoked' in average event-related potentials (ERPs) or on changes 'induced' in the EEG power spectrum by experimental events. Although these measures are nearly complementary, they do not fully model the event-related dynamics in the data, and cannot isolate the signals of the contributing cortical areas. We propose that many ERPs and other EEG features are better viewed as time/frequency perturbations of underlying field potential processes. The new approach combines independent component analysis (ICA), time/frequency analysis, and trial-by-trial visualization that measures EEG source dynamics without requiring an explicit head model.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Delorme200415019707,
  title = {Interaction of top-down and bottom-up processing in the fast visual analysis of natural scenes.},
  author = {Delorme, A and Rousselet, GA and Macé, MJ and Fabre-Thorpe, M},
  journal = {Brain research. Cognitive brain research},
  year = {2004},
  doi = {10.1016/j.cogbrainres.2003.11.010},
  pmid = {15019707},
  url = {https://pubmed.ncbi.nlm.nih.gov/15019707/},
  abstract = {The influence of task requirements on the fast visual processing of natural scenes was studied in 14 human subjects performing in alternation an "animal" categorization task and a single-photograph recognition task. Target photographs were randomly mixed with non-target images and flashed for only 20 ms. Subjects had to respond to targets within 1 s. Processing time for image-recognition was 30-40 ms shorter than for the categorization task, both for the fastest behavioral responses and for the latency at which event related potentials evoked by target and non-target stimuli started to diverge. The faster processing in image-recognition is shown to be due to the use of low-level cues, but source analysis produced evidence that, regardless of the task, the dipoles accounting for the differential activity had the same localization and orientation in the occipito-temporal cortex. We suggest that both tasks involve the same visual pathway and the same decisional brain area but because of the total predictability of the target in the image recognition task, the first wave of bottom-up feed-forward information is speeded up by top-down influences that might originate in the prefrontal cortex and preset lower levels of the visual pathway to the known target features.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Luu200415261861,
  title = {Frontal midline theta and the error-related negativity: neurophysiological mechanisms of action regulation.},
  author = {Luu, P and Tucker, DM and Makeig, S},
  journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
  year = {2004},
  doi = {10.1016/j.clinph.2004.03.031},
  pmid = {15261861},
  url = {https://pubmed.ncbi.nlm.nih.gov/15261861/},
  abstract = {The error-related negativity (ERN) is an event-related potential (ERP) peak occurring between 50 and 100 ms after the commission of a speeded motor response that the subject immediately realizes to be in error. The ERN is believed to index brain processes that monitor action outcomes. Our previous analyses of ERP and EEG data suggested that the ERN is dominated by partial phase-locking of intermittent theta-band EEG activity. In this paper, this possibility is further evaluated. The possibility that the ERN is produced by phase-locking of theta-band EEG activity was examined by analyzing the single-trial EEG traces from a forced-choice speeded response paradigm before and after applying theta-band (4-7 Hz) filtering and by comparing the averaged and single-trial phase-locked (ERP) and non-phase-locked (other) EEG data. Electrical source analyses were used to estimate the brain sources involved in the generation of the ERN. Beginning just before incorrect button presses in a speeded choice response paradigm, midfrontal theta-band activity increased in amplitude and became partially and transiently phase-locked to the subject's motor response, accounting for 57% of ERN peak amplitude. The portion of the theta-EEG activity increase remaining after subtracting the response-locked ERP from each trial was larger and longer lasting after error responses than after correct responses, extending on average 400 ms beyond the ERN peak. Multiple equivalent-dipole source analysis suggested 3 possible equivalent dipole sources of the theta-bandpassed ERN, while the scalp distribution of non-phase-locked theta amplitude suggested the presence of additional frontal theta-EEG sources. These results appear consistent with a body of research that demonstrates a relationship between limbic theta activity and action regulation, including error monitoring and learning.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200415208723,
  title = {Electroencephalographic brain dynamics following manually responded visual targets.},
  author = {Makeig, S and Delorme, A and Westerfield, M and Jung, TP and Townsend, J and Courchesne, E and Sejnowski, TJ},
  journal = {PLoS biology},
  year = {2004},
  doi = {10.1371/journal.pbio.0020176},
  pmid = {15208723},
  url = {https://pubmed.ncbi.nlm.nih.gov/15208723/},
  abstract = {Scalp-recorded electroencephalographic (EEG) signals produced by partial synchronization of cortical field activity mix locally synchronous electrical activities of many cortical areas. Analysis of event-related EEG signals typically assumes that poststimulus potentials emerge out of a flat baseline. Signals associated with a particular type of cognitive event are then assessed by averaging data from each scalp channel across trials, producing averaged event-related potentials (ERPs). ERP averaging, however, filters out much of the information about cortical dynamics available in the unaveraged data trials. Here, we studied the dynamics of cortical electrical activity while subjects detected and manually responded to visual targets, viewing signals retained in ERP averages not as responses of an otherwise silent system but as resulting from event-related alterations in ongoing EEG processes. We applied infomax independent component analysis to parse the dynamics of the unaveraged 31-channel EEG signals into maximally independent processes, then clustered the resulting processes across subjects by similarities in their scalp maps and activity power spectra, identifying nine classes of EEG processes with distinct spatial distributions and event-related dynamics. Coupled two-cycle postmotor theta bursts followed button presses in frontal midline and somatomotor clusters, while the broad postmotor "P300" positivity summed distinct contributions from several classes of frontal, parietal, and occipital processes. The observed event-related changes in local field activities, within and between cortical areas, may serve to modulate the strength of spike-based communication between cortical areas to update attention, expectancy, memory, and motor preparation during and after target recognition and speeded responding.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Delorme200415102499,
  title = {EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.},
  author = {Delorme, A and Makeig, S},
  journal = {Journal of neuroscience methods},
  year = {2004},
  doi = {10.1016/j.jneumeth.2003.10.009},
  pmid = {15102499},
  url = {https://pubmed.ncbi.nlm.nih.gov/15102499/},
  abstract = {We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEG data of any number of channels. Available functions include EEG data, channel and event information importing, data visualization (scrolling, scalp map and dipole model plotting, plus multi-trial ERP-image plots), preprocessing (including artifact rejection, filtering, epoch selection, and averaging), independent component analysis (ICA) and time/frequency decompositions including channel and component cross-coherence supported by bootstrap statistical methods based on data resampling. EEGLAB functions are organized into three layers. Top-layer functions allow users to interact with the data through the graphic interface without needing to use MATLAB syntax. Menu options allow users to tune the behavior of EEGLAB to available memory. Middle-layer functions allow users to customize data processing using command history and interactive 'pop' functions. Experienced MATLAB users can use EEGLAB data structures and stand-alone signal processing functions to write custom and/or batch analysis scripts. Extensive function help and tutorial information are included. A 'plug-in' facility allows easy incorporation of new EEG modules into the main menu. EEGLAB is freely available (http://www.sccn.ucsd.edu/eeglab/) under the GNU public license for noncommercial use and open source development, together with sample data, user tutorial and extensive documentation.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Culm200312915235,
  title = {Reduced G(i) and G(o) protein function in the rat nucleus accumbens attenuates sensorimotor gating deficits.},
  author = {Culm, KE and Lim, AM and Onton, JA and Hammer, RP},
  journal = {Brain research},
  year = {2003},
  doi = {10.1016/s0006-8993(03)02880-4},
  pmid = {12915235},
  url = {https://pubmed.ncbi.nlm.nih.gov/12915235/},
  abstract = {Prepulse inhibition of the acoustic startle response (PPI) is a cross-species measure of sensorimotor gating, which is severely disrupted in patients with schizophrenia. PPI deficits can be produced in experimental animals by administration of selective D(2)-like dopamine receptor agonists in the nucleus accumbens (NAc). G proteins coupled to these receptors reportedly are altered in the NAc of patients with schizophrenia. Therefore, we sought to determine whether experimental inactivation of intracellular G proteins in the NAc alters PPI. In adult male Sprague-Dawley rats, baseline PPI was determined by presenting acoustic pulse stimuli (120 dB) alone or preceded 100 ms earlier by prepulse stimuli (3, 6 or 12 dB above 70 dB ambient noise). PPI disruption was assessed in the presence of quinpirole (0.0, 0.05, 0.1, 0.5 mg/kg, sc), and pertussis toxin (PTX; 0.05 microg/side) was then infused into the NAc bilaterally. Ten days later, quinpirole-mediated disruption of PPI was significantly reduced; neither PTX alone, nor heat-inactivated PTX had any effect on quinpirole-induced PPI reductions. PPI was significantly higher after PTX infusion upon moderate quinpirole challenge, suggesting that D(2)-like receptors were less effective. PTX treatment significantly reduced basal and dopamine-stimulated [35S]GTPgammaS binding in the NAc core and shell, and reduced G(i)(alpha) protein immunoreactivity in the NAc. The results suggest that PPI disruption mediated by D(2)-like receptor activation in the NAc depends on coupling to G(i) and G(o) proteins, alteration of which could cause sensorimotor gating deficits in schizophrenia.},
  note = {PubMed query source: Julie Onton}
}

@article{Delorme200314618070,
  title = {Early cortical orientation selectivity: how fast inhibition decodes the order of spike latencies.},
  author = {Delorme, A},
  journal = {Journal of computational neuroscience},
  year = {2003},
  doi = {10.1023/a:1027420012134},
  pmid = {14618070},
  url = {https://pubmed.ncbi.nlm.nih.gov/14618070/},
  abstract = {Following a flashed stimulus, I show that a simple neurophysiological mechanism in the primary visual system can generate orientation selectivity based on the first incoming spikes. A biological model of the lateral geniculate nucleus generates an asynchronous wave of spikes, with the most strongly activated neurons firing first. Geniculate activation leads to both the direct excitation of a cortical pyramidal cell and disynaptic feed-forward inhibition. The mechanism provides automatic gain control, so the cortical neurons respond over a wide range of stimulus contrasts. It also demonstrates the biological plausibility of a new computationally efficient neural code: latency rank order coding.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Delorme200312899255,
  title = {EEG changes accompanying learned regulation of 12-Hz EEG activity.},
  author = {Delorme, A and Makeig, S},
  journal = {IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2003},
  doi = {10.1109/TNSRE.2003.814428},
  pmid = {12899255},
  url = {https://pubmed.ncbi.nlm.nih.gov/12899255/},
  abstract = {We analyzed 15 sessions of 64-channel electroencephalographic (EEG) data recorded from a highly trained subject during sessions in which he attempted to regulate power at 12 Hz over his left- and right-central scalp to control the altitude of a cursor moving toward target boxes placed at the top-, middle-, or bottom-right of a computer screen. We used infomax independent component analysis (ICA) to decompose 64-channel EEG data from trials in which the subject successfully up- or down-regulated the measured EEG signals. Applying time-frequency analysis to the time courses of activity of several of the resulting 64 independent EEG components revealed that successful regulation of the measured activity was accompanied by extensive, asymmetrical changes in power and coherence, at both nearby and distant frequencies, in several parts of cortex. A more complete understanding of these phenomena could help to explain the nature and locus of learned regulation of EEG rhythms and might also suggest ways to further optimize the performance of brain-computer interfaces.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Anemller200314622887,
  title = {Complex independent component analysis of frequency-domain electroencephalographic data.},
  author = {Anemüller, J and Sejnowski, TJ and Makeig, S},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  year = {2003},
  doi = {10.1016/j.neunet.2003.08.003},
  pmid = {14622887},
  url = {https://pubmed.ncbi.nlm.nih.gov/14622887/},
  abstract = {Independent component analysis (ICA) has proven useful for modeling brain and electroencephalographic (EEG) data. Here, we present a new, generalized method to better capture the dynamics of brain signals than previous ICA algorithms. We regard EEG sources as eliciting spatio-temporal activity patterns, corresponding to, e.g. trajectories of activation propagating across cortex. This leads to a model of convolutive signal superposition, in contrast with the commonly used instantaneous mixing model. In the frequency-domain, convolutive mixing is equivalent to multiplicative mixing of complex signal sources within distinct spectral bands. We decompose the recorded spectral-domain signals into independent components by a complex infomax ICA algorithm. First results from a visual attention EEG experiment exhibit: (1). sources of spatio-temporal dynamics in the data, (2). links to subject behavior, (3). sources with a limited spectral extent, and (4). a higher degree of independence compared to sources derived by standard ICA.},
  note = {PubMed query source: Scott Makeig}
}

@article{Duann200211906223,
  title = {Single-trial variability in event-related BOLD signals.},
  author = {Duann, JR and Jung, TP and Kuo, WJ and Yeh, TC and Makeig, S and Hsieh, JC and Sejnowski, TJ},
  journal = {NeuroImage},
  year = {2002},
  doi = {10.1006/nimg.2001.1049},
  pmid = {11906223},
  url = {https://pubmed.ncbi.nlm.nih.gov/11906223/},
  abstract = {Most current analysis methods for fMRI data assume a priori knowledge of the time course of the hemodynamic response (HR) to experimental stimuli or events in brain areas of interest. In addition, they typically assume homogeneity of both the HR and the non-HR "noise" signals, both across brain regions and across similar experimental events. When HRs vary unpredictably, from area to area or from trial to trial, an alternative approach is needed. Here, we use Infomax independent component analysis (ICA) to detect and visualize variations in single-trial HRs in event-related fMRI data. Six subjects participated in four fMRI sessions each in which ten bursts of 8-Hz flickering-checkerboard stimulation were presented for 0.5-s (short) or 3-s (long) durations at 30-s intervals. Five axial slices were acquired by a Bruker 3-T magnetic resonance imager at interscan intervals of 500 ms (TR). ICA decomposition of the resulting blood oxygenation level-dependent (BOLD) data from each session produced an independent component active in primary visual cortex (V1) and, in several sessions, another active in medial temporal cortex (MT/V5). Visualizing sets of BOLD response epochs with novel BOLD-image plots demonstrated that component HRs varied substantially and often systematically across trials as well as across sessions, subjects, and brain areas. Contrary to expectation, in four of the six subjects the V1 component HR contained two positive peaks in response to short-stimulus bursts, while components with nearly identical regions of activity in long-stimulus sessions from the same subjects were associated with single-peaked HRs. Thus, ICA combined with BOLD-image visualization can reveal dramatic and unforeseen HR variations not apparent to researchers analyzing their data with event-related response averaging and fixed HR templates.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200212127749,
  title = {Response: event-related brain dynamics -- unifying brain electrophysiology.},
  author = {Makeig, S},
  journal = {Trends in neurosciences},
  year = {2002},
  doi = {10.1016/s0166-2236(02)02198-7},
  pmid = {12127749},
  url = {https://pubmed.ncbi.nlm.nih.gov/12127749/},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200211809976,
  title = {Dynamic brain sources of visual evoked responses.},
  author = {Makeig, S and Westerfield, M and Jung, TP and Enghoff, S and Townsend, J and Courchesne, E and Sejnowski, TJ},
  journal = {Science (New York, N.Y.)},
  year = {2002},
  doi = {10.1126/science.1066168},
  pmid = {11809976},
  url = {https://pubmed.ncbi.nlm.nih.gov/11809976/},
  abstract = {It has been long debated whether averaged electrical responses recorded from the scalp result from stimulus-evoked brain events or stimulus-induced changes in ongoing brain dynamics. In a human visual selective attention task, we show that nontarget event-related potentials were mainly generated by partial stimulus-induced phase resetting of multiple electroencephalographic processes. Independent component analysis applied to the single-trial data identified at least eight classes of contributing components, including those producing central and lateral posterior alpha, left and right mu, and frontal midline theta rhythms. Scalp topographies of these components were consistent with their generation in compact cortical domains.},
  note = {PubMed query source: Scott Makeig}
}

@article{Thorpe200111665765,
  title = {Spike-based strategies for rapid processing.},
  author = {Thorpe, S and Delorme, A and Van Rullen, R},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  year = {2001},
  doi = {10.1016/s0893-6080(01)00083-1},
  pmid = {11665765},
  url = {https://pubmed.ncbi.nlm.nih.gov/11665765/},
  abstract = {Most experimental and theoretical studies of brain function assume that neurons transmit information as a rate code, but recent studies on the speed of visual processing impose temporal constraints that appear incompatible with such a coding scheme. Other coding schemes that use the pattern of spikes across a population a neurons may be much more efficient. For example, since strongly activated neurons tend to fire first, one can use the order of firing as a code. We argue that Rank Order Coding is not only very efficient, but also easy to implement in biological hardware: neurons can be made sensitive to the order of activation of their inputs by including a feed-forward shunting inhibition mechanism that progressively desensitizes the neuronal population during a wave of afferent activity. In such a case, maximum activation will only be produced when the afferent inputs are activated in the order of their synaptic weights.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Jung200120824156,
  title = {Imaging Brain Dynamics Using Independent Component Analysis.},
  author = {Jung, TP and Makeig, S and McKeown, MJ and Bell, AJ and Lee, TW and Sejnowski, TJ},
  journal = {Proceedings of the IEEE. Institute of Electrical and Electronics Engineers},
  year = {2001},
  doi = {10.1109/5.939827},
  pmid = {20824156},
  url = {https://pubmed.ncbi.nlm.nih.gov/20824156/},
  abstract = {The analysis of electroencephalographic (EEG) and magnetoencephalographic (MEG) recordings is important both for basic brain research and for medical diagnosis and treatment. Independent component analysis (ICA) is an effective method for removing artifacts and separating sources of the brain signals from these recordings. A similar approach is proving useful for analyzing functional magnetic resonance brain imaging (fMRI) data. In this paper, we outline the assumptions underlying ICA and demonstrate its application to a variety of electrical and hemodynamic recordings from the human brain.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delorme200111665771,
  title = {Face identification using one spike per neuron: resistance to image degradations.},
  author = {Delorme, A and Thorpe, SJ},
  journal = {Neural networks : the official journal of the International Neural Network Society},
  year = {2001},
  doi = {10.1016/s0893-6080(01)00049-1},
  pmid = {11665771},
  url = {https://pubmed.ncbi.nlm.nih.gov/11665771/},
  abstract = {The short response latencies of face selective neurons in the inferotemporal cortex impose major constraints on models of visual processing. It appears that visual information must essentially propagate in a feed-forward fashion with most neurons only having time to fire one spike. We hypothesize that flashed stimuli can be encoded by the order of firing of ganglion cells in the retina and propose a neuronal mechanism, that could be related to fast shunting inhibition, to decode such information. Based on these assumptions, we built a three-layered neural network of retino-topically organized neuronal maps. We showed, by using a learning rule involving spike timing dependant plasticity, that neuronal maps in the output layer can be trained to recognize natural photographs of faces. Not only was the model able to generalize to novel views of the same faces, it was also remarkably resistant to image noise and reductions in contrast.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{VanOrden200111474756,
  title = {Eye activity correlates of workload during a visuospatial memory task.},
  author = {Van Orden, KF and Limbert, W and Makeig, S and Jung, TP},
  journal = {Human factors},
  year = {2001},
  doi = {10.1518/001872001775992570},
  pmid = {11474756},
  url = {https://pubmed.ncbi.nlm.nih.gov/11474756/},
  abstract = {Changes in six measures of eye activity were assessed as a function of task workload in a target identification memory task. Eleven participants completed four 2-hr blocks of a mock anti-air-warfare task, in which they were required to examine and remember target classifications (friend/enemy) for subsequent prosecution (fire upon/allow to pass), while targets moved steadily toward two centrally located ship icons. Target density served as the task workload variable; between one and nine targets were simultaneously present on the display. For each participant, moving estimates of blink frequency and duration, fixation frequency and dwell time, saccadic extent, and mean pupil diameter, integrated over periods of 10 to 20 s, demonstrated systematic changes as a function of target density. Nonlinear regression analyses found blink frequency, fixation frequency, and pupil diameter to be the most predictive variables relating eye activity to target density. Participant-specific artificial neural network models, developed through training on two or three sessions and subsequently tested on a different session from the same participant, correlated well with actual target density levels (mean R = 0.66). Results indicate that moving mean estimation and artificial neural network techniques enable information from multiple eye measures to be combined to produce reliable near-real-time indicators of workload in some visuospatial tasks. Potential applications include the monitoring of visual activity of system opetators for indications of visual workload and scanning efficiency.},
  note = {PubMed query source: Scott Makeig}
}

@article{Townsend200111240116,
  title = {Event-related brain response abnormalities in autism: evidence for impaired cerebello-frontal spatial attention networks.},
  author = {Townsend, J and Westerfield, M and Leaver, E and Makeig, S and Jung, T and Pierce, K and Courchesne, E},
  journal = {Brain research. Cognitive brain research},
  year = {2001},
  doi = {10.1016/s0926-6410(00)00072-0},
  pmid = {11240116},
  url = {https://pubmed.ncbi.nlm.nih.gov/11240116/},
  abstract = {Although under some conditions the attention-related late positive event-related potential (ERP) response (LPC) is apparently normal in autism during visual processing, the LPC elicited by visuospatial processing may be compromised. Results from this study provide evidence for abnormalities in autism in two components of the LPC generated during spatial processing. The early frontal distribution of the LPC which may reflect attention orienting was delayed or missing in autistic subjects during conditions in which attention was to peripheral visual fields. The later parietal distribution of the LPC which may be associated with context updating was smaller in amplitude in autistic subjects regardless of attention location. Both abnormalities suggest disruption of function in spatial attention networks in autism. Evidence that the cerebellar abnormalities in autism may underlie these deficits comes from: (1) similar results in ERP responses and spatial attention deficits in patients with cerebellar lesions; (2) brain-behavior correlations in normally functioning individuals associating the size of the posterior cerebellar vermis and the latency of the frontal LPC; and (3) a previously reported complementary correlation between the size of the posterior vermal lobules and spatial orienting speed. Although the scalp-recorded LPC is thought to be cortically generated, it may be modulated by subcortical neural activity. The cerebellum may serve as a modulating influence by affecting the task-related antecedent attentional process. The electrophysiological abnormalities reported here index spatial attention deficits in autism that may reflect cerebellar influence on both frontal and parietal spatial attention function.},
  note = {PubMed query source: Scott Makeig}
}

@article{Jung200111559961,
  title = {Analysis and visualization of single-trial event-related potentials.},
  author = {Jung, TP and Makeig, S and Westerfield, M and Townsend, J and Courchesne, E and Sejnowski, TJ and New Collective Author},
  journal = {Human brain mapping},
  year = {2001},
  doi = {10.1002/hbm.1050},
  pmid = {11559961},
  url = {https://pubmed.ncbi.nlm.nih.gov/11559961/},
  abstract = {In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data.},
  note = {PubMed query source: Scott Makeig}
}

@article{Jung200010731767,
  title = {Removing electroencephalographic artifacts by blind source separation.},
  author = {Jung, TP and Makeig, S and Humphries, C and Lee, TW and McKeown, MJ and Iragui, V and Sejnowski, TJ},
  journal = {Psychophysiology},
  year = {2000},
  pmid = {10731767},
  url = {https://pubmed.ncbi.nlm.nih.gov/10731767/},
  abstract = {Eye movements, eye blinks, cardiac signals, muscle noise, and line noise present serious problems for electroencephalographic (EEG) interpretation and analysis when rejecting contaminated EEG segments results in an unacceptable data loss. Many methods have been proposed to remove artifacts from EEG recordings, especially those arising from eye movements and blinks. Often regression in the time or frequency domain is performed on parallel EEG and electrooculographic (EOG) recordings to derive parameters characterizing the appearance and spread of EOG artifacts in the EEG channels. Because EEG and ocular activity mix bidirectionally, regressing out eye artifacts inevitably involves subtracting relevant EEG signals from each record as well. Regression methods become even more problematic when a good regressing channel is not available for each artifact source, as in the case of muscle artifacts. Use of principal component analysis (PCA) has been proposed to remove eye artifacts from multichannel EEG. However, PCA cannot completely separate eye artifacts from brain signals, especially when they have comparable amplitudes. Here, we propose a new and generally applicable method for removing a wide variety of artifacts from EEG records based on blind source separation by independent component analysis (ICA). Our results on EEG data collected from normal and autistic subjects show that ICA can effectively detect, separate, and remove contamination from a wide variety of artifactual sources in EEG records with results comparing favorably with those obtained using regression and PCA methods. ICA can also be used to analyze blink-related brain activity.},
  note = {PubMed query source: Scott Makeig}
}

@article{Jung200011018488,
  title = {Removal of eye activity artifacts from visual event-related potentials in normal and clinical subjects.},
  author = {Jung, TP and Makeig, S and Westerfield, M and Townsend, J and Courchesne, E and Sejnowski, TJ},
  journal = {Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology},
  year = {2000},
  doi = {10.1016/s1388-2457(00)00386-2},
  pmid = {11018488},
  url = {https://pubmed.ncbi.nlm.nih.gov/11018488/},
  abstract = {Electrical potentials produced by blinks and eye movements present serious problems for electroencephalographic (EEG) and event-related potential (ERP) data interpretation and analysis, particularly for analysis of data from some clinical populations. Often, all epochs contaminated by large eye artifacts are rejected as unusable, though this may prove unacceptable when blinks and eye movements occur frequently. Frontal channels are often used as reference signals to regress out eye artifacts, but inevitably portions of relevant EEG signals also appearing in EOG channels are thereby eliminated or mixed into other scalp channels. A generally applicable adaptive method for removing artifacts from EEG records based on blind source separation by independent component analysis (ICA) (Neural Computation 7 (1995) 1129; Neural Computation 10(8) (1998) 2103; Neural Computation 11(2) (1999) 606) overcomes these limitations. Results on EEG data collected from 28 normal controls and 22 clinical subjects performing a visual selective attention task show that ICA can be used to effectively detect, separate and remove ocular artifacts from even strongly contaminated EEG recordings. The results compare favorably to those obtained using rejection or regression methods. The ICA method can preserve ERP contributions from all of the recorded trials and all the recorded data channels, even when none of the single trials are artifact-free.},
  note = {PubMed query source: Scott Makeig}
}

@article{Byrnes200010800749,
  title = {Inhibition of nitric oxide synthase in the ventral tegmental area attenuates cocaine sensitization in rats.},
  author = {Byrnes, JJ and Pantke, MM and Onton, JA and Hammer, RP},
  journal = {Progress in neuro-psychopharmacology & biological psychiatry},
  year = {2000},
  doi = {10.1016/s0278-5846(99)00094-9},
  pmid = {10800749},
  url = {https://pubmed.ncbi.nlm.nih.gov/10800749/},
  abstract = {1. Male Sprague-Dawley rats were pretreated via bilateral infusion of the VTA with the selective neuronal nitric oxide synthase inhibitor, 7-nitroindazole (0, 8, or 40 ng/hemisphere), prior to each of 7 daily systemic cocaine (30 mg/kg, i.p.) or saline (1 ml/kg) treatments. 2. After a 7-day treatment withdrawal period, rats received a final systemic challenge with either cocaine (30 mg/kg, i.p.) or saline (1 ml/kg). 3. Locomotor and stereotypic activity were measured following the first and last treatments. 4. Daily cocaine treatment led to the development of sensitization to its stereotypic effects as revealed upon drug challenge. 5. The development of sensitization of cocaine-induced stereotypy was completely blocked by daily intra-VTA pretreatment with 7-nitroindazole. 6. In addition, attenuation of the locomotor effects of cocaine challenge was also observed in animals that received daily intra-VTA 7-nitroindazole (40 ng/hemisphere) infusions. 7. The results indicate that VTA nitric oxide is necessary for the development of sensitization of cocaine-induced stereotypic behavior, and that its repeated inhibition may produce lasting effects on the locomotor response to the drug.},
  note = {PubMed query source: Julie Onton}
}

@article{VanOrden200010725565,
  title = {Combined eye activity measures accurately estimate changes in sustained visual task performance.},
  author = {Van Orden, KF and Jung, TP and Makeig, S},
  journal = {Biological psychology},
  year = {2000},
  doi = {10.1016/s0301-0511(99)00043-5},
  pmid = {10725565},
  url = {https://pubmed.ncbi.nlm.nih.gov/10725565/},
  abstract = {Five concurrent eye activity measures were used to model fatigue-related changes in performance during a visual compensatory tracking task. Nine participants demonstrated considerable variations in performance level during two 53-min testing sessions in which continuous video-based eye activity measures were obtained. Using a trackball, participants were required to maneuver a target disk (destabilized by pseudorandom wind forces) within the center of an annulus on a CRT display. Mean tracking performance as a function of time across 18 sessions demonstrated a monotonic increase in error from 0 to 11 min, and a performance plateau thereafter. Individual performance fluctuated widely around this trend - with an average root mean square (RMS) error of 2.3 disk radii. For each participant, moving estimates of blink duration and frequency, fixation dwell time and frequency, and mean pupil diameter were analyzed using non-linear regression and artificial neural network techniques. Individual models were derived using eye and performance data from one session and cross-validated on data from a second session run on a different day. A general regression model (based only on fixation dwell time and frequency) trained on data from both sessions from all participants produced a correlation of estimated to actual tracking performance of R=0.68 and an RMS error of 1.55 (S. D.=0.26) disk radii. Individual non-linear regression models containing a general linear model term produced the cross-session correlations of estimated to actual tracking performance of R=0.67. Individualized neural network models derived from the data of both experimental sessions produced the lowest RMS error (mean=1.23 disk radii, S.D.=0.13) and highest correlation (R=0.82) between eye activity-based estimates and actual tracking performance. Results suggest that information from multiple eye measures may be combined to produce accurate individualized real-time estimates of sub-minute scale performance changes during sustained tasks.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200011195717,
  title = {Awareness during drowsiness: dynamics and electrophysiological correlates.},
  author = {Makeig, S and Jung, TP and Sejnowski, TJ and New Collective Author},
  journal = {Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale},
  year = {2000},
  doi = {10.1037/h0087346},
  pmid = {11195717},
  url = {https://pubmed.ncbi.nlm.nih.gov/11195717/},
  abstract = {During drowsy periods, performance on tasks requiring continuous attention becomes intermittent. Previously, we have reported that during drowsy periods of intermittent performance, 7 of 10 participants performing an auditory detection task exhibited episodes of non-responding lasting about 18 s (Makeig & Jung, 1996). Further, the time patterns of these episodes were repeated precisely in subsequent sessions. The 18-s cycles were accompanied by counterbalanced power changes within two frequency bands in the vertex EEG (near 4 Hz and circa 40 Hz). In the present experiment, performance patterns and concurrent EEG spectra were examined in four participants performing a continuous visuomotor compensatory tracking task in 15-20 minute bouts during a 42-hour sleep deprivation study. During periods of good performance, participants made compensatory trackball movements about twice per second, attempting to keep a target disk near a central ring. Autocorrelations of time series representing the distance of the target disk from the ring centre showed that during periods of poor performance marked near-18-s cycles in performance again appeared. There were phases of poor or absent performance accompanied by an increase in EEG power that was largest at 3-4 Hz. These studies show that in drowsy humans, opening and closing of the gates of behavioural awareness is marked not by the appearance of (12-14 Hz) sleep spindles, but by prominent EEG amplitude changes in the low theta band. Further, both EEG and behavioural changes during drowsiness often exhibit stereotyped 18-s cycles.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig200010896189,
  title = {A natural basis for efficient brain-actuated control.},
  author = {Makeig, S and Enghoff, S and Jung, TP and Sejnowski, TJ and New Collective Author},
  journal = {IEEE transactions on rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society},
  year = {2000},
  doi = {10.1109/86.847818},
  pmid = {10896189},
  url = {https://pubmed.ncbi.nlm.nih.gov/10896189/},
  abstract = {The prospect of noninvasive brain-actuated control of computerized screen displays or locomotive devices is of interest to many and of crucial importance to a few 'locked-in' subjects who experience near total motor paralysis while retaining sensory and mental faculties. Currently several groups are attempting to achieve brain-actuated control of screen displays using operant conditioning of particular features of the spontaneous scalp electroencephalogram (EEG) including central mu-rhythms (9-12 Hz). A new EEG decomposition technique, independent component analysis (ICA), appears to be a foundation for new research in the design of systems for detection and operant control of endogenous EEG rhythms to achieve flexible EEG-based communication. ICA separates multichannel EEG data into spatially static and temporally independent components including separate components accounting for posterior alpha rhythms and central mu activities. We demonstrate using data from a visual selective attention task that ICA-derived mu-components can show much stronger spectral reactivity to motor events than activity measures for single scalp channels. ICA decompositions of spontaneous EEG would thus appear to form a natural basis for operant conditioning to achieve efficient and multidimensional brain-actuated control in motor-limited and locked-in subjects.},
  note = {PubMed query source: Scott Makeig}
}

@article{DeLorme199910235684,
  title = {Programmed cell death of an identified motoneuron examined in vivo: electrophysiological and morphological correlates.},
  author = {DeLorme, AW and Mesce, KA},
  journal = {Journal of neurobiology},
  year = {1999},
  doi = {10.1002/(sici)1097-4695(199905)39:2<307::aid-neu14>3.0.co;2-9},
  pmid = {10235684},
  url = {https://pubmed.ncbi.nlm.nih.gov/10235684/},
  abstract = {A paucity of information exists about the electrophysiological and anatomical correlates of neurons committed to die in vivo. Thus, we examined how an identified neuron, motoneuron MN-12, dies during development in the intact moth Manduca sexta. The developmental programmed cell death of this motoneuron was examined because of its defined commitment point of death. In addition, its ability to be unambiguously identified between animals and its accessibility to recording and dye injection facilitated our examination. MN-12 becomes committed to die approximately 28-30 h after adult emergence. At this time, MN-12 can no longer be saved by manipulations of steroid hormone levels, protein synthesis, or removal of descending inputs. Our initial prediction was that within a few hours after the commitment point, MN-12 would begin showing a gradual loss of central arbors and alterations in membrane properties. Contrary to our expectations, we found the MN-12 motoneuron to exhibit a stable central morphology and electrophysiological profile for approximately 12 h, followed by a rapid dismantling that occurred within a 1- to 2-h period. Several hours prior to the commitment point, the target muscle of MN-12 was no longer viable; yet, this did not affect the death of MN-12 or cause retraction of its motor terminals. We conclude that the delayed (12-h) onset of rapid cell death is not preceded by a slow accumulation of damages to the neuronal membrane (e.g., ion channels or cytoskeletal components) as both the electrical activity and morphology of MN-12 remained measurably unaltered during this 12-h lag.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Roman199910336531,
  title = {Pharmacological properties of trimebutine and N-monodesmethyltrimebutine.},
  author = {Roman, FJ and Lanet, S and Hamon, J and Brunelle, G and Maurin, A and Champeroux, P and Richard, S and Alessandri, N and Gola, M},
  journal = {The Journal of pharmacology and experimental therapeutics},
  year = {1999},
  pmid = {10336531},
  url = {https://pubmed.ncbi.nlm.nih.gov/10336531/},
  abstract = {Trimebutine [2-dimethylamino-2-phenylbutyl-3,4,5-trimethoxybenzoate hydrogen maleate (TMB)] has been demonstrated to be active for relieving abdominal pain in humans. To better understand its mechanism of action, we have tested TMB; nor-TMB, its main metabolite in humans; and their respective stereoisomers for their affinity toward sodium channels labeled by [3H]batrachotoxin, their effect on sodium, potassium, and calcium currents in rat dorsal root ganglia neurons, and their effect on veratridine-induced glutamate release from rat spinal cord slices. TMB has also been tested in an animal model of local anesthesia. TMB (Ki = 2.66 +/- 0.15 microM) and nor-TMB (Ki = 0.73 +/- 0.02 microM) displaced [3H]batrachotoxin from its binding site with affinities similar to that of bupivacaine (Ki = 7.1 +/- 0.9 microM). nor-TMB was found to block veratridine-induced glutamate release with an IC50 value of 8.5 microM, which is very similar to that of bupivacaine (IC50 = 8.2 microM); the effect of TMB was limited to 50% inhibition at 100 microM. TMB and nor-TMB blocked sodium currents in sensory neurons from rat dorsal root ganglia (IC50 = 0.83 +/- 0.09 and 1.23 +/- 0.19 microM, respectively), whereas no effect was observed on calcium currents at the same concentrations. A limited effect was observed on potassium currents (IC50 = 23 +/- 6 at 10 microM) for TMB. In vivo, when tested in the rabbit corneal reflex, TMB displayed a local anesthetic activity 17-fold more potent than that of lidocaine.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Makeig199910087080,
  title = {Functionally independent components of the late positive event-related potential during visual spatial attention.},
  author = {Makeig, S and Westerfield, M and Jung, TP and Covington, J and Townsend, J and Sejnowski, TJ and Courchesne, E},
  journal = {The Journal of neuroscience : the official journal of the Society for Neuroscience},
  year = {1999},
  doi = {10.1523/JNEUROSCI.19-07-02665.1999},
  pmid = {10087080},
  url = {https://pubmed.ncbi.nlm.nih.gov/10087080/},
  abstract = {Human event-related potentials (ERPs) were recorded from 10 subjects presented with visual target and nontarget stimuli at five screen locations and responding to targets presented at one of the locations. The late positive response complexes of 25-75 ERP average waveforms from the two task conditions were simultaneously analyzed with Independent Component Analysis, a new computational method for blindly separating linearly mixed signals. Three spatially fixed, temporally independent, behaviorally relevant, and physiologically plausible components were identified without reference to peaks in single-channel waveforms. A novel frontoparietal component (P3f) began at approximately 140 msec and peaked, in faster responders, at the onset of the motor command. The scalp distribution of P3f appeared consistent with brain regions activated during spatial orienting in functional imaging experiments. A longer-latency large component (P3b), positive over parietal cortex, was followed by a postmotor potential (Pmp) component that peaked 200 msec after the button press and reversed polarity near the central sulcus. A fourth component associated with a left frontocentral nontarget positivity (Pnt) was evoked primarily by target-like distractors presented in the attended location. When no distractors were presented, responses of five faster-responding subjects contained largest P3f and smallest Pmp components; when distractors were included, a Pmp component appeared only in responses of the five slower-responding subjects. Direct relationships between component amplitudes, latencies, and behavioral responses, plus similarities between component scalp distributions and regional activations reported in functional brain imaging experiments suggest that P3f, Pmp, and Pnt measure the time course and strength of functionally distinct brain processes.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig199910466141,
  title = {Functionally independent components of early event-related potentials in a visual spatial attention task.},
  author = {Makeig, S and Westerfield, M and Townsend, J and Jung, TP and Courchesne, E and Sejnowski, TJ},
  journal = {Philosophical transactions of the Royal Society of London. Series B, Biological sciences},
  year = {1999},
  doi = {10.1098/rstb.1999.0469},
  pmid = {10466141},
  url = {https://pubmed.ncbi.nlm.nih.gov/10466141/},
  abstract = {Spatial visual attention modulates the first negative-going deflection in the human averaged event-related potential (ERP) in response to visual target and non-target stimuli (the N1 complex). Here we demonstrate a decomposition of N1 into functionally independent subcomponents with functionally distinct relations to task and stimulus conditions. ERPs were collected from 20 subjects in response to visual target and non-target stimuli presented at five attended and non-attended screen locations. Independent component analysis, a new method for blind source separation, was trained simultaneously on 500 ms grand average responses from all 25 stimulus-attention conditions and decomposed the non-target N1 complexes into five spatially fixed, temporally independent and physiologically plausible components. Activity of an early, laterally symmetrical component pair (N1aR and N1aL) was evoked by the left and right visual field stimuli, respectively. Component N1aR peaked ca. 9 ms earlier than N1aL. Central stimuli evoked both components with the same peak latency difference, producing a bilateral scalp distribution. The amplitudes of these components were no reliably augmented by spatial attention. Stimuli in the right visual field evoked activity in a spatio-temporally overlapping bilateral component (N1b) that peaked at ca. 180 ms and was strongly enhanced by attention. Stimuli presented at unattended locations evoked a fourth component (P2a) peaking near 240 ms. A fifth component (P3f) was evoked only by targets presented in either visual field. The distinct response patterns of these components across the array of stimulus and attention conditions suggest that they reflect activity in functionally independent brain systems involved in processing attended and unattended visuospatial events.},
  note = {PubMed query source: Scott Makeig}
}

@article{Mourre199910565809,
  title = {Distribution in rat brain of binding sites of kaliotoxin, a blocker of Kv1.1 and Kv1.3 alpha-subunits.},
  author = {Mourre, C and Chernova, MN and Martin-Eauclaire, MF and Bessone, R and Jacquet, G and Gola, M and Alper, SL and Crest, M},
  journal = {The Journal of pharmacology and experimental therapeutics},
  year = {1999},
  pmid = {10565809},
  url = {https://pubmed.ncbi.nlm.nih.gov/10565809/},
  abstract = {The distribution of the binding sites for kaliotoxin (KTX), a blocker of voltage-dependent K(+) channels, was studied with quantitative autoradiography in adult rat brain and during postnatal brain maturation. Iodinated KTX bound specifically to tissue sections with a high affinity (K(d) = 82 pM) and a maximal binding capacity of 13.4 fmol/mg protein. The distribution of KTX binding sites within the central nervous system was heterogeneous. The highest densities were found in the neocortex, hypothalamus, dentate gyrus, bed nucleus of the stria terminalis, and parabrachial nuclei. The lowest level was observed in the white matter. From postnatal day 5 onward, KTX binding sites were detectable only in the hindbrain. The density of KTX binding sites in whole brain drastically increased after postnatal day 15 to achieve adult levels at postnatal day 60 in the whole brain. Bath application of KTX to Xenopus laevis oocytes blocked recombinant Kv1.3 and Kv1.1 channels potently and Kv1.2 channels less potently, with respective K(d) values of 0.1, 1.5, and 25 nM. KTX affinities for each of these channels expressed in mammalian cells were about 10-fold lower. A comparison of the distribution of KTX binding sites with that of Kv1 channel polypeptides, together with the pharmacology of KTX block, suggests that the principal targets for KTX in rat brain are K(+) channels containing Kv1.1 and Kv1.3 alpha-subunits.},
  note = {PubMed query source: Mateusz Gola}
}

@article{McKeown19989448244,
  title = {Spatially independent activity patterns in functional MRI data during the stroop color-naming task.},
  author = {McKeown, MJ and Jung, TP and Makeig, S and Brown, G and Kindermann, SS and Lee, TW and Sejnowski, TJ},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  year = {1998},
  doi = {10.1073/pnas.95.3.803},
  pmid = {9448244},
  url = {https://pubmed.ncbi.nlm.nih.gov/9448244/},
  abstract = {A method is given for determining the time course and spatial extent of consistently and transiently task-related activations from other physiological and artifactual components that contribute to functional MRI (fMRI) recordings. Independent component analysis (ICA) was used to analyze two fMRI data sets from a subject performing 6-min trials composed of alternating 40-sec Stroop color-naming and control task blocks. Each component consisted of a fixed three-dimensional spatial distribution of brain voxel values (a "map") and an associated time course of activation. For each trial, the algorithm detected, without a priori knowledge of their spatial or temporal structure, one consistently task-related component activated during each Stroop task block, plus several transiently task-related components activated at the onset of one or two of the Stroop task blocks only. Activation patterns occurring during only part of the fMRI trial are not observed with other techniques, because their time courses cannot easily be known in advance. Other ICA components were related to physiological pulsations, head movements, or machine noise. By using higher-order statistics to specify stricter criteria for spatial independence between component maps, ICA produced improved estimates of the temporal and spatial extent of task-related activation in our data compared with principal component analysis (PCA). ICA appears to be a promising tool for exploratory analysis of fMRI data, particularly when the time courses of activation are not known in advance.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig199821227248,
  title = {Response from Martin McKeown, Makeig, Brown, Jung, Kindermann, Bell and Sejnowski.},
  author = {Makeig, S and Brown, GG and Kindermann, SS and Jung, TP and Bell, AJ and Sejnowski, TJ and McKeown, MJ},
  journal = {Trends in cognitive sciences},
  year = {1998},
  doi = {10.1016/s1364-6613(98)01228-5},
  pmid = {21227248},
  url = {https://pubmed.ncbi.nlm.nih.gov/21227248/},
  note = {PubMed query source: Scott Makeig}
}

@article{McKeown19989673671,
  title = {Analysis of fMRI data by blind separation into independent spatial components.},
  author = {McKeown, MJ and Makeig, S and Brown, GG and Jung, TP and Kindermann, SS and Bell, AJ and Sejnowski, TJ},
  journal = {Human brain mapping},
  year = {1998},
  doi = {10.1002/(SICI)1097-0193(1998)6:3&#x0003c;160::AID-HBM5&#x0003e;3.0.CO;2-1},
  pmid = {9673671},
  url = {https://pubmed.ncbi.nlm.nih.gov/9673671/},
  abstract = {Current analytical techniques applied to functional magnetic resonance imaging (fMRI) data require a priori knowledge or specific assumptions about the time courses of processes contributing to the measured signals. Here we describe a new method for analyzing fMRI data based on the independent component analysis (ICA) algorithm of Bell and Sejnowski ([1995]: Neural Comput 7:1129-1159). We decomposed eight fMRI data sets from 4 normal subjects performing Stroop color-naming, the Brown and Peterson work/number task, and control tasks into spatially independent components. Each component consisted of voxel values at fixed three-dimensional locations (a component "map"), and a unique associated time course of activation. Given data from 144 time points collected during a 6-min trial, ICA extracted an equal number of spatially independent components. In all eight trials, ICA derived one and only one component with a time course closely matching the time course of 40-sec alternations between experimental and control tasks. The regions of maximum activity in these consistently task-related components generally overlapped active regions detected by standard correlational analysis, but included frontal regions not detected by correlation. Time courses of other ICA components were transiently task-related, quasiperiodic, or slowly varying. By utilizing higher-order statistics to enforce successively stricter criteria for spatial independence between component maps, both the ICA algorithm and a related fourth-order decomposition technique (Comon [1994]: Signal Processing 36:11-20) were superior to principal component analysis (PCA) in determining the spatial and temporal extent of task-related activation. For each subject, the time courses and active regions of the task-related ICA components were consistent across trials and were robust to the addition of simulated noise. Simulated movement artifact and simulated task-related activations added to actual fMRI data were clearly separated by the algorithm. ICA can be used to distinguish between nontask-related signal components, movements, and other artifacts, as well as consistently or transiently task-related fMRI activations, based on only weak assumptions about their spatial distributions and without a priori assumptions about their time courses. ICA appears to be a highly promising method for the analysis of fMRI data from normal and clinical populations, especially for uncovering unpredictable transient patterns of brain activity associated with performance of psychomotor tasks.},
  note = {PubMed query source: Scott Makeig}
}

@article{Delmas19979403140,
  title = {Low-threshold Na+ currents: a new family of receptor-operated inward currents in mammalian nerve cells.},
  author = {Delmas, P and Raggenbass, M and Gola, M},
  journal = {Brain research. Brain research reviews},
  year = {1997},
  doi = {10.1016/s0165-0173(97)00022-2},
  pmid = {9403140},
  url = {https://pubmed.ncbi.nlm.nih.gov/9403140/},
  abstract = {In the mammalian nervous system, various neurotransmitters can modulate cell excitability by inducing slow membrane potential changes. In the last decade, inhibition of potassium currents has been characterized as the primary mechanism by which neurones can undergo sustained depolarization. More recently (1990s), a new class of inward currents, which are voltage-dependent and mainly carried by sodium ions, has been found to be activated by various neurotransmitter receptors in mammalian central and peripheral neurones. Because the channels involved pass depolarizing current, are open at more negative membrane potentials than the resting potential, and are voltage-gated and persistent, these currents are capable of producing regenerative and maintained depolarizations and play an important role in neuronal signalling.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Jung19979214784,
  title = {Estimating alertness from the EEG power spectrum.},
  author = {Jung, TP and Makeig, S and Stensmo, M and Sejnowski, TJ},
  journal = {IEEE transactions on bio-medical engineering},
  year = {1997},
  doi = {10.1109/10.553713},
  pmid = {9214784},
  url = {https://pubmed.ncbi.nlm.nih.gov/9214784/},
  abstract = {In tasks requiring sustained attention, human alertness varies on a minute time scale. This can have serious consequences in occupations ranging from air traffic control to monitoring of nuclear power plants. Changes in the electroencephalographic (EEG) power spectrum accompany these fluctuations in the level of alertness, as assessed by measuring simultaneous changes in EEG and performance on an auditory monitoring task. By combining power spectrum estimation, principal component analysis and artificial neural networks, we show that continuous, accurate, noninvasive, and near real-time estimation of an operator's global level of alertness is feasible using EEG measures recorded from as few as two central scalp sites. This demonstration could lead to a practical system for noninvasive monitoring of the cognitive state of human operators in attention-critical settings.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig19979380745,
  title = {Blind separation of auditory event-related brain responses into independent components.},
  author = {Makeig, S and Jung, TP and Bell, AJ and Ghahremani, D and Sejnowski, TJ},
  journal = {Proceedings of the National Academy of Sciences of the United States of America},
  year = {1997},
  doi = {10.1073/pnas.94.20.10979},
  pmid = {9380745},
  url = {https://pubmed.ncbi.nlm.nih.gov/9380745/},
  abstract = {Averaged event-related potential (ERP) data recorded from the human scalp reveal electroencephalographic (EEG) activity that is reliably time-locked and phase-locked to experimental events. We report here the application of a method based on information theory that decomposes one or more ERPs recorded at multiple scalp sensors into a sum of components with fixed scalp distributions and sparsely activated, maximally independent time courses. Independent component analysis (ICA) decomposes ERP data into a number of components equal to the number of sensors. The derived components have distinct but not necessarily orthogonal scalp projections. Unlike dipole-fitting methods, the algorithm does not model the locations of their generators in the head. Unlike methods that remove second-order correlations, such as principal component analysis (PCA), ICA also minimizes higher-order dependencies. Applied to detected-and undetected-target ERPs from an auditory vigilance experiment, the algorithm derived ten components that decomposed each of the major response peaks into one or more ICA components with relatively simple scalp distributions. Three of these components were active only when the subject detected the targets, three other components only when the target went undetected, and one in both cases. Three additional components accounted for the steady-state brain response to a 39-Hz background click train. Major features of the decomposition proved robust across sessions and changes in sensor number and placement. This method of ERP analysis can be used to compare responses from multiple stimuli, task conditions, and subject states.},
  note = {PubMed query source: Scott Makeig}
}

@article{Cotton19979063464,
  title = {A potassium-channel toxin from the sea anemone Bunodosoma granulifera, an inhibitor for Kv1 channels. Revision of the amino acid sequence, disulfide-bridge assignment, chemical synthesis, and biological activity.},
  author = {Cotton, J and Crest, M and Bouet, F and Alessandri, N and Gola, M and Forest, E and Karlsson, E and Castañeda, O and Harvey, AL and Vita, C and Ménez, A},
  journal = {European journal of biochemistry},
  year = {1997},
  doi = {10.1111/j.1432-1033.1997.00192.x},
  pmid = {9063464},
  url = {https://pubmed.ncbi.nlm.nih.gov/9063464/},
  abstract = {The potassium channel toxin secreted by the sea anemone Bunodosoma granulifera (BgK) is a 37-amino-acid peptide containing three disulfide bridges. Because a synthetic peptide corresponding to the reported sequence of BgK was found not to fold properly, the sequence was determined again. The new sequence differed from the previous one in the C-terminal tetrapeptide, which contains two cysteines involved in disulfide bridging. The revised sequence is: V C R D W F K E T A C R H A K S L G N C R T S Q K Y R A N C A K T C E L C. The toxin BgK was synthesized according to the new sequence and folded successfully. Disulfide bridges were assigned by peptide mapping on both natural and synthetic forms to be between Cys2-Cys37, Cys11-Cys30 and Cys20-Cys34. The toxin contains a C-terminal free carboxylate as shown by comparing the native toxin with two synthetic peptides containing the C-terminus in either the carboxylate or carboxamido form. Synthetic BgK inhibits binding of 125I-alpha-dendrotoxin to rat brain synaptosomal membranes, similarly to natural BgK (nanomolar range). No activity was observed on maxi-K+ channels incorporated into planar lipid bilayers. The ability of BgK to block voltage-dependent K+ channels was determined from recordings of whole cell currents in Xenopus oocytes injected with cRNA encoding three cloned Kv1 channels (Kv1.1, Kv1.2, Kv1.3) and one Kv3 (Kv3.1) channel. The Shaker-related Kv1 channels are equally affected by BgK, while the Shaw-related channel Kv3.1 is insensitive up to 0.125 microM toxin. Indeed, half blockage of the current through the three Kv1 channels tested occurred in the same concentration range (Kd = 6 nM for Kv1.1, 15 nM for Kv1.2, 10 nM for Kv1.3). The specificity of BgK for the Shaker-related K+ channels indicates that BgK is able to discriminate a large group of neuronal Kv1 channels in situ. The sequence, the disulfide bridge pattern, the secondary structure and the biological activity of BgK demonstrated that the sea anemone toxins, i.e. BgK, ShK and Kaliseptine, constitute novel molecular probes useful for investigating K+ channel properties.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Makeig19968813409,
  title = {Tonic, phasic, and transient EEG correlates of auditory awareness in drowsiness.},
  author = {Makeig, S and Jung, TP},
  journal = {Brain research. Cognitive brain research},
  year = {1996},
  doi = {10.1016/0926-6410(95)00042-9},
  pmid = {8813409},
  url = {https://pubmed.ncbi.nlm.nih.gov/8813409/},
  abstract = {During drowsiness, human performance in responding to above-threshold auditory targets tends to vary irregularly over periods of 4 min and longer. These performance fluctuations are accompanied by distinct changes in the frequency spectrum of the electroencephalogram (EEG) on three time scales: (1) during minute-scale and longer periods of intermittent responding, mean activity levels in the (< 4 Hz) delta and (4-6 Hz) theta bands, and at the sleep spindle frequency (14 Hz) are higher than during alert performance. (2) In most subjects, 4-6 Hz theta EEG activity begins to increase, and gamma band activity above 35 Hz begins to decrease, about 10 s before presentations of undetected targets, while before detected targets, 4-6 Hz amplitude decreases and gamma band amplitude increases. Both these amplitude differences last 15-20 s and occur in parallel with event-related cycles in target detection probability. In the same periods, alpha and sleep-spindle frequency amplitudes also show prominent 15-20 s cycles, but these are not phase locked to performance cycles. (3) A second or longer after undetected targets, amplitude at intermediate (10-25 Hz) frequencies decreases briefly, while detected targets are followed by a transient amplitude increase in the same latency and frequency range.},
  note = {PubMed query source: Scott Makeig}
}

@article{Makeig19968871108,
  title = {Effects of voluntary movements on early auditory brain responses.},
  author = {Makeig, S and Müller, MM and Rockstroh, B},
  journal = {Experimental brain research},
  year = {1996},
  doi = {10.1007/BF00229149},
  pmid = {8871108},
  url = {https://pubmed.ncbi.nlm.nih.gov/8871108/},
  abstract = {It has not been clear whether or not early information processing in the human auditory cortex is altered by voluntary movements. We report a movement-related, complex event-related potential consisting of relatively long-lasting amplitude and phase perturbations induced in an ongoing auditory steady-state response (SSR) by brief self-paced finger movements. Our results suggest that processing in the auditory cortex during the first 50-100 ms after stimulus delivery is affected before, during, and after voluntary movements, beginning with a 1- to 2-ms delay in the SSR wave form starting 1-2 s before the movement.},
  note = {PubMed query source: Scott Makeig}
}

@article{Steinschneider19968873972,
  title = {Appearance of neurofilament subunit epitopes correlates with electrophysiological maturation in cortical embryonic neurons cocultured with mature astrocytes.},
  author = {Steinschneider, R and Delmas, P and Nedelec, J and Gola, M and Bernard, D and Boucraut, J},
  journal = {Brain research. Developmental brain research},
  year = {1996},
  doi = {10.1016/0165-3806(96)00052-1},
  pmid = {8873972},
  url = {https://pubmed.ncbi.nlm.nih.gov/8873972/},
  abstract = {E14 rat cortical neurons which have almost no glial progenitors were cocultured with a homogeneous population of mature type 1 astrocytes at a 4/1 ratio in serum free medium. Maturation of neurons was evaluated using a set of well characterized antibodies and two new monoclonal antibodies (MN2E4 and MN3H6) raised against various neurofilament subunits and whole-cell patch clamp experiments. We observed that this coculture method leads to a well-timed and very homogeneous neuronal maturation and that sequential appearance of neurofilament subunits in developing neurons correlates with the electrophysiological maturation. This sequence, early expression of the 68 kDa neurofilament subunit and late appearance of the 200 kDa neurofilament subunit, occurs in normal brain development, which validates this culture model as a useful tool for studying neuronal maturation and differentiation. MN2E4 staining (non-phosphorylated 200 kDa cytoskeletal protein antibody) appeared just before the neurons became excitable. It could thus be used as a functional neuronal marker. MN3H6 staining (phosphorylated 160-200 kDa neurofilament subunit antibody) appeared just after the neurons made synaptic contacts and generated synaptically driven spike bursts. This finding indicated that some phosphorylated epitopes of 160-200 kDa neurofilament followed synaptogenesis. These processes may play a key role in stabilizing the synapses to achieve a functional neuronal network.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Kowalski19957753390,
  title = {Emergence of a synaptic neuronal network within primary striatal cultures seeded in serum-free medium.},
  author = {Kowalski, C and Crest, M and Vuillet, J and Pin, T and Gola, M and Nieoullon, A},
  journal = {Neuroscience},
  year = {1995},
  doi = {10.1016/0306-4522(94)00453-c},
  pmid = {7753390},
  url = {https://pubmed.ncbi.nlm.nih.gov/7753390/},
  abstract = {In order to investigate the basic cellular mechanisms involved in neuronal interactions within the striatum, we prepared a primary striatal cell culture from rat fetal brain in chemically defined medium. Using morphological and whole-cell recording methods, we observed that an intensive neuritic elongation with a progressive build up of a sodium-dependent electrogenesis occurred during the first week of culture. Morphologically mature synapses began to develop after 10 days in vitro. By this time, most of the neurons (82 +/- 9%) received spontaneously synaptic potentials, which led them to fire (71 +/- 11%). The spontaneous firing was prevented by cadmium (200 microM) and tetrodotoxin (5 microM), which suggested that a Ca(2+)-dependent release of neurotransmitters was involved in the synaptic activation. We further obtained evidence that GABA, and to a lesser extent acetylcholine, contributed to these spontaneous synaptic potentials. At 15 days in vitro, it was possible to observe up to four synaptic contacts on a given dendrite. By this time, whole-cell recordings performed on pairs of neurons showed that the mature neurons were interconnected by excitatory synapses. As the number of synapses increased, the striatal neurons gradually formed a large network in which spontaneous activity developed, which tended to be organized into synchronized bursting patterns.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Makeig19958742454,
  title = {Changes in alertness are a principal component of variance in the EEG spectrum.},
  author = {Makeig, S and Jung, TP},
  journal = {Neuroreport},
  year = {1995},
  pmid = {8742454},
  url = {https://pubmed.ncbi.nlm.nih.gov/8742454/},
  abstract = {Minute-scale fluctuations in the normalized EEG log spectrum, when correlated with concurrent changes in level of performance on a sustained auditory detection task, showed that a single principal component of EEG spectral variance is linearly related to minute-scale changes in detection performance. The particular EEG frequencies at which this coupling is expressed are similar for most subjects under a range of task conditions, and match those recently reported from analysis of verbal self-reports during drowsiness. The one-dimensional relationship between detection performance and the EEG spectrum confirms quantitatively the intuitive assumption that minute-scale changes in behavioral alertness during drowsiness are predominantly linked to changes in global brain dynamics along a single dimension of psychophysiological arousal.},
  note = {PubMed query source: Scott Makeig}
}

@article{LarabaDjebari19947806508,
  title = {The kaliotoxin family enlarged. Purification, characterization, and precursor nucleotide sequence of KTX2 from Androctonus australis venom.},
  author = {Laraba-Djebari, F and Legros, C and Crest, M and Céard, B and Romi, R and Mansuelle, P and Jacquet, G and van Rietschoten, J and Gola, M and Rochat, H},
  journal = {The Journal of biological chemistry},
  year = {1994},
  pmid = {7806508},
  url = {https://pubmed.ncbi.nlm.nih.gov/7806508/},
  abstract = {Kaliotoxin (KTX) has been originally described as an inhibitor of the intermediate conductance Ca(2+)-activated K+ channel (Crest, M., Jacquet, G., Gola, M., Zerrouk, H., Benslimane, A., Rochat, H., Mansuelle, P., and Martin-Eauclaire, M.-F. (1992) J. Biol. Chem. 267, 1640-1647). However, the radioiodinated 125I-KTX-(1-37) was also able to bind to the dendrotoxin sensitive voltage-dependent K+ channel (Romi, R., Crest, M., Gola, M., Sampieri, F., Jacquet, G., Zerrouk, H., Mansuelle, P., Sorokine, O., Van Dorsselaer, A., Rochat, H., Martin-Eauclaire, M.-F., and Van Rietschoten, J. (1993) J. Biol. Chem. 268, 26302-26309). By following the ability to compete with 125I-KTX-(1-37) for binding to its receptor on rat brain synaptosomes, a new kaliotoxin-like peptide, KTX2, was isolated from Androctonus australis scorpion venom. It is a 37-amino acid residue peptide, and its sequence shares 76% identity with KTX. The differences between the two peptides concern the NH2-terminal region and the residues 31 and 34 located in the region involved in the channel recognition. These differences may explain the 5-fold decrease of the molluscan Ca(2+)-activated K+ channel blockage by KTX2 (kd = 135 nM) as well as of its binding affinity to rat brain synaptosomes (IC50 = 50 pM), compared with KTX. Specific antibodies raised against KTX-(1-37) were not able to recognize KTX2. Using degenerate primers, a 370-base pair cDNA encoding the KTX2 precursor was amplified by polymerase chain reaction from a cDNA library of A. australis venom glands. It encoded a presumed signal peptide of 22 residues followed by the sequence of the mature peptide.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Romi19938253752,
  title = {Synthesis and characterization of kaliotoxin. Is the 26-32 sequence essential for potassium channel recognition?},
  author = {Romi, R and Crest, M and Gola, M and Sampieri, F and Jacquet, G and Zerrouk, H and Mansuelle, P and Sorokine, O and Van Dorsselaer, A and Rochat, H},
  journal = {The Journal of biological chemistry},
  year = {1993},
  pmid = {8253752},
  url = {https://pubmed.ncbi.nlm.nih.gov/8253752/},
  abstract = {Kaliotoxin (KTX), a scorpion toxin characterized as a 37-residue inhibitor of the neuronal high conductance Ca(2+)-activated K+ channels (KCa channels), has been chemically synthetized. Differences were observed between natural toxin and the two peptides, KTX(1-37) and KTX(1-37)-amide. Re-examination of the KTX sequence showed that an extra lysine residue was present at the C-terminal end. The 38-residue synthetic peptide was found identical with natural toxin. All three peptides had comparable activities, with LD50 values of 6-9 pmol/mouse after intracerebroventricular injection, and Kd = 2-8 nM for blockage of the whole cell and unitary molluscan KCa currents. Pairing of the disulfide bonds in synthetic KTX corresponded to that in charybdotoxin and iberiotoxin. A competition assay between 125I-KTX(1-37) and different toxins (KTX, dendrotoxin, charybdotoxin, MCD peptide, and iberiotoxin) for binding to rat brain synaptosomal membranes suggested that KTX interacts also with voltage-gated K+ channels. Shorter peptides, KTX(25-35)-amide and KTX(26-32)-amide, expressed no KTX activity, but were able to compete in binding. They were further shown to antagonize KTX in both its toxicity and blocking activity. The (26-32) sequence of KTX, which is a highly conserved region, may contain a low affinity binding subsite essential for potassium channel recognition.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Crest19902117989,
  title = {Two subtypes of C current in identified Helix neurons.},
  author = {Crest, M and Watanabe, K and Gola, M},
  journal = {Brain research},
  year = {1990},
  doi = {10.1016/0006-8993(90)90986-l},
  pmid = {2117989},
  url = {https://pubmed.ncbi.nlm.nih.gov/2117989/},
  abstract = {Ca-activated K currents (C currents) were identified in various Helix pomatia neurons under voltage-clamp conditions. This comparative study revealed the existence of two C currents: a fast-inactivating current and a non-inactivating current; both had identical gating and pharmacological properties. Inactivation of the C currents was induced by either cell depolarization or short Ca entry.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Chagneux19892743128,
  title = {Voltage-dependent opening of single calcium-activated potassium channels in Helix neurons.},
  author = {Chagneux, H and Ducreux, C and Gola, M},
  journal = {Brain research},
  year = {1989},
  doi = {10.1016/0006-8993(89)90726-9},
  pmid = {2743128},
  url = {https://pubmed.ncbi.nlm.nih.gov/2743128/},
  abstract = {Single Ca-activated K channels (C channels) were identified in cell-attached patches in Helix neurons. The respective effects of membrane potential and calcium on the opening probability Po were separated by using Ca-free filled patch electrodes. C channels were found to be highly voltage-dependent, with an e-fold increase in Po per 15 mV increase in potential. The location of the Po(V) curve on the voltage axis was dependent on the intracellular Ca concentration. These data indicate that C channels provide the cell with a powerful repolarizing mechanism.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Pin19873607451,
  title = {Decreased resting membrane conductance as the proximate cause of burst modulation by an identified interneuron in Helix.},
  author = {Pin, T and Gola, M},
  journal = {Brain research},
  year = {1987},
  doi = {10.1016/0006-8993(87)91454-5},
  pmid = {3607451},
  url = {https://pubmed.ncbi.nlm.nih.gov/3607451/},
  abstract = {The mechanism by which an identified interneuron modulates bursting activity was studied in the mollusc Helix pomatia. Firing of the interneuron was found to enhance endogenous bursting activity by causing a slow, persistent decrease in resting K-conductance, leading to a relative increase in the effectiveness of the burst-generating mechanism.},
  note = {PubMed query source: Mateusz Gola}
}

@article{Danan19826896712,
  title = {Presence of 25-hydroxyvitamin D3 and 1,25-dihydroxyvitamin D3 24-hydroxylase in vitamin D target cells of rat yolk sac.},
  author = {Danan, JL and Delorme, AC and Mathieu, H},
  journal = {The Journal of biological chemistry},
  year = {1982},
  pmid = {6896712},
  url = {https://pubmed.ncbi.nlm.nih.gov/6896712/},
  abstract = {In the pregnant rat, the yolk sac, which possesses true placental functions, is a vitamin D target organ. We tested its ability to hydroxylate 25-hydroxy- and 1,25-dihydroxyvitamin D3 (25-OHD3 and 1,25-(OH)2D3). 24,25-Dihydroxy- and 1,24,25-trihydroxyvitamin D3 were produced by rat yolk sac homogenates incubated with tritiated 25-OHD3 and 1,25-(OH)2D3. Rat yolk sac homogenates also formed small amounts of 25,26-dihydroxyvitamin D3. These newly synthesized metabolites were isolated and identified by Sephadex LH-20 chromatography, high performance liquid chromatography, and periodate cleavage. Yolk sac 25-OHD3- and 1,25-(OH)2D3-24-hydroxylases were present in mitochondria and were of a mixed function oxidase nature. They were detected in the yolk sac as early as day 12 in the embryonic period and until the end of gestation. No hydroxylation occurred in maternal liver, amnion, fetal brain, or skin homogenates. Both 24-hydroxylases were detected in pure isolated rat yolk sac endodermal cells. This may be of physiological importance, since they are the 1,25-(OH)2D3 target cells in the yolk sac. Injection of 1,25-(OH)2[3H]D3 into rat yolk sac vitelline veins strongly suggested that the yolk sac vitelline veins strongly suggested that the yolk sac produced 1,24,25-(OH)3D3 in vivo. We conclude that the yolk sac and more precisely its endodermal cells may help to control vitamin D metabolism within the fetoplacental unit.},
  note = {PubMed query source: Arnaud Delorme}
}

@article{Ducreux1977843934,
  title = {Ionic mechanism of Ba2+-induced square-shaped potential waves in molluscan neurons.},
  author = {Ducreux, C and Gola, M},
  journal = {Brain research},
  year = {1977},
  doi = {10.1016/0006-8993(77)90491-7},
  pmid = {843934},
  url = {https://pubmed.ncbi.nlm.nih.gov/843934/},
  note = {PubMed query source: Mateusz Gola}
}