How to cite EEGLAB
Primary EEGLAB citation
Delorme A & Makeig S (2004) EEGLAB: an open-source toolbox for analysis of single-trial EEG dynamics, Journal of Neuroscience Methods 134:9-21. PDF.
Includes details of EEGLAB ICA and time/frequency methods. Please cite this paper to reference EEGLAB in publications. Browse its 14,000+ citations in Google Scholar. Consult these papers, plus the extensive EEGLAB tutorial and help facilities, for instructions and examples of their use.
Third-party analysis of EEGLAB popularity
Mohammad Fayaz (2023) The bibliometric analysis of EEGLAB software in the Web of Science indexed articles, Neuroscience Informatics, Volume 4, Issue 1, ISSN 2772-5286, https://www.sciencedirect.com/science/article/pii/S2772528623000390. This article analyzes usage of EEGLAB compared to other EEG software packages, and shows it is still the most popular EEG software in 2023.
Hanke, M., & Halchenko, Y. O. (2011). Neuroscience Runs on GNU/Linux. Frontiers in neuroinformatics, 5, 8. https://doi.org/10.3389/fninf.2011.00008. This article (footnotes) shows that EEGLAB is the most popular EEG software.
EEGLAB ICA methods introductions
Makeig S, Debener S, Onton J, Delorme A (2004) Mining event-related brain dynamics. Trends in Cognitive Science 8:204-210. PDF.
Summarizes benefits and pitfalls of combining ICA, time/frequency analysis, and ERP-image visualization.
Delorme A, Palmer J, Oostenveld R, Onton J, Makeig S (2012) Independent EEG components are dipolar. PLOS One, 7(2). PDF.
Demonstrates that the more mutual information a linear transform removes from multi-channel EEG data, the more the resulting components are compatible with an origin in a small patch of locally synchronous cortex.
Delorme, A., Sejnowski, T., Makeig, S. Improved rejection of artifacts from EEG data using high-order
statistics and independent component analysis. Neuroimage. 2007; 34, 1443-1449. PDF.
This paper demonstrates the advantages of using ICA for rejecting EEG artifacts.
Onton J, Delorme, A., Makeig, S. Frontal midline EEG dynamics during working memory. NeuroImage. 2005;27, 341-356. PDF.
An early application of ICA to the study of time/frequency dynamics, showing the value of ICA spatial filtering for resolving brain sources, etc.
S. Makeig, A.J. Bell, T-P. Jung, and T.J. Sejnowski, Independent component analysis of electroencephalographic data, In: D. Touretzky, M. Mozer and M. Hasselmo (Eds). Advances in Neural Information Processing Systems 8:145-151, MIT Press, Cambridge, MA 1996. PDF.
The first paper demonstrating the benefits of applying ICA decomposition to EEG data.
EEGLAB time/frequency methods introductions
Makeig S, Debener S, Onton J, Delorme A (2004) Mining event-related brain dynamics. Trends in Cognitive Science 8:204-210. PDF.
Summarizes benefits and pitfalls of combining ICA, time/frequency analysis, and ERP-image visualization.
Makeig, S, Auditory event-related dynamics of the EEG spectrum and effects of exposure to tones, Electroencephalogr clin Neurophysiol, 86:283-293, 1993. PDF.
The first paper demonstrating the event-related spectral perturbation (ERSP) measure.
Subset of EEGLAB plug-in references
Delorme A, Mullen T, Kothe C, Akalin Acar Z, Bigdely-Shamlo N, Vankov A, Makeig S. (2011) EEGLAB, SIFT, NFT, BCILAB, and ERICA: New tools for advanced EEG processing. Computat Intelligence Neurosci 2011:130714, doi: 10.1155/2011/130714. HTML.
Pernet CR, Chauveauy N, Gaspar C, Rousselet GA (2011) LIMO EEG: A toolbox for hierarchical linear modeling of electroencephalographic data. Computat Intelligence Neurosci 2011:831409, doi: 10.1155/2011/831409. HTML.
Pion-Tonachini, L., Kreutz-Delgado, K., Makeig, S. ICLabel: An automated electroencephalographic independent component classifier, dataset, and website. NeuroImage 198:181-197, 2019. PDF.
Zeynep Akalin Acar & Scott Makeig, Neuroelectromagnetic Forward Head Modeling Toolbox J Neurosci Meth, doi:10.1016/jneumeth.2010.04.031. PDF.
Martinez-Cancino, R., Heng, J., Delorme, A., Kreutz-Delgado, K., Sotero, R.C. Makeig, S. Measuring transient phase-amplitude coupling using local mutual information. NeuroImage, 2018. PDF.