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Links to lecture slides
Mining EEG Brain Dynamics I (Scott Makeig)
EEGLAB overview (Arnaud Delorme)
Independent Component Analysis (Scott Makeig)
Time-frequency methods (John Iversen)
New Tools: MEEG Analysis (John Iversen)
Which ICs are which? IC classification by machine learning (Luca Pion-Tonachini)
Automated source classification and online ICA (Luca Pion-Tonachini)
Independent Component Clustering (Scott Makeig)
Understanding Hierarchical Linear Models and their application to EEG (Cyril Pernet)
Whole brain analyses and multiple comparison corrections (Cyril Pernet)
Introduction to the EEGLAB STUDY and STUDY designs (Arnaud Delorme)
Real-world MoBI and BCIs (Tzyy-Ping Jung)
Modeling and Visualizing Source Connectivity (Intro Blitz) (Tim Mullen)
Modeling Source Resolved Information Flow 1:SIFT-I (Tim Mullen)
Modeling Source Resolved Information Flow 1:SIFT-I Practicum (Tim Mullen)
Modeling Source Resolved Information Flow 1:SIFT-II (Tim Mullen)
Performing independent component cluster analysis in EEGLAB (Arnaud Delorme)
New EEG Tools and Measures(John Iversen)
Practicum Performing ERP Analysis with BCILAB (Christian Kothe)
EEG Nonstationarity and AMICA (Shawn Hsu)
Mining Event-Related Brain Dynamics II (Scott Makeig)
Phase/Amplitude Coupling (Ramon Martinez-Cancino)
Data import, preprocessing and plotting (Julie Onton)
Performing ICA decomposition & visualization (Julie Onton)
Analyzing multimodal data: MoBILAB, etc. (Alejandro Ojeda)