The online EEGLAB workshop
This page comprises materials for and videos from different EEGLAB Workshops held at the San Diego Supercomputer Center on the campus of the University of California San Diego (UCSD), La Jolla, California, plus more recently recorded talks and short Youtube tutorial videos. Note that the wiki pages for EEGLAB workshops also contain the slides of the presentations.
List of Youtube Tutorial Videos
EEGLAB introduction (2019, Delorme)
- Part 1: Why EEGLAB
- Part 2: The origin of the EEG signal
- Part 3: Source resolved EEG brain dynamics
- Part 4: EEGLAB history and usage statistics
- Part 5: Single subject processing pipeline
- Part 6: Multi subject analysis and scripting
Preprocessing data in EEGLAB (2018, Delorme)
- Part 1: How to import raw data
- Part 2: How to import events and channel locations
- Part 3: Rereferencing and resampling
- Part 4: Filtering
- Part 5: Visualizing data and looking for artifacts
- Part 6: Removing bad channels
- Part 7: Removing bad data segments
Independent component analysis (2020, Delorme)
- Part 1: What is ICA?
- Part 2: How does Infomax ICA work?
- Part 3: ICA applied to EEG data
- Part 4: Removing ICA component artifacts in EEG data
- Part 5: Source localization of ICA components
- Part 6: Reproducibility of ICA decompositions
- Part 7: Running ICA in EEGLAB and visualizing components
- Part 8: Removing Artifactual Components in EEGLAB
- Part 9: Automatically detecting ICA component classes
- Part 10: Looking at brain components
- Part 11: Common misconceptions about ICA and conclusion
Time-Frequency Analysis of EEG Time Series (2020, Delorme)
Robust statistics applied to EEG data (2020, Delorme)
- Part 1: Basic inferential statistics
- Part 2: Increasing robustness
- Part 3: The bootstrap approach
- Part 4: Bootstrap vs. permutation
- Part 5: Correction for multiple comparisons
General Linear Model of EEG using EEGLAB/LIMO (2020, Delorme)
Preprocessing Muse data in EEGLAB (2017, Delorme)
- Part 1: Acquiring data
- Part 2: Artifact rejection
- Part 3: Analysis of multiple data files
- Part 4: Statistical analysis
EEGLAB 2016 workshop at UCSD
Videos of the workshop talks are available for streaming through the links below. The talk videos are more recent than those from the 2010 workshop below although their video quality tends to be lower and the 2010 workshop videos were also better formatted. Some 2010 & 2016 presentations were given by different researchers. It is therefore worthwhile to compare the 2010 and 2016 versions.
- Mining Event-Related Brain-Dynamics by Scott Makeig
- Independent Component Analysis of Electrophysiological Data by Scott Makeig
- Time-Frequency Measures by John Iversen
- Introduction to hierarchical GLM Statistics and Bootstrap by Cyril Pernet
- Source Localization: The EEG Forward and Inverse Problem by Zeynep Akalin Acar
- BCILAB Intro: Building and Testing a Simple BCI Model by Christian Kothe
- SIFT Intro: Building and Visualizing Source Connectivity by Tim Mullen
- EEGLAB Overview by Arnaud Delorme
- Data Import/Preprocessing and Basic Plotting by Julie Onton
- Performing ICA and ICA Visualization by Julie Onton
- Evaluating Independent Components by Luca Pion-Tonachini (ICLabel)
- Introduction to the EEGLAB STUDY and Study Design by Arnaud Delorme
EEGLAB 2010 workshop at UCSD
Videos of the workshop talks are available for streaming through the links below. The video web pages will also contain relevant questions and links to further information. The talk slides are available for download in PDF format through links below. Individual users or classes may use the videos, slides, and further links to learn or teach how to use EEGLAB, to review the workshop, and/or to prepare for a future workshop. We appreciate any feedback or suggestions for building the Online EEGLAB Workshop site (email firstname.lastname@example.org).
EEGLAB Signal Overview
EEGLAB Toolbox Overview
EEGLAB Methods for EEG-based functional brain imaging
- Independent Component Analysis (ICA) theory I (Jason Palmer)
- Independent Component Analysis (ICA) theory II (Jason Palmer)
- Time-frequency decomposition (Arnaud Delorme). Youtube version (Part 1, Part 2, Part 3, Part 4, Part 5, Part 6).
- Forward and inverse source modeling (Zeynep Akalin Acar)
Computing across subjects and conditions
- Resampling-based statistics and correcting for multiple comparisons (David Groppe)
- STUDY ICA component clustering (Arnaud Delorme)
Extending EEGLAB with Plug-ins
- Building EEGLAB plugins (Arnaud Delorme)
- The SIFT source information-flow toolbox (Tim Mullen)
- The NFT head modeling toolbox (Zeynep Akalin Acar)
- The BCILAB toolbox for machine learning and EEG classification (Christian Kothe). See also Ten lecture course on contemporary BCI design by Christian Kothe.
- Imaging human agency with Mobile brain/body imaging (MoBI) and the Mobilab toolbox (Scott Makeig)
MATLAB and matrix operations tutorials
If you are new to MATLAB or need a refresher, do not hesitate to consult the material on the Getting started with MATLAB page.
IMPORTANT NOTE: The practical portions of the workshop are largely dedicated to writing EEGLAB MATLAB scripts, so if you are not yet able to understand MATLAB syntax, you will not be able to make good use of these sections.
Relevant publications demonstrating EEGLAB capabilities
You can consult a list of relevant EEGLAB papers here
Material to download
To access the talk slides and videos, use the links in the Program listing above. You may also download and uncompress the anonymized data used in the workshop here. These files are valid for both the 2010 and 2016 workshops.