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 Youtube tutorials. Note that the wiki page for each EEGLAB workshop also contain the slides of the presentations.
Tutorial Videos on Youtube.com
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
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
- Note: EEGLAB now has native support for eLoreta through its DIPFIT plug-in.
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 I by Scott Makeig
- EEGLAB Overview by Arnaud Delorme
- Data Import/Preprocessing and Basic Plotting by Julie Onton
- Independent Component Analysis of Electrophysiological Data by Scott Makeig
- Performing ICA and ICA Visualization by Julie Onton
- Evaluating Independent Components By Luca Pion-Tonachini
- Time-Frequency Measures by John Iversen
- Introduction to hierarchical GLM Statistics and Bootstrap by Cyril Pernet
- Introduction to the EEGLAB STUDY and Study Design by Arnaud Delorme
- 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 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
Getting started using EEGLAB
- Data import and channel analysis (Klaus Gramann) - no video
- Evaluating ICA components (Julie Onton) - no video
- Basic scripting using EEGLAB “history” and the EEG structure (Julie Onton) - no video
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
- STUDY component clustering (Arnaud Delorme)
- The new 'STUDY.design' facility and multi-subject plotting (Arnaud Delorme) - no video
- Advanced uses of 'STUDY.design' statistics (Arnaud Delorme) - no video
Extending EEGLAB with Plug-ins
- Building EEGLAB plug-ins (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.
Matlab and matrix operations tutorials
The EEGLAB graphic interface is built on top of the powerful Matlab scripting language. Enjoying the full capabilities of EEGLAB for building macro commands and performing custom and automated processing requires the ability to manipulate EEGLAB data structures in Matlab. Because of time constraints, we will NOT provide an introduction to the Matlab language. Instead users need to familiarize themselves with Matlab prior to the workshop. Users of Matlab 7: We recommend running the following demos and reading the following help sections.
In the Matlab help, you should perform the first 3 tutorials (Matlab 2018)
- Getting Started with MATLAB
- Language Fundamentals
- Graphics (first section 2-D plot only)
Each section or demo (if read thoroughly) should take you about 40 minutes, for a total here of about 2 hours. We encourage you to read these sections over several days. 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
- Delorme, A., Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods 134:9-21, 2004. This is the EEGLAB reference article.
- Makeig, S., Debener, S., Onton, J., Delorme, A. Mining event-related brain dynamics. Trends Cogn Sci 8:204-10, 2004.
- Jung, TP, Makeig, S, Westerfield, M, Townsend, J, Courchesne, E, Sejnowski, TJ. Analysis and visualization of single-trial event-related potentials. Human Brain Mapping. 14:166-185, 2001.
- Onton J., Delorme, A., Makeig, S. Frontal midline EEG dynamics during working memory. NeuroImage 27:341-356, 2005.
- Delorme, A., Sejnowski, T., Makeig, S. Improved rejection of artifacts from EEG data using high-order statistics and independent component analysis. Neuroimage 34:1443-1449, 2007.
- Akalin Acar, Z., Makeig S, Neuroelectromagnetic forward head modeling toolbox, J Neuroscience Methods, 190(2):258-70, 2010.
- Delorme, A., Kothe, C., Bigdely, N., Vankov, A., Oostenveld, R., Makeig, S. Matlab Tools for BCI Research? In "human-computer interaction and brain-computer interfaces". Editors : Tan, D. and Nijholt, A.. Springer Publishing, 2010.
- Delorme, A., Mullen, T., Kothe, C., Bigdely-Shamlo, N., Akalin, Z., Vankov, A., Makeig, S. EEGLAB, MPT, NetSIFT, NFT, BCILAB, and ERICA: New tools for advanced EEG/MEG processing. Computational Neuroscience, 2011.
- Delorme A, Palmer J, Onton J, Oostenveld R, S Makeig, Independent EEG sources are dipolar. PLoS One i7(2):e30135, 2012.
- Makeig, S., Kothe, C., Mullen, T., Bigdely-Shamlo, N., Zhang, Z., Kreutz-Delgado, K. Evolving signal processing for brain-computer interfaces, Proceedings IEEE 100:1567-1584, 2012.
- Bigdely-Shamlo, N., Mullen, T., Kreutz-Delgado, K., Makeig, S., Measure projection analysis: A probabilistic approach to EEG source comparison and multi-subject inference. NeuroImage 15:287-303, 2013.
- Makeig, S., Gramann, K., Jung, T-P., Sejnowski, T.J., and Poizner, H. Linking brain, mind and behavior. Int J Psychophysiology 73:985-100, 2009.
- Kothe, C. A., Makeig, S., BCILAB: A platform for brain-computer interface development. J Neural Engineering 10(5):056014, 2013.
- Ojeda, A., Bigdely-Shamlo, N., Makeig, S. MoBILAB: An open source toolbox for analysis and visualization of mobile brain/body imaging data. Frontiers Hum Neurosci 5;8:121 2014.
- Artoni, F., Menicucci, D., Delorme, A., Makeig, S., Micera, S. RELICA: A method for estimating the reliability of independent components. NeuroImage 103:391-400, 2014.
- Artoni F, Delorme A, Makeig S. Applying dimension reduction to EEG data by principal component analysis reduces the quality of its subsequent independent component decomposition. NeuroImage 175:176-187. PMID: 29526744, 2018.
- Pion-Tonachini, L., Kreutz-Delgado, K., Makeig, S. ICLabel: An automated electroencephalographic independent component classifier, dataset, and website. NeuroImage 198:181-197, 2019.
- 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, 2019.
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 below. These files are valid for both the 2010 and 2016 workshops.