11th EEGLAB Workshop
NCTU, Taiwan September 8 – September 10, 2010 See also the Chinese workshop website
Maps and Directions
Venue of Conference
National Chiao Tung University
Microelectronics and Information Systems Research Center
|09:30~10:30||Invited Presentation 1：|
Scott Makeig - Mining event-related brain dynamics (PDF)
|10:30~11:20||Invited Presentation 2：|
Arnaud Delorme – ICA component reliability
|11:40~12:30||Invited Presentation 3：|
Julie Onton – EEG spectral modulations during emotional imagery (PDF)
|13:50~14:40||Invited Presentation 4：|
Tzyy-Ping Jung - Independent components and modulators of electroencephalographic data in sustained-attention tasks (PDF)
|14:40~15:30||Invited Presentation 5：|
Klaus Gramann - Mobile brain/body imaging of natural cognition (PDF)
|15:50~16:40||Invited Presentation 6：|
Jeng-Ren Duann - Functional connectivity delineates distinct roles of the inferior frontal cortex and pre-supplementary motor area in stop signal inhibition.
|16:40~17:30||Arnaud Delorme – EEGLAB overview (PDF)|
|September 9 （Thursday）|
|09:00~11:00||Workshop 1：EEGLAB methods I|
|11:10~12:30||Workshop 2：EEGLAB methods I|
|13:30~15:10||Workshop 3：EEGLAB methods II|
|15:20~16:30||Workshop 4：EEGLAB methods II|
|September 10 （Friday）|
|09:00~11:00||Workshop 5：EEGLAB methods III|
|11:10~12:30||Workshop 6：EEGLAB methods IV|
|13:30~15:20||Workshop 7：EEGLAB methods V|
|15:20~17:00||Group research continued|
|17:00~18:00||Group research reports and discussion|
MATLAB and matrix introductory reading material
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 constrains, 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.
After opening the MATLAB desktop, select menu item “Help Demos” and run the following demos. Note that while the demo is running, you can retype the text (or copy it) to the main MATLAB window:
- Mathematics - Basic Matrix Operations
- Mathematics - Matrix manipulations
- Graphics - 2-D Plots
- Programming - Manipulating Multidimentional arrays
- Programming - Structures
In the Help Content, read and practice at least the following sections:
- Getting Started - Matrices and Arrays - Matrices and Magic squares
- Getting Started - Matrices and Arrays - Expressions
- Getting Started - Matrices and Arrays - Working with Matrices
- Getting Started - Graphics - Basic plotting functions
- Getting Started - Programming - Flow Control
- Getting Started - Programming - Other data structures
- Getting Started - Programming - Scripts and Functions
Each section or demo (if read thoroughly) should take you about 10 minutes, for a total here of about 2 hours. We encourage you to watch these demos and read these sections over several days.
IMPORTANT NOTE: A large portion of the workshop will be dedicated to writing EEGLAB scripts, so not being able to understand MATLAB syntax will result in you missing out on a large portion of the workshop.
Relevant publications using ICA/EEGLAB
- Delorme, A., Makeig, S. EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J Neurosci Methods. 2004; Mar 15; 134(1):9-21.
- Makeig, S., Debener, S., Onton, J., Delorme, A. Mining event-related brain dynamics. Trends Cogn Sci. 2004; May; 8(5):204-10.
- Jung, TP, Makeig, S, Westerfield, M, Townsend, J, Courchesne, E, Sejnowski, TJ. Analysis and visualization of single-trial event-related potentials. Human Brain Mapping. 2001; 14(3), 166-185.
- 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.
- Delorme, A., Palmer, J. Oostenveld, R., Onton, J., Makeig, S. Comparing results of algorithms implementing blind source separation of EEG data. unpublished manuscript.
- Onton J, Delorme, A., Makeig, S. Frontal midline EEG dynamics during working memory. NeuroImage. 2005;27, 341-356
- Onton J, Makeig S. High-frequency broadband modulations of electroencephalographic spectra. Frontiers in Neuroscience 159: 99-120. 2009.
- Onton J, Makeig S. Information-based modeling of event-related brain dynamics.Prog Brain Res. 159: 99-120. 2006.
Material to Download
If you are using your own laptop, please install the latest version of EEGLAB:
Latest EEGLAB version here: http://sccn.ucsd.edu/eeglab/install.html
Tutorial scripts Download scripts for certain tutorial sessions with scripting components.
Tutorial slides Download the PDFs of the tutorial lectures here.
EEGLAB dataset: single subject This is a sample dataset for use in the first few tutorial sessions. This is a dataset from the Sternberg experiment (same as used for the full STUDY).
EEGLAB STUDY with 13 subjects (2.3 GB) This is a VERY large file and may fail the first few times you try. Make sure you have a fast and reliable internet connection before attempting this download.
NFT: Neuroelectromagnetic Forward Head Modeling Toolbox (11 MB) Download the NFT plugin software.
NFT: Neuroelectromagnetic Forward Head Modeling demo data (2.3 GB) This is also a VERY large file and may fail the first few times you try. Make sure you have a fast and reliable internet connection before attempting this download.
Tim Mullen’s connectivity toolbox and sample data. Will be available soon.
You will also be able to download all presented material from this site during and after the workshop, so don’t panic if you can’t download it before the workshop starts.