sccn / eeglab

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and developed at the SCCN/UCSD
https://eeglab.ucsd.edu/
Other
610 stars 246 forks source link
biosignal brain compiled ecg ecog eda eeg eeg-preprocessing eeg-signals-processing eeglab electrophysiology hrv ieeg matlab meg neurophysiology octave source-localization spectral-analysis

GitHub issues Twitter Follow

What is EEGLAB?

EEGLAB is an open source signal processing environment for electrophysiological signals running on Matlab and Octave (command line only for Octave). This folder contains original Matlab functions from the EEGLAB (formerly ICA/EEG) Matlab toolbox, all released under the Gnu public license (see eeglablicence.txt). See the EEGLAB tutorial and reference paper (URLs given below) for more information.

Installing/cloning

Recommended: Download the official EEGLAB release from https://sccn.ucsd.edu/eeglab/download.php

Do not download a ZIP file directly from GIT as it will not contain EEGLAB submodules. Instead clone the reposity while pulling EEGLAB sub-modules.

git clone --recurse-submodules https://github.com/sccn/eeglab.git

If you forgot to clone the submodule, go to the eeglab folder and type

git submodule update --init --recursive --remote
git pull --recurse-submodules

Sub-directories:

To use EEGLAB:

  1. Start Matlab

  2. Use Matlab to navigate to the folder containing EEGLAB

  3. Type "eeglab" at the Matlab command prompt ">>" and press enter

  4. Open the main EEGLAB tutorial page (http://sccn.ucsd.edu/wiki/EEGLAB_Wiki)

  5. Please send feedback and suggestions to: eeglab@sccn.ucsd.edu

In publications, please reference:

Delorme, A., & Makeig, S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. Journal of neuroscience methods, 134(1), 9-21. (See article here)

Compiled version of EEGLAB

If you experience problems, try running EEGLAB as administrator.

Documentation:

EEGLAB documentation is available on the EEGLAB wiki (see http://sccn.ucsd.edu/wiki/EEGLAB_Wiki for more details).