EEGLAB is an interactive Matlab toolbox for processing continuous and event-related EEG, MEG and other electrophysiological data incorporating independent component analysis (ICA), time/frequency analysis, artifact rejection, event-related statistics, and several useful modes of visualization of the averaged and single-trial data. EEGLAB runs under Linux, Unix, Windows, and Mac OS X.
EEGLAB provides an interactive graphic user interface (GUI) allowing users to flexibly and interactively process their high-density EEG and other dynamic brain data using independent component analysis (ICA) and/or time/frequency analysis (TFA), as well as standard averaging methods. EEGLAB also incorporates extensive tutorial and help windows, plus a command history function that eases users' transition from GUI-based data exploration to building and running batch or custom data analysis scripts. EEGLAB offers a wealth of methods for visualizing and modeling event-related brain dynamics, both at the level of individual EEGLAB 'datasets' and/or across a collection of datasets brought together in an EEGLAB 'studyset.'
For experienced Matlab users, EEGLAB offers a structured programming environment for storing, accessing, measuring, manipulating and visualizing event-related EEG data. For creative research programmers and methods developers, EEGLAB offers an extensible, open-source platform through which they can share new methods with the world research community by publishing EEGLAB 'plug-in' functions that appear automatically in the EEGLAB menu of users who download them. For example, novel EEGLAB plug-ins might be built and released to 'pick peaks' in ERP or time/frequency results, or to perform specialized import/export, data visualization, or inverse source modeling of EEG, MEG, and/or ECOG data.
Graphic user interface
Multiformat data importing
High-density data scrolling
Interactive plotting functions
Semi-automated artifact removal
ICA & time/frequency transforms
Event & channel location handling
Forward/inverse head/source modeling
Defined EEG data structure
Many advanced plug-in/extension toolboxes
Q: Do my dataset independent component (IC) processes account for brain, muscle, eye, line or channel noise, or other activity?
Use the ICLabel tutorial website to learn about and practice classifying ICs. Then download the ICLabel plug-in to automatically classify your dataset ICs. You can also help improve the ICLabel classifier by using the website to classify still un-classified ICs. The ICLabel plug-in should become still more and more accurate the more labels you and others contribute.
Use EEGLAB to work at the EEG source level
EEGLAB features processing source activity isolated using ICA. Scalp electroencephalographic (EEG) electrodes record sums of activity from cortical sources and non-brain processes, making direct interpretation of scalp channel waveforms problematic. As an example, the video above shows a silent 1/10th-speed simulation by Zeynep Akalin Acar and Scott Makeig shows (on the left) two cm-sized, parietal EEG sources expressing simulated alpha band activities (at 9 Hz and 10 Hz respectively), and (on the right) their summed scalp projection. Note the strong difference between the cortical source dynamics (left) and scalp EEG dynamics (right), and the difficulty of determining the nature and locations of the source activities directly from the scalp pattern. To download this animation directly (.mp4, 7MB), right click here.