EEGLAB
EEGLAB is a
History
In 1997, a set of data processing functions was first released on the Internet by Scott Makeig in the Computational Neurobiology Laboratory directed by
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EEGLAB was downloaded about 25,000 times from 73 countries worldwide in its first three years (2003–2006) and in 2011 was reported to be the most widely used signal processing environment for processing of EEG data by cognitive neuroscientists (survey results). Its reference paper (Delorme & Makeig, 2004) has received over 12,400 citations (02/2013).
EEGLAB comprises over 380 stand-alone MATLAB functions and over 50,000 lines of code and hosts over 20 user-contributed plug-ins. Significant plug-in toolboxes continue to be written and published by researchers at the Swartz Center, UCSD, and by many other groups. Major plug-ins include:
- DIPFIT, for source localization of ICA component sources of EEG data;
- ERPLAB, for deriving measures from average event-related potentials;
- FASTER, a fully automated, unsupervised method for processing high density EEG data;
- NBT, a toolbox for the computation and integration of neurophysiological biomarkers;
- NFT, for building electrical forward head models from MR images and/or electrode positions;
- SIFT, a source information flow toolbox;
- BCILAB, an extensive environment for building and testing brain–computer interface models;
Hundreds of researchers have contributed directly or indirectly to the software by programming functions or reporting bugs. The current eeglablist email discussion list has over 5,000 members worldwide (2013).
See also
Other open-source toolboxes for neurophysiological signals processing include:
- MNE-Python (Python)
- Neurophysiological Biomarker Toolbox (MatLab)
- NeuroKit (Python)