EEGLAB

EEGLAB
Name	EEGLAB
Developer	Swartz Center for Computational Neuroscience; originally by Scott Makeig; maintained by Arnaud Delorme and collaborators
Released	1997
Programming language	MATLAB
Operating system	Linux, macOS, Microsoft Windows
Genre	Electroencephalography analysis, Signal processing
License	GNU GPL

EEGLAB EEGLAB is a widely used open-source software environment for processing electroencephalography (EEG) data within the MATLAB ecosystem. It provides graphical and scripting interfaces designed for researchers in cognitive neuroscience, clinical neurophysiology, and brain–computer interface communities, integrating methods from signal processing, statistical analysis, and blind source separation.

Overview

EEGLAB supports import, visualization, preprocessing, and analysis of EEG datasets collected using systems such as BioSemi, Electrical Geodesics Inc., Neuroscan, Brain Products, and ANT Neuro. Researchers often combine EEGLAB with toolboxes like FieldTrip, BCILAB, MNE, SPM, and Psychtoolbox for experiment control and multimodal analysis. Institutions that have contributed to or used EEGLAB include the Swartz Center for Computational Neuroscience, Neuroinformatics Research Group, Massachusetts Institute of Technology, University of California, San Diego, University of Oxford, and Max Planck Society laboratories.

Features and Functionality

EEGLAB offers functions for data import, channel montage management, event and epoch handling, artifact rejection, time–frequency decomposition, and statistical testing. Visualization tools provide topographic maps, scalp plots, ERP image plots, and time–frequency spectrograms suitable for presentations at venues like the Society for Neuroscience, Organization for Human Brain Mapping, and Cognitive Neuroscience Society. Integration points allow connectivity analyses compatible with measures developed in groups at Karolinska Institutet, Johns Hopkins University, University College London, and University of Cambridge.

History and Development

EEGLAB was initiated in the late 1990s by researchers associated with the Swartz Center for Computational Neuroscience and led by Scott Makeig. Development has involved contributors from entities such as the National Institutes of Health, Defense Advanced Research Projects Agency, National Science Foundation, and collaborative projects with teams at Stanford University, University of California, Berkeley, Harvard University, Yale University, and Princeton University. Major milestones align with advances presented at conferences like Neural Information Processing Systems, International Conference on Learning Representations, and symposiums hosted by the Royal Society.

Algorithms and Data Processing

Core algorithms include independent component analysis variants such as Infomax ICA, FastICA, and adaptive methods influenced by research from Johns Hopkins University Applied Physics Laboratory and groups at New York University. EEGLAB implements filtering, epoching, baseline correction, channel interpolation, and artifact subspace reconstruction approaches originating from studies at University of Queensland, Monash University, and University of Melbourne. Time–frequency decomposition uses wavelet transforms and multitaper methods comparable to implementations from Columbia University, Brown University, and Duke University laboratories. Statistical testing pipelines draw from nonparametric permutation frameworks promoted by researchers at University of Oxford, University of Cambridge, and ETH Zurich.

Toolboxes and Extensions

A rich ecosystem of plug-ins and extensions enhances EEGLAB, including toolboxes developed by teams at UC San Diego, Centre National de la Recherche Scientifique, Inserm, Karolinska Institutet, and RIKEN. Notable integrations include ADJUST artifact detection, ICLabel automated component classification, ERPLAB event-related potential analysis, and SIFT connectivity modeling. Community repositories host contributions from universities like University of Minnesota, McGill University, University of Washington, University of Toronto, and Ohio State University, facilitating workflows for groups presenting at IEEE Engineering in Medicine and Biology Society and European Brain and Behaviour Society meetings.

Applications and Use Cases

EEGLAB is applied in basic and clinical research addressing topics studied at institutions such as Massachusetts General Hospital, Cleveland Clinic, Mayo Clinic, and Charité – Universitätsmedizin Berlin. Use cases include sleep research in collaboration with Brigham and Women's Hospital, cognitive workload studies at Carnegie Mellon University, pediatric neurodevelopmental investigations at University of Pennsylvania, and epilepsy source localization akin to work at Rambam Health Care Campus. It serves brain–computer interface projects at University of Tübingen, neurofeedback studies connected to University of Zurich, and pharmacological EEG assessments performed at Imperial College London.

Licensing and Availability

EEGLAB is distributed under the GNU General Public License and is available for use on major platforms supported by MathWorks. Educational courses at Coursera partner institutions and workshops at Cold Spring Harbor Laboratory, European Neuroscience Institute, and the Allen Institute for Brain Science often include EEGLAB training. Ongoing maintenance and community support are provided through mailing lists, workshops, and contributions from research groups at Swartz Center for Computational Neuroscience and partner laboratories.

Category:Neuroscience software