EEGLAB v12 and earlier plugins

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This page was for downloading plugins for old versions of EEGLAB although some of the documentation below might still be relevant. The download link refer to old versions of plugins though. The most current plugin/extension page is available here.

Data import extensions for EEGLAB

These extensions allow to import various type of data. Although EEGLAB contains native function to import some data formats, these functions support other formats.

  • BIOSIG data import: Import/export data in a wide variety of data formats, developed by Alois Schloegl, the creator of the EDF+ data format. For more information about BIOSIG toolbox from this page.
  • FileIO:: toolbox allowing data import in multiple data formats.
  • CTF data import: Import CTF MEG data. Available from Darren Weber's EEG sourceforge project, this extension imports MEG data (plus concurrent EEG, if any) plus sensor locations and data events from data in the CTF (Vancouver, CA) data format.
  • ANT data import (v1.03): Import data files in the EEP format. Contributed by ANT Software (Netherlands) to import data in their format. Email contact: info@ant-software.nl.
  • BVA data import/export: Import/export files from/to the Brain Vision Software Analyser suite. Contributed by Andreas Widmann of the University of Leipzig (Germany) with Arnaud Delorme.
  • Neuroimaging 4D: Christian Wienbruch of the University of Konstanz (Germany) has an extension available for loading Neuroimaging 4-D data into EEGLAB.
  • TDT data import: Adam Wilson at the NITRO Lab at the University of Wisconsin Madison (USA) offers an extension available for loading Tucker-Davis Technology format data into EEGLAB.
  • NeurOne data import: EEGLAB extension for reading the file format of NeurOne system.

Data processing extensions for EEGLAB

Many other EEGLAB extensions are available for EEGLAB. The list below is not complete, and the methods they make available may have not been assessed by the EEGLAB developers. (We recommend that EEG researchers thoroughly study and consider the basis of any methods they apply to experimental data). To allow us to add new extensions or information to the list below, send us an email at eeglab@sccn.ucsd.edu:

  • DIPFIT2: Dipole modeling of independent data components using a spherical or boundary element head model. Uses functions from the FIELDTRIP toolbox of Robert Oostenveld at the Donders Center, University of Nijmegen. A DIPFIT2 tutorial is available.
  • IIRfilt: Infinite impulse response filtering: Apply short non-linear filters to EEGLAB data. Contributed by Maksyn Pozdin.
  • FMRIB: Remove FMRI-environment artifacts from EEGLAB data. This extension, by Rami Niazy of Cardiff University (Wales, UK), allows removal of scanner-related artifacts from EEG data collected during fMRI scanning. These tools provide a gui for removing FMRI gradient artifacts, detecting QRS complexes from an ECG channel, and removing pulse-related ballistocardiographic (BCG) artifacts from the EEG data. All of the tools can also be used from the Matlab command line, allowing expert users to use them in custom scripts.
  • LORETA: Import/export command line bridge function between EEGLAB and this well-known 'low-resolution' EEG source imaging approach by R.D. Pascual-Marqui. Contributed by Arnaud Delorme.
  • CLUSTSET: Cluster ICs of a single dataset by their residual mutual information. See tutorial here. Contributed by Nima Bigdely Shamlo of SCCN (UCSD, La Jolla)
  • AAR (Automatic Artifact Removal toolbox): This toolbox (web page here), implemented as an EEGLAB extension, aims to integrate several state-of-the-art methods for automatic removal of ocular and muscular artifacts in the electroencephalogram (EEG). Contact is German Gomez Herrero (Tampere, Finland) for details.
  • ADJUST: A completely automatic algorithm that identifies artifact-related Independent Components by combining stereotyped artifact-specific spatial and temporal features. Features are optimized to capture blinks, eye movements and generic discontinuities. Once artifacte-related ICs are identified, they can be simply removed from the data while leaving the activity due to neural sources almost unaffected. Download the extension and tutorial here. Contact mail: ADJUST staff. Contributed by Andrea Mognon and Marco Buiatti.
  • batch_context: The batch_context extension provides an interface for generating data processing pipelines and executing them on multiple EEGLAB data files either locally or on remote compute clusters. The main development source is located at [1]. Email James here.
  • BCILAB: An extensive toolbox by Christian Kothe for building and running online brain-computer interface (BCI) models for a wide variety of purposes (volitional control, cognitive monitoring, neurofeedback, etc.). Extensive documentation and code are available here, and a series of over 60 short video lectures here.
  • BERGEN: Removal of fMRI-related gradient artifacts from simultaneous EEG-fMRI data. The BERGEN extension for EEGLAB provides a GUI with different methods for gradient artifact correction. Contributed by Matthias Moosmann and Emanuel Neto.
  • CIAC (cochlear implant artifact correction): is a semi-automatic ICA-based tool for the correction of electrical artifacts originating from cochlear implants. A validation paper describing CIAC in detail has been published in Hearing Research. More info and download.
  • CORRMAP: Semi-automatic identification of common EEG artifacts based in a template. The CORRMAP extension consists of a set of Matlab functions allowing the identification and clustering of independent components representing common EEG artifacts (eye blinks, other ocular artifacts and heartbeat artifacts) in a large number of datasets (requires STUDY structure). Contributed by Filipa Campos Viola. Download extension and tutorial available here.
  • ERPLAB: The ERPLAB Toolbox is a set of open source Matlab routines for analyzing ERP data that operate as a set of extensions to EEGLAB. The development of ERPLAB Toolbox is being coordinated by Steve Luck and Javier Lopez-Calderon at UC Davis.
  • EYE-EEG: The EYE-EEG Toolbox is an extension for EEGLAB developed by Olaf Dimigen & Ulrich Reinacher in Werner Sommer's Biological Psychology lab at Humboldt University Berlin with the goal of facilitating integrated analyses of electrophysiological and oculomotor data. The extension parses, imports, and synchronizes simultaneously recorded eye tracking data and adds it as extra channels to the EEG. Saccades and fixations can be imported from the eye tracking raw data or detected with a velocity-based algorithm. Eye movements are added as new time-locking events to the existing EEGLAB event structure, allowing easy saccade- and fixation-related EEG analyses in the time and frequency domains (e.g., fixation-related potentials, FRPs). Alternatively, EEG data can be aligned to stimulus onsets and analyzed according to oculomotor behavior (e.g. pupil size, microsaccades) in a given trial. Saccade-related ICA components can be objectively identified based on their covariance with the electrically independent eye tracker.
  • FASTER: implements a fully automated, unsupervised method for processing of high density EEG data. FASTER can be used to process EEGLAB datasets, .set and .bdf files. Includes common features such as data importing, epoching, re-referencing, and grand average creation, as well as automated channel, epoch and artifact rejection based on ICA. FASTER has been peer-reviewed, it is free and the software is open source. If you use FASTER, please reference: Nolan, H., Whelan, R., & Reilly, R.B. Journal of Neuroscience Methods, 192, 152-162, which can be obtained here. Download FASTER here. Contributed by Hugh Nolan and Robert Whelan.
  • FIRfilt: Apply a variety of linear filters to EEGLAB data. Contributed by Andreas Widmann (Leipzig, Germany). Latest version updates are available here. For more information about this extension, check firfilt FAQ.
  • Grandaverage: Perform grand averaging across specified EEGLAB datasets. Contributed by Andreas Widmann of the University of Leipzig (Germany). Download here.
  • LIINC extensions: Cogniscan data import, Linear Discrimination, Generalized Eigenvalue decomposition, Common Spatial Patterns, Peak Fitting, Eye Movement Removal: Paul Sajda and colleagues at the LIINC Lab at Columbia University (New York City) distribute several extensions for use in single-trial response detection. A reference article has been published here. The download link is here.
  • MARA: Automatic identification of artifactual independent components contributed by Irene Winkler and colleagues. MARA is a linear classifier that learns from expert ratings by extracting six features from the spatial, the spectral and the temporal domain. Features were optimized to solve the binary classification problem "reject vs. accept", and should be able to handle eye artifacts, muscular artifacts and loose electrodes equally well. Download the extension and tutorial here.
  • Mass Univariate ERP Toolbox: is a freely available set of MATLAB functions by David Groppe and colleagues for performing mass univariate analyses of event-related brain potentials (ERPs), a noninvasive measure of neural activity popular in cognitive neuroscience. A mass univariate analysis is the analysis of a massive number of simultaneously measured dependent variables via the performance of univariate hypothesis tests (e.g., t-tests). Savvy corrections for multiple comparisons are applied to make spurious findings unlikely while still retaining a useful degree of statistical power. This approach is popular in the fMRI community but has not been commonly used by ERP researchers. Compatible with EEGLAB and ERPLAB. Documentation and downloads here. See also David's lecture on multiple comparisons in the Online EEGLAB Workshop.
  • MPT: A toolbox for Measure Projection Analysis developed by Nima Bigdely-Shamlo at SCCN/UCSD for projecting EEG measures tagged by source location into a common template brain space, testing local spatial measure consistency, and parsing measure-consistent brain areas into measure-separable domains. Attractive 3-D graphics and some support for condition and group statistics are provided. A paper is available.
  • NFT: The Neuroelectromagnetic Forward Head Modeling Toolbox, an elaborate extension by Zeynep Akalin Acar, builds custom Boundary Element Method (BEM) and Finite Element Model (FEM) forward head models from subject MR head images and/or from an MNI template brain model warps to measured electrode positions. Web documentation and a reference paper are available here.
  • PACT: is an EEGLAB extension for computing cross-frequency phase-amplitude coupling developed by Makoto Miyakoshi at SCCN/UCSD, with with documentation here
  • REGICA: An extension by Manousos A. Klados of Aristotle University of Thessaloniki, Greece to remove EOG artifacts by regression performed on ICA components. A semi-simulated dataset that might be used in any artifact rejection study is also available. A paper on the method is here. Email Manousos Klados here.
  • SIFT: The Source Information Flow Toolbox by Tim Mullen computes a wide variety of multivariate effective causal models of source-resolved EEG data. Interactive visualizations and animations of event-related 'information flow' networks are included. Extensive documentation is available here.
  • bioelectromag: The bioelectromagnetism Matlab toolbox is interfaced in this extension to plot average ERPs and to find their minima and maxima. Only a few files from this toolbox are included in this extension.
  • Fieldtrip: The Fieldtrip toolbox may be used an extension to EEGLAB. Some Fieldtrip functions are used within EEGLAB for source localization (DIPFIT) and for computing STUDY statistics.

Other Matlab EEG tools working well with EEGLAB

The tools below may not create new EEGLAB menus. Nevertheless they may be used with EEGLAB.

  • Svarog data format: This web site allows importing Svarog data format. Though this is not an EEGLAB extension, once data and its parameters have been imported into Matlab, they can be imported into EEGLAB link.
  • LOC: Performs approximate localization of electrocorticographic electrode positions from x-ray images, as documented by Kai Miller (University of Washington, Seattle) in this J. Neurosci. Methods paper. The download link is here (27.8 MB)].
  • LIINC extensions: Bilinear Discriminant Component Analysis (BDCA) by Paul Sajda and colleagues at the LIINC Lab at Columbia University (New York City). The download link is here.
  • BESAfit: dipole modeling using BESA3: Computes equivalent dipole locations for independent data components using BESA (old) version 3.0 (Megis Software, Germany) run external to Matlab. Download extension version 1.0 here.
  • Micromed data import: Micromed (Italy) has an extension available for loading their data format into EEGLAB. Contact Cristiano Rizzo for details.

Many other EEGLAB plug-ins may be available from authors' or maintainers' web sites. The (alphabetically sorted) list below is not complete, and the methods they make available may have not been assessed by the EEGLAB developers. (We recommend that EEG researchers thoroughly study and consider the basis of any methods they apply to experimental data). To allow us to add new plug-ins or information to the list below, send an email to us at eeglab@sccn.ucsd.edu: