EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. 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. First developed on Matlab 5.3 under Linux, EEGLAB runs on Matlab v5 and higher under Linux, Unix, Windows, and Mac OS X (Matlab 7+ recommended).

References in zbMATH (referenced in 32 articles )

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  1. Schillinger, Frieder L.; De Smedt, Bert; Grabner, Roland H.: When errors count: an EEG study on numerical error monitoring under performance pressure (2016)
  2. Hinault, Thomas; Dufau, Stéphane; Lemaire, Patrick: Sequential modulations of poorer-strategy effects during strategy execution: an event-related potential study in arithmetic (2014)
  3. Li, Zhaohui; Ouyang, Gaoxiang; Yao, Li; Li, Xiaoli: Estimating the correlation between bursty spike trains and local field potentials (2014)
  4. Moewes, Christian; Kruse, Rudolf; Sabel, Bernhard A.: Analysis of dynamic brain networks using VAR models (2013)
  5. Daly, Ian; Nasuto, Slawomir J.; Warwick, Kevin: Brain computer interface control via functional connectivity dynamics (2012)
  6. Wang, Juan; Li, Xiaoli; Lu, Chengbiao; Voss, Logan J.; Barnard, John P.M.; Sleigh, Jamie W.: Characteristics of evoked potential multiple EEG recordings in patients with chronic pain by means of parallel factor analysis (2012)
  7. Aguera, Pierre-Emmanuel; Jerbi, Karim; Caclin, Anne; Bertrand, Olivier: ELAN: A software package for analysis and visualization of MEG, EEG, and LFP signals (2011)
  8. Christodoulou, Eleni G.; Sakkalis, Vangelis; Tsiaras, Vassilis; Tollis, Ioannis G.: BrainNetVis: an open-access tool to effectively quantify and visualize brain networks (2011)
  9. Degenhart, Alan D.; Kelly, John W.; Ashmore, Robin C.; Collinger, Jennifer L.; Tyler-Kabara, Elizabeth C.; Weber, Douglas J.; Wang, Wei: Craniux: a labview-based modular software framework for brain-machine interface research (2011)
  10. Delorme, Arnaud; Mullen, Tim; Kothe, Christian; Acar, Zeynep Akalin; Bigdely-Shamlo, Nima; Vankov, Andrey; Makeig, Scott: EEGLAB, SIFT, NFT, BCILAB, and ERICA: new tools for advanced EEG processing (2011)
  11. Eichele, Tom; Rachakonda, Srinivas; Brakedal, Brage; Eikeland, Rune; Calhoun, Vince D.: EEGIFT: group independent component analysis for event-related EEG data (2011)
  12. Leclercq, Yves; Schrouff, Jessica; Noirhomme, Quentin; Maquet, Pierre; Phillips, Christophe: fMRI artefact rejection and sleep scoring toolbox (2011)
  13. Oostenveld, Robert; Fries, Pascal; Maris, Eric; Schoffelen, Jan-Mathijs: Fieldtrip: open source software for advanced analysis of MEG, EEG, and invasive electrophysiological data (2011)
  14. Pernet, Cyril R.; Chauveau, Nicolas; Gaspar, Carl; Rousselet, Guillaume A.: LIMO EEG: a toolbox for hierarchical linear modeling of electroencephalographic data (2011)
  15. Peyk, Peter; De Cesarei, Andrea; Junghöfer, Markus: Electromagnetoencephalography software: overview and integration with other EEG/MEG toolboxes (2011)
  16. Tadel, François; Baillet, Sylvain; Mosher, John C.; Pantazis, Dimitrios; Leahy, Richard M.: Brainstorm: a user-friendly application for MEG/EEG analysis (2011)
  17. Tian, Xing; Poeppel, David; Huber, David E.: Topotoolbox: using sensor topography to calculate psychologically meaningful measures from event-related EEG/MEG (2011)
  18. Gao, Junfeng; Lin, Pan; Yang, Yong; Wang, Pei; Zheng, Chongxun: Real-time removal of ocular artifacts from EEG based on independent component analysis and manifold learning (2010)
  19. Ventouras, Erricos M.; Ktonas, Periklis Y.; Tsekou, Hara; Paparrigopoulos, Thomas; Kalatzis, Ioannis; Soldatos, Constantin R.: Independent component analysis for source localization of EEG sleep spindle components (2010)
  20. Naeem, Muhammad; Brunner, Clemens; Pfurtscheller, Gert: Dimensionality reduction and channel selection of motor imagery electroencephalographic data (2009)

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