EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis.

By Arnaud Delorme, Scott Makeig. Journal of Neuroscience Methods, 2004

23,269 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Signal Processing

View Paper: https://www.semanticscholar.org/paper/76ad159a2887b008e5a7335d124c148c13e65465

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Citations in the corpus

EEG Source Imaging: A Practical Review of the Analysis Steps (2019, methodology): “A comprehensive overview of different academic software applications can be found in a special issue of the Journal Computational Intelligence and Neuroscience (30), where programs such as BrainStorm (31), EEGLAB (32), FieldTrip (33), NUTMEG (34), SPM (35), andCartool (29) are described.”
Event-related EEG time-frequency analysis: an overview of measures and an analysis of early gamma band phase locking in schizophrenia. (2008, methodology): “pendent waveforms from the scalp EEG data using independent component analysis, followed by assessment of MS coherence and/or phase coherence between independent components.(10) Because of the contamination of electrodes or sensors by volume-conducted signals, the absolute value of phase coherence b”
Mental Training Affects Distribution of Limited Brain Resources (2007, neutral): “EEGLAB [26] and Matlab (Mathworks, http:// www.”
Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis (2007, methodology): “The EEGLAB routines that implement these detection methods use this strategy (Delorme and Makeig, 2004).”
Robust artifactual independent component classification for BCI practitioners (2014, methodology): “We provide the ready-to-use artifact classiﬁer to the community as an open-source EEGLAB plug-in called MARA (multiple artifact rejection algorithm).”
Independent EEG Sources Are Dipolar (2012, methodology): “Data were analyzed by custom MATLAB scripts built on the open source EEGLAB toolbox [48].”
A Review on Machine Learning for EEG Signal Processing in Bioengineering (2020, background): “[22] Traditionally, Mohammad-Parsa Hosseini is with the Bioengineering Department, Santa Clara University, Santa Clara, CA 95053 USA and also with the AI Research, Silicon Valley, CA USA (e-mail: mhosseini@scu.edu).”
Removing artefacts from TMS-EEG recordings using independent component analysis: Importance for assessing prefrontal and motor cortex network properties (2014, methodology): “Analysis of EEG data was performed using EEGLAB (Delorme and Makeig, 2004), field trip (Oostenveld et al., 2011) and custom scripts all on the MATLAB platform (R2013a, The Mathworks, USA).”
Investigating the efficacy of neurofeedback training for expediting expertise and excellence in sport (2015, positive): “Processing of EEG data recorded during the test phase of the experiment was conducted with EEGLab software (Delorme & Makeig, 2004) using the following procedure: First, datafiles were resampled (256 Hz), filtered (1e50 Hz) and referenced to the average mastoid.”
ERPLAB: an open-source toolbox for the analysis of event-related potentials (2014, methodology): “A convenient GUI is an important aspect of an ERP analysis package.”
EEGNet: a compact convolutional neural network for EEG-based brain–computer interfaces (2016, methodology): “The data were referenced to linked mastoids, bandpass filtered, using an FIR filter implemented in EEGLAB [53], between 0.”
Mass univariate analysis of event-related brain potentials/fields I: A critical tutorial review (2011, methodology): “The software is compatible with the EEGLAB toolbox (Delorme & Makeig, 2004) as well as the ERPLAB toolbox (http://erpinfo.org/ erplab).”