• Publications
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EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis
  • A. Delorme, S. Makeig
  • Computer Science, Materials Science
  • Journal of Neuroscience Methods
  • 15 March 2004
We have developed a toolbox and graphic user interface, EEGLAB, running under the crossplatform MATLAB environment (The Mathworks, Inc.) for processing collections of single-trial and/or averaged EEGExpand
Mining event-related brain dynamics
A new approach combines independent component analysis (ICA), time/frequency analysis, and trial-by-trial visualization that measures EEG source dynamics without requiring an explicit head model. Expand
Enhanced detection of artifacts in EEG data using higher-order statistics and independent component analysis
Simulations demonstrate that ICA decomposition, here tested using three popular ICA algorithms, Infomax, SOBI, and FastICA, can allow more sensitive automated detection of small non-brain artifacts than applying the same detection methods directly to the scalp channel data. Expand
Independent EEG Sources Are Dipolar
Though these and other commonly-used decomposition methods returned many similar components, across 18 ICA/BSS algorithms mean dipolarity varied linearly with both MIR and with PMI remaining between the resulting component time courses, a result compatible with an interpretation of many maximally independent EEG components as being volume-conducted projections of partially-synchronous local cortical field activity within single compact cortical domains. Expand
EEGLAB, SIFT, NFT, BCILAB, and ERICA: New Tools for Advanced EEG Processing
We describe a set of complementary EEG data collection and processing tools recently developed at the Swartz Center for Computational Neuroscience (SCCN) that connect to and extend the EEGLABExpand
Lost in thoughts: Neural markers of low alertness during mind wandering
To the knowledge, this experiment is one of the first neuro-imaging studies that relies purely on subjects' introspective judgment, and shows that such judgment may be used to contrast different brain activity patterns. Expand
Spike-based strategies for rapid processing
It is argued that Rank Order Coding is not only very efficient, but also easy to implement in biological hardware: neurons can be made sensitive to the order of activation of their inputs by including a feed-forward shunting inhibition mechanism that progressively desensitizes the neuronal population during a wave of afferent activity. Expand
Frontal midline EEG dynamics during working memory
We show that during visual working memory, the electroencephalographic (EEG) process producing 5-7 Hz frontal midline theta (fmtheta) activity exhibits multiple spectral modes involving at leastExpand
Electroencephalographic Brain Dynamics Following Manually Responded Visual Targets
The observed event-related changes in local field activities, within and between cortical areas, may serve to modulate the strength of spike-based communication between cortex areas to update attention, expectancy, memory, and motor preparation during and after target recognition and speeded responding. Expand
Face identification using one spike per neuron: resistance to image degradations
It is shown, by using a learning rule involving spike timing dependant plasticity, that neuronal maps in the output layer can be trained to recognize natural photographs of faces and was also remarkably resistant to image noise and reductions in contrast. Expand