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PubMed · 15120678

Mining event-related brain dynamics.

Scott Makeig·Stefan Debener·Julie Onton·Arnaud Delorme
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Abstract

This article provides a new, more comprehensive view of event-related brain dynamics founded on an information-based approach to modeling electroencephalographic (EEG) dynamics. Most EEG research focuses either on peaks 'evoked' in average event-related potentials (ERPs) or on changes 'induced' in the EEG power spectrum by experimental events. Although these measures are nearly complementary, they do not fully model the event-related dynamics in the data, and cannot isolate the signals of the contributing cortical areas. We propose that many ERPs and other EEG features are better viewed as time/frequency perturbations of underlying field potential processes. The 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.

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Action PotentialsBrainBrain MappingElectroencephalographyEvoked PotentialsHumansImage Processing, Computer-AssistedMagnetoencephalographyModels, NeurologicalReproducibility of ResultsJournal ArticleResearch Support, Non-U.S. Gov'tReview

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Scott Makeig, Stefan Debener, Julie Onton, Arnaud Delorme. 2004. Mining event-related brain dynamics.. https://doi.org/10.1016/j.tics.2004.03.008

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