Mining event-related brain dynamics.
- Authors
- Makeig, Scott; Debener, Stefan; Onton, Julie; Delorme, Arnaud
- Year
- 2004
- Journal
- Trends in cognitive sciences
- PMID
- 15120678
- DOI
- 10.1016/j.tics.2004.03.008
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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