title: EEG changes accompanying learned regulation of 12-Hz EEG activity.
abstract: We analyzed 15 sessions of 64-channel electroencephalographic (EEG) data recorded from a highly trained subject during sessions in which he attempted to regulate power at 12 Hz over his left- and right-central scalp to control the altitude of a cursor moving toward target boxes placed at the top-, middle-, or bottom-right of a computer screen. We used infomax independent component analysis (ICA) to decompose 64-channel EEG data from trials in which the subject successfully up- or down-regulated the measured EEG signals. Applying time-frequency analysis to the time courses of activity of several of the resulting 64 independent EEG components revealed that successful regulation of the measured activity was accompanied by extensive, asymmetrical changes in power and coherence, at both nearby and distant frequencies, in several parts of cortex. A more complete understanding of these phenomena could help to explain the nature and locus of learned regulation of EEG rhythms and might also suggest ways to further optimize the performance of brain-computer interfaces.
authors.affiliation: Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California at San Diego, La Jolla 92093-0961, USA. arno@salk.edu
authors.forename: Arnaud
authors.initials: A
authors.lastname: Delorme
authors.forename: Scott
authors.initials: S
authors.lastname: Makeig
mesh_terms: D000222:Adaptation, Physiological / Q000502:physiology; D000465:Algorithms; D001676:Biofeedback, Psychology / Q000379:methods; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005246:Feedback; D006801:Humans; D007858:Learning / Q000502:physiology*; D008297:Male; D010775:Photic Stimulation / Q000379:methods; D025341:Principal Component Analysis; D012815:Signal Processing, Computer-Assisted; D013647:Task Performance and Analysis; D014584:User-Computer Interface; D014796:Visual Perception / Q000502:physiology*