DocumentCode :
747781
Title :
EEG changes accompanying learned regulation of 12-Hz EEG activity
Author :
Delorme, Arnaud ; Makeig, Scott
Author_Institution :
Inst. for Neural Comput., Univ. of California, San Diego, La Jolla, CA, USA
Volume :
11
Issue :
2
fYear :
2003
fDate :
6/1/2003 12:00:00 AM
Firstpage :
133
Lastpage :
137
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.
Keywords :
electroencephalography; handicapped aids; independent component analysis; medical signal processing; time-frequency analysis; 12 Hz; 64-channel EEG data decomposition; EEG rhythms; brain-computer interfaces performance optimization; cortex; cursor movement control; highly trained subject; independent EEG components; infomax independent component analysis; left-central scalp; right-central scalp; Electrodes; Electroencephalography; Frequency measurement; Independent component analysis; Muscles; Particle measurements; Power measurement; Rhythm; Scalp; Time frequency analysis; Adaptation, Physiological; Algorithms; Biofeedback (Psychology); Brain; Electroencephalography; Feedback; Humans; Learning; Male; Photic Stimulation; Principal Component Analysis; Signal Processing, Computer-Assisted; Task Performance and Analysis; User-Computer Interface; Visual Perception;
fLanguage :
English
Journal_Title :
Neural Systems and Rehabilitation Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1534-4320
Type :
jour
DOI :
10.1109/TNSRE.2003.814428
Filename :
1214702
Link To Document :
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