An empirical Bayesian solution to the source reconstruction problem in EEG

NeuroImage

Volumn 24, Issue 4, 2005, Pages 997-1011

  Phillips, Christophe ^a   Mattout, Jeremie ^b   Rugg, Michael D ^c   Maquet, Pierre ^a   Friston, Karl J ^b  

^a UNIVERSITY OF LIÈGE   (Belgium)

^b UNIVERSITY COLLEGE LONDON   (United Kingdom)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

Distributed solution; EEG; Expectation maximisation (EM) procedure; Restricted maximum likelihood (ReML) solution; Source reconstruction

Indexed keywords

ACCURACY; ALGORITHM; ARTICLE; BAYES THEOREM; CORRELATION ANALYSIS; COVARIANCE; DATA ANALYSIS; ELECTROENCEPHALOGRAM; EMPIRICISM; EVOKED SOMATOSENSORY RESPONSE; MATHEMATICAL COMPUTING; MATHEMATICAL MODEL; NEUROIMAGING; NOISE; PARAMETER; PRIORITY JOURNAL; PROBABILITY; TECHNIQUE;

ALGORITHMS; ARTIFACTS; BAYES THEOREM; ELECTROENCEPHALOGRAPHY; EVOKED POTENTIALS, SOMATOSENSORY; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; LIKELIHOOD FUNCTIONS; MAGNETIC RESONANCE IMAGING;

EID: 12844268707     PISSN: 10538119     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2004.10.030     Document Type: Article

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