DocumentCode :
1242651
Title :
Model selection in spatio-temporal electromagnetic source analysis
Author :
Waldorp, Lourens J. ; Huizenga, Hilde M. ; Nehorai, Arye ; Grasman, Raoul P P P ; Molenaar, Peter C M
Author_Institution :
Dept. of Psychol., Univ. of Amsterdam, Netherlands
Volume :
52
Issue :
3
fYear :
2005
fDate :
3/1/2005 12:00:00 AM
Firstpage :
414
Lastpage :
420
Abstract :
Several methods [model selection procedures (MSPs)] to determine the number of sources in electroencephalogram (EEG) and magnetoencphalogram (MEG) data have previously been investigated in an instantaneous analysis. In this paper, these MSPs are extended to a spatio-temporal analysis if possible. It is seen that the residual variance (RV) tends to overestimate the number of sources. The Akaike information criterion (AIC) and the Wald test on amplitudes (WA) and the Wald test on locations (WL) have the highest probabilities of selecting the correct number of sources. The WA has the advantage that it offers the opportunity to test which source is active at which time sample.
Keywords :
electroencephalography; magnetoencephalography; medical signal processing; spatiotemporal phenomena; Akaike information criterion; Wald test; electroencephalogram; magnetoencephalogram; model selection; residual variance; spatio-temporal electromagnetic source analysis; Bayesian methods; Brain modeling; Covariance matrix; Electroencephalography; Electromagnetic analysis; Electromagnetic modeling; Estimation error; Magnetic analysis; Psychology; Testing; Akaike criterion; Bayesian criterion; EEG; MEG; model order selection; source localization; testing source activity; Algorithms; Animals; Brain Mapping; Computer Simulation; Diagnosis, Computer-Assisted; Electroencephalography; Humans; Magnetoencephalography; Models, Neurological; Models, Statistical;
fLanguage :
English
Journal_Title :
Biomedical Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
0018-9294
Type :
jour
DOI :
10.1109/TBME.2004.842982
Filename :
1396381
Link To Document :
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