title: Model selection in spatio-temporal electromagnetic source analysis.
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.
authors.affiliation: Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018 WB Amsterdam, The Netherlands. waldorp@psy.uva.nl
authors.forename: Lourens J
authors.initials: LJ
authors.lastname: Waldorp
authors.forename: Hilde M
authors.initials: HM
authors.lastname: Huizenga
authors.forename: Arye
authors.initials: A
authors.lastname: Nehorai
authors.forename: Raoul P P P
authors.initials: RP
authors.lastname: Grasman
authors.forename: Peter C M
authors.initials: PC
authors.lastname: Molenaar
mesh_terms: D000465:Algorithms; D000818:Animals; D001931:Brain Mapping / Q000379:methods*; D003198:Computer Simulation; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D004569:Electroencephalography / Q000379:methods*; D006801:Humans; D015225:Magnetoencephalography / Q000379:methods*; D008959:Models, Neurological; D015233:Models, Statistical