Model selection in spatio-temporal electromagnetic source analysis.

Lourens J Waldorp; Hilde M Huizenga; Arye Nehorai; Raoul P P P Grasman; Peter C M Molenaar

doi:10.1109/tbme.2004.842982

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Model selection in spatio-temporal electromagnetic source analysis.

Lourens J Waldorp·Hilde M Huizenga·Arye Nehorai·Raoul P P P Grasman·Peter C M Molenaar

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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.

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Algorithms Animals Brain Mapping Computer Simulation Diagnosis, Computer-Assisted Electroencephalography Humans Magnetoencephalography Models, Neurological Models, Statistical Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't

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Lourens J Waldorp, Hilde M Huizenga, Arye Nehorai, Raoul P P P Grasman, Peter C M Molenaar. 2005. Model selection in spatio-temporal electromagnetic source analysis.. https://doi.org/10.1109/tbme.2004.842982

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