Name
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. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1109/TBME.2004.842982 | IEEE transactions on bio-medical engineering |
Keywords | DocType | Volume |
magnetoencephalogram,source localization,model order selection,electroencephalogram,meg,model selection,electroencephalography,spatio-temporal electromagnetic source analysis,medical signal processing,spatiotemporal phenomena,bayesian criterion,testing source activity,residual variance,magnetoencephalography,wald test,akaike criterion,eeg,akaike information criterion | Journal | 52 |
Issue | ISSN | Citations |
3 | 0018-9294 | 3 |
PageRank | References | Authors |
0.48 | 5 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lourens J. Waldorp | 1 | 128 | 20.11 |
| Hilde M. Huizenga | 2 | 3 | 0.48 |
| Arye Nehorai | 3 | 12 | 2.53 |
| Raoul P. P. P. Grasman | 4 | 61 | 9.64 |
| Peter C. M. Molenaar | 5 | 107 | 19.15 |