NDLI: Maximum likelihood estimation with a parametric noise covariance model for instantaneous and spatio-temporal electromagnetic source analysis

Content Provider	IEEE Xplore Digital Library
Author	Waldorp, L.J. Huizenga, H.M. Dolan, C.V. Grasman, R.P.P.P. Molenaar, P.C.M.
Copyright Year	2000
Description	Author affiliation: Dept. of Psychol., Amsterdam Univ., Netherlands (Waldorp, L.J.)
Abstract	In instantaneous encephalogram or magnetoencephalogram (EEG/MEG) source analysis, ordinary least squares estimation (OLS) requires that the spatial noise is homoscedastic and uncorrelated over sensors. In spatio-temporal analysis OLS also requires that the noise is homoscedastic and uncorrelated in time (over samples). Generally, these assumptions are violated and, as a consequence, OLS can give rise to inaccuracies in the estimates of location and moment parameters of sources underlying the EEG/MEG. To improve these estimates of the sources, the generalized least squares (GLS) was developed, which uses the spatial or spatio-temporal noise covariances. In GLS these noise covariances are estimated from trial variation around the mean. Therefore, GLS requires many trials to accurately estimate the spatial noise covariances and thus the source parameters. Alternatively, with maximum likelihood (ML) the spatial or spatio-temporal noise covariances can be modeled parametrically. Here, only the model parameters describing the noise covariances need to be estimated. Consequently, fewer trials are required to obtain accurate noise covariances and consequently accurate source parameters. In this paper ML estimation for spatio-temporal analysis is derived, and it is shown that the noise and source parameters can be estimated separately. Furthermore, the likelihood ratio function is proposed to estimate the spatial or spatio-temporal noise covariance model parameters, which can also be used to test whether the model is adequate.
Starting Page	266
Ending Page	270
File Size	513814
Page Count	5
File Format	PDF
ISBN	0780363396
DOI	10.1109/SAM.2000.878011
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-03-17
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Maximum likelihood estimation Covariance matrix Least squares approximation Parameter estimation Magnetic analysis Magnetic separation Electroencephalography Brain modeling Electromagnetic modeling Psychology
Content Type	Text
Resource Type	Article

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