Stochastic maximum likelihood mean and cross-spectrum structure modelling in neuro-magnetic source estimation

Authors:
Raoul P. P. P. Grasman;Hilde M. Huizenga;Lourens J. Waldorp;Peter C. M. Molenaar;Koen B. E. Böcker
Affiliations:
Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018WB Amsterdam, The Netherlands;Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018WB Amsterdam, The Netherlands;Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018WB Amsterdam, The Netherlands;Department of Psychology, University of Amsterdam, Roetersstraat 15, 1018WB Amsterdam, The Netherlands;Department of Psychopharmacology, Utrecht University, P.O. Box 80082, 3508TB Utrecht, The Netherlands
Venue:
Digital Signal Processing
Year:
2005

Citing 4
Cited 0

Brain and cognition

Foundations of cognitive science
Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems

Theoretical Neuroscience: Computational and Mathematical Modeling of Neural Systems
Optimal array signal processing in the presence of coherent wavefronts

ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05
Analysis of subspace fitting and ML techniques for parameterestimation from sensor array data

IEEE Transactions on Signal Processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

In [R.P.P.P. Grasman et al., Frequency domain simultaneous source and source coherence estimation with an application to MEG, IEEE Trans. Biomed. Eng. 51 (1) (2004) 45-55] we proposed to analyze cross-spectrum matrices obtained from electro- or magnetoencephalographic (EEG/MEG) signals, to obtain estimates of the EEG/MEG sources and their coherence. In this paper we extend this method in two ways. First, by modelling such interactions as linear filters, and second, by taking the mean of the signals across different trials into account. To obtain estimates we propose a stochastic maximum likelihood (SML) method, and obtain the concentrated likelihood that includes the trial means.