TY - JOUR
T1 - Stochastic maximum likelihood mean and cross-spectrum structure modelling in neuro-magnetic source estimation
AU - Grasman, Raoul P.P.P.
AU - Huizenga, Hilde M.
AU - Waldorp, Lourens J.
AU - Molenaar, Peter C.M.
AU - Böcker, Koen B.E.
N1 - Funding Information:
The Netherlands Organization for Scientific Research (NWO) is gratefully acknowledged for funding this project. This research was conducted while R. Grasman (527-25-014), L. Waldorp (527-25-013), and K. Böcker (527-25-015) were supported by a grant of the NWO foundation for Behavioral and Educational Sciences of this organization awarded to H.M. Huizenga, P.C.M. Molenaar, L.J. Kenemans, and J.C. de Munck. We thank Dr. Conor V. Dolan for proofreading.
PY - 2005/1
Y1 - 2005/1
N2 - 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.
AB - 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.
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U2 - 10.1016/j.dsp.2004.09.003
DO - 10.1016/j.dsp.2004.09.003
M3 - Article
AN - SCOPUS:10444242011
SN - 1051-2004
VL - 15
SP - 56
EP - 72
JO - Digital Signal Processing: A Review Journal
JF - Digital Signal Processing: A Review Journal
IS - 1
ER -