Population-level inferences for distributed MEG source localization under multiple constraints: Application to face-evoked fields

Henson, R.N., Mattout, J., Singh, Krish Devi ORCID: https://orcid.org/0000-0002-3094-2475, Barnes, G.R., Hillebrand, A. and Friston, K. 2007. Population-level inferences for distributed MEG source localization under multiple constraints: Application to face-evoked fields. Neuroimage 38 (3) , pp. 422-438. 10.1016/j.neuroimage.2007.07.026

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Abstract

We address some key issues entailed by population inference about responses evoked in distributed brain systems using magnetoencephalography (MEG). In particular, we look at model selection issues at the within-subject level and feature selection issues at the between-subject level, using responses evoked by intact and scrambled faces around 170 ms (M170). We compared the face validity of subject-specific forward models and their summary statistics in terms of how estimated responses reproduced over subjects. At the within-subject level, we focused on the use of multiple constraints, or priors, for inverting distributed source models. We used restricted maximum likelihood (ReML) estimates of prior covariance components (in both sensor and source space) and show that their relative importance is conserved over subjects. At the between-subject level, we used standard anatomical normalization methods to create posterior probability maps that furnish inference about regionally specific population responses. We used these to compare different summary statistics, namely; (i) whether to test for differences between condition-specific source estimates, or whether to test the source estimate of differences between conditions, and (ii) whether to accommodate differences in source orientation by using signed or unsigned (absolute) estimates of source activity.

Item Type:	Article
Status:	Published
Schools:	Psychology Neuroscience and Mental Health Research Institute (NMHRI)
Subjects:	R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Uncontrolled Keywords:	Magnetoencephalography; Inverse problem; Restricted maximum likelihood
Publisher:	Elsevier
ISSN:	1053-8119
Last Modified:	20 Oct 2022 09:39
URI:	https://orca.cardiff.ac.uk/id/eprint/32708

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