A general Bayesian treatment for MEG source reconstruction incorporating lead field uncertainty

López, J D, Penny, W D ORCID: https://orcid.org/0000-0001-9064-1191, Espinosa, J J and Barnes, G R (2012) A general Bayesian treatment for MEG source reconstruction incorporating lead field uncertainty. NeuroImage, 60 (2). pp. 1194-1204. ISSN 1053-8119

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There is uncertainty introduced when a cortical surface based model derived from an anatomical MRI is used to reconstruct neural activity with MEG data. This is a specific case of a problem with uncertainty in parameters on which M/EEG lead fields depend non-linearly. Here we present a general mathematical treatment of any such problem with a particular focus on co-registration. We use a Metropolis search followed by Bayesian Model Averaging over multiple sparse prior source inversions with different headlocation/orientation parameters. Based on MEG data alone we can locate the cortex to within 4mm at empirically realistic signal to noise ratios. We also show that this process gives improved posterior distributions on the estimated current distributions, and can be extended to make inference on the locations of local maxima by providing confidence intervals for each source.

Item Type: Article
Additional Information: Copyright © 2012 Elsevier Inc. All rights reserved.
Uncontrolled Keywords: bayes theorem,magnetoencephalography,uncertainty,journal article,research support, non-u.s. gov't
Faculty \ School: Faculty of Social Sciences > School of Psychology
UEA Research Groups: Faculty of Social Sciences > Research Centres > Centre for Behavioural and Experimental Social Sciences
Depositing User: Pure Connector
Date Deposited: 19 Aug 2017 05:06
Last Modified: 20 Apr 2023 00:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/64589
DOI: 10.1016/j.neuroimage.2012.01.077

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