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Dynamic filtering of static dipoles in magnetoencephalography

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Sorrentino, Alberto, Johansen, Adam M., Aston, John A. D., Nichols, Thomas E. and Kendall, W. S. (2013) Dynamic filtering of static dipoles in magnetoencephalography. Annals of Applied Statistics, Volume 7 (Number 2). pp. 955-988. doi:10.1214/12-AOAS611

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Official URL: http://dx.doi.org/10.1214/12-AOAS611

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Abstract

We consider the problem of estimating neural activity from measurements
of the magnetic fields recorded by magnetoencephalography. We exploit
the temporal structure of the problem and model the neural current as a
collection of evolving current dipoles, which appear and disappear, but whose
locations are constant throughout their lifetime. This fully reflects the physiological
interpretation of the model.
In order to conduct inference under this proposed model, it was necessary
to develop an algorithm based around state-of-the-art sequential Monte
Carlo methods employing carefully designed importance distributions. Previous
work employed a bootstrap filter and an artificial dynamic structure
where dipoles performed a random walk in space, yielding nonphysical artefacts
in the reconstructions; such artefacts are not observed when using the
proposed model. The algorithm is validated with simulated data, in which
it provided an average localisation error which is approximately half that of
the bootstrap filter. An application to complex real data derived from a somatosensory
experiment is presented. Assessment of model fit via marginal
likelihood showed a clear preference for the proposed model and the associated
reconstructions show better localisation.

Item Type: Journal Article
Subjects: Q Science > QA Mathematics
R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry
Divisions: Faculty of Science > Statistics
Faculty of Science > WMG (Formerly the Warwick Manufacturing Group)
Library of Congress Subject Headings (LCSH): Magnetoencephalography, Neurons, Magnetic dipoles , Monte Carlo method, Mathematical physics
Journal or Publication Title: Annals of Applied Statistics
Publisher: Insitute of Mathematical Statistics
ISSN: 1932-6157
Official Date: June 2013
Dates:
DateEvent
June 2013Published
Volume: Volume 7
Number: Number 2
Number of Pages: 34
Page Range: pp. 955-988
DOI: 10.1214/12-AOAS611
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Restricted or Subscription Access
Copyright Holders: IMS
Funder: Marie Curie Intra-European Fellowship (IEF), Seventh Framework Programme (European Commission) (FP7), Engineering and Physical Sciences Research Council (EPSRC), Higher Education Funding Council for England (HEFCE), Medical Research Council (Great Britain) (MRC)
Grant number: EP/I017984/1, EP/H016856/1 (EPSRC) ; G0900908 (MRC)
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