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June 2013 Dynamic filtering of static dipoles in magnetoencephalography
Alberto Sorrentino, Adam M. Johansen, John A. D. Aston, Thomas E. Nichols, Wilfrid S. Kendall
Ann. Appl. Stat. 7(2): 955-988 (June 2013). DOI: 10.1214/12-AOAS611

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.

Citation

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Alberto Sorrentino. Adam M. Johansen. John A. D. Aston. Thomas E. Nichols. Wilfrid S. Kendall. "Dynamic filtering of static dipoles in magnetoencephalography." Ann. Appl. Stat. 7 (2) 955 - 988, June 2013. https://doi.org/10.1214/12-AOAS611

Information

Published: June 2013
First available in Project Euclid: 27 June 2013

zbMATH: 1288.62168
MathSciNet: MR3113497
Digital Object Identifier: 10.1214/12-AOAS611

Rights: Copyright © 2013 Institute of Mathematical Statistics

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Vol.7 • No. 2 • June 2013
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