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Optimising beamformer regions of interest analysis.

Oswal, A; Litvak, V; Brown, P; Woolrich, M; Barnes, G; (2014) Optimising beamformer regions of interest analysis. Neuroimage , 102 pp. 945-954. 10.1016/j.neuroimage.2014.08.019. Green open access

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Abstract

Beamforming is a spatial filtering based source reconstruction method for EEG and MEG that allows the estimation of neuronal activity at a particular location within the brain. The computation of the location specific filter depends solely on an estimate of the data covariance matrix and on the forward model. Increasing the number of M/EEG sensors, increases the quantity of data required for accurate covariance matrix estimation. Often however we have a prior hypothesis about the site of, or the signal of interest. Here we show how this prior specification, in combination with optimal estimations of data dimensionality, can give enhanced beamformer performance for relatively short data segments. Specifically we show how temporal (Bayesian Principal Component Analysis) and spatial (lead field projection) methods can be combined to produce improvements in source estimation over and above employing the approaches individually.

Type: Article
Title: Optimising beamformer regions of interest analysis.
Open access status: An open access version is available from UCL Discovery
DOI: 10.1016/j.neuroimage.2014.08.019
Publisher version: http://dx.doi.org/10.1016/j.neuroimage.2014.08.019
Language: English
Additional information: © 2014 The Authors. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/3.0/)
Keywords: Bayesian PCA, Beamforming, Regions of Interest
UCL classification: UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology
UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Imaging Neuroscience
URI: https://discovery.ucl.ac.uk/id/eprint/1437906
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