A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential

In this study, a robust minimum variance beamformer (RMVB) is employed for source reconstruction in simultaneous MEG and local field potential (LFP) measurements. RMVB selects the electrical activity only from a specified volume of the brain while suppressing the rest. To improve imaging we added tw...

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Main Authors: Mohseni, H, Kringelbach, M, Woolrich, M, Smith, P, Aziz, T, IEEE
Format: Journal article
Language:English
Published: 2011
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author Mohseni, H
Kringelbach, M
Woolrich, M
Smith, P
Aziz, T
IEEE
author_facet Mohseni, H
Kringelbach, M
Woolrich, M
Smith, P
Aziz, T
IEEE
author_sort Mohseni, H
collection OXFORD
description In this study, a robust minimum variance beamformer (RMVB) is employed for source reconstruction in simultaneous MEG and local field potential (LFP) measurements. RMVB selects the electrical activity only from a specified volume of the brain while suppressing the rest. To improve imaging we added two more terms to the RMVB: the first term minimises the mean squared error (i.e. maximises the correlation) between the recorded LFP and reconstructed time courses from MEG data, the second term nulls the large inference induced by deep brain stimulation (DBS) device. A solution of this problem, relevant both with and without extra terms, is presented using the Lagrange multiplier method. This solution - if we ignore the new terms - has a simpler secular equation compared to its original solution and therefore is faster. The method is validated using both simulated and real data to show its potential use in practical applications. © 2011 IEEE.
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spelling oxford-uuid:36019a97-7aec-45a6-a83c-aafc7ca48c9a2022-03-26T13:35:10ZA Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field PotentialJournal articlehttp://purl.org/coar/resource_type/c_dcae04bcuuid:36019a97-7aec-45a6-a83c-aafc7ca48c9aEnglishSymplectic Elements at Oxford2011Mohseni, HKringelbach, MWoolrich, MSmith, PAziz, TIEEEIn this study, a robust minimum variance beamformer (RMVB) is employed for source reconstruction in simultaneous MEG and local field potential (LFP) measurements. RMVB selects the electrical activity only from a specified volume of the brain while suppressing the rest. To improve imaging we added two more terms to the RMVB: the first term minimises the mean squared error (i.e. maximises the correlation) between the recorded LFP and reconstructed time courses from MEG data, the second term nulls the large inference induced by deep brain stimulation (DBS) device. A solution of this problem, relevant both with and without extra terms, is presented using the Lagrange multiplier method. This solution - if we ignore the new terms - has a simpler secular equation compared to its original solution and therefore is faster. The method is validated using both simulated and real data to show its potential use in practical applications. © 2011 IEEE.
spellingShingle Mohseni, H
Kringelbach, M
Woolrich, M
Smith, P
Aziz, T
IEEE
A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title_full A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title_fullStr A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title_full_unstemmed A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title_short A Fast Solution to Robust Minimum Variance Beamformer and Application to Simultaneous MEG and Local Field Potential
title_sort fast solution to robust minimum variance beamformer and application to simultaneous meg and local field potential
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