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A fast solution to robust minimum variance beamformer and application to simultaneous MEG and local field potential

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  • H.R. Mohseni, University of Oxford
  • ,
  • P.P. Smith, University of Oxford
  • ,
  • Morten L. Kringelbach
  • M.W. Woolrich, University of Oxford
  • ,
  • T.Z. Aziz, John Radcliffe Hospital
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.
Original languageEnglish
Title of host publicationICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Number of pages4
Publication year1 Jan 2011
Publication statusPublished - 1 Jan 2011

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