MEG and EEG source localization in beamspace

IEEE Transactions on Bio-medical Engineering
Alberto Rodríguez-RiveraRonald T Wakai

Abstract

Beamspace methods are applied to EEG/MEG source localization problems in this paper. Beamspace processing involves passing the data through a linear transformation that reduces the data dimension prior to applying a desired statistical signal processing algorithm. This process generally reduces the data requirements of the subsequent algorithm. We present one approach for designing beamspace transformations that are optimized to preserve source activity located within a given region of interest and show that substantial reductions in dimension are obtained with negligible signal loss. Beamspace versions of maximum likelihood dipole fitting, MUSIC, and minimum variance beamforming source localization algorithms are presented. The performance improvement offered by the beamspace approach with limited data is demonstrated by bootstrapping somatosensory data to evaluate the variability of the source location estimates obtained with each algorithm. The quantitative benefits of beamspace processing depend on the algorithm, signal to noise ratio, and amount of data. Dramatic performance improvements are obtained in scenarios with low signal to noise ratio and a small number of independent data samples.

References

Jun 1, 1992·IEEE Transactions on Bio-medical Engineering·J C MosherR M Leahy
Jan 1, 1985·Electroencephalography and Clinical Neurophysiology·M Scherg, D Von Cramon
Apr 28, 1989·Science·R Hari, O V Lounasmaa
Sep 1, 1997·IEEE Transactions on Bio-medical Engineering·B D Van VeenA Suzuki
Sep 3, 1999·Physics in Medicine and Biology·J Gross, A A Ioannides
Jul 10, 2001·IEEE Transactions on Bio-medical Engineering·K SekiharaY Miyashita
Sep 24, 2004·Brain Topography·Samu TauluJuha Simola
Oct 20, 2004·IEEE Transactions on Bio-medical Engineering·Kensuke SekiharaAlec Marantz
Nov 13, 2004·IEEE Transactions on Bio-medical Engineering·Boris V BaryshnikovRonald T Wakai
Jul 13, 2006·IEEE Transactions on Bio-medical Engineering·Sarang S DalalSrikantan S Nagarajan

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Citations

Jun 2, 2012·Computational and Mathematical Methods in Medicine·Cristiano Micheli, Christoph Braun
Nov 11, 2008·Clinical Neurophysiology : Official Journal of the International Federation of Clinical Neurophysiology·Marco CongedoChristian Jutten
Oct 11, 2013·IEEE Transactions on Bio-medical Engineering·Maryam RavanGary Hasey
Sep 1, 2006·IEEE Transactions on Bio-medical Engineering·Tulaya LimpitiRonald T Wakai
Aug 22, 2008·IEEE Transactions on Bio-medical Engineering·Tolga Esat OzkurtRobert J Sclabassi
Aug 19, 2006·IEEE Transactions on Bio-medical Engineering·Marco Congedo
Jun 17, 2009·IEEE Transactions on Bio-medical Engineering·Tolga Esat OzkurtRobert J Sclabassi
Mar 11, 2009·IEEE Transactions on Bio-medical Engineering·Kaushik Majumdar
Dec 25, 2015·IEEE Transactions on Bio-medical Engineering·Jinyin ZhangAnto Bagić
Aug 20, 2014·NeuroImage·Ashwini OswalGareth Barnes
Mar 13, 2018·Journal of Neural Engineering·Kensuke SekiharaSrikantan S Nagarajan
Apr 6, 2006·Physics in Medicine and Biology·M CongedoA Lécuyer
Apr 13, 2021·Frontiers in Neural Circuits·Abolfazl Ziaeemehr, Alireza Valizadeh

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