Virtual depth-electrode measurement using MEG eigenspace beamformer

K. Sekihara, D. Poeppel, Y. Miyashita

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We have developed a method that can estimate the time course of a neural activity at a predetermined location with a high signal-to-noise ratio. Using this method, an MEG sensor array can perform like a virtual depth electrode in vivo. The developed method consists of two steps: the first step estimating the orientation of a neural source and the second step estimating its activity time course. The second step uses the eigenspace beamformer, which is known to give the signal-to-noise ratio higher than that from the conventional minimum-variance beamformer.

Original languageEnglish (US)
Title of host publicationAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
PublisherIEEE
Pages464
Number of pages1
ISBN (Print)0780356756
StatePublished - 1999
EventProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS) - Atlanta, GA, USA
Duration: Oct 13 1999Oct 16 1999

Publication series

NameAnnual International Conference of the IEEE Engineering in Medicine and Biology - Proceedings
Volume1
ISSN (Print)0589-1019

Other

OtherProceedings of the 1999 IEEE Engineering in Medicine and Biology 21st Annual Conference and the 1999 Fall Meeting of the Biomedical Engineering Society (1st Joint BMES / EMBS)
CityAtlanta, GA, USA
Period10/13/9910/16/99

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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