Skull Conductivity Estimation for EEG Source Localization

Facundo Costa, Hadj Batatia, Thomas Oberlin, Jean-Yves Tourneret

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

A reliable leadfield matrix is needed to solve the magnetoencephalography/electroencephalography (M/EEG) source localization problem. The computation of this matrix requires several physical parameters, including the conductivity of the tissues that compose the subject's head. Since it is not precisely known, we modify a recent Bayesian algorithm to estimate the skull conductivity jointly with the brain activity directly from the M/EEG measurements. Synthetic and real data are used to compare our technique with two optimization algorithms, showing that the proposed method is able to provide results of similar or better quality with the advantage of being applicable in a more general case.

Original languageEnglish
Pages (from-to)422-426
Number of pages5
JournalIEEE Signal Processing Letters
Volume24
Issue number4
Early online date14 Feb 2017
DOIs
Publication statusPublished - Apr 2017

Keywords

  • Bayes methods
  • M/EEG measurements
  • source localization
  • sparsity

ASJC Scopus subject areas

  • Signal Processing
  • Electrical and Electronic Engineering
  • Applied Mathematics

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