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 language | English |
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Pages (from-to) | 422-426 |
Number of pages | 5 |
Journal | IEEE Signal Processing Letters |
Volume | 24 |
Issue number | 4 |
Early online date | 14 Feb 2017 |
DOIs | |
Publication status | Published - Apr 2017 |
Keywords
- Bayes methods
- M/EEG measurements
- source localization
- sparsity
ASJC Scopus subject areas
- Signal Processing
- Electrical and Electronic Engineering
- Applied Mathematics