Skull Conductivity Estimation for EEG Source Localization

被引：3
|
作者：
Costa, Facundo [1 ]
Batatia, Hadj [1 ]
Oberlin, Thomas [1 ]
Tourneret, Jean-Yves [1 ]
机构：
[1] Univ Toulouse, INP ENSEEIHT, F-31071 Toulouse, France
来源：
IEEE SIGNAL PROCESSING LETTERS | 2017年 / 24卷 / 04期
关键词：
Bayes methods; M/EEG measurements; source localization; sparsity; IN-VIVO; TISSUE CONDUCTIVITY; MODEL ERRORS; MEG; HEAD; BRAIN;
D O I：
10.1109/LSP.2017.2669101
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
Areliable 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.
引用
收藏
页码：422 / 426
页数：5
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