HYPERPARAMETERS ESTIMATION FOR THE BAYESIAN LOCALIZATION OF THE EEG SOURCES WITH TV PRIORS

被引：0

作者：

Lopez, Antonio ^{[1
]}

Cortes, Jesus M. ^{[2
,4
]}

Lopez-Oller, Domingo ^{[3
]}

Molina, Rafael ^{[2
]}

Katsaggelos, Aggelos K. ^{[5
]}

机构：

[1] Univ Granada, Dept Lenguajes & Sistemas Informat, E-18071 Granada, Spain

[2] Univ Granada, Dept Ciencias Computac I.A, E-18071 Granada, Spain

[3] Univ Granada, Dept Teoria Senal, Telemat Comunicac, E-18071 Granada, Spain

[4] Ikerbasque, Biocruces Hlth Res Inst, Basque Fdn Sci, Baracaldo 48903, Spain

[5] Northwestern Univ, Dept Elect Engn & Comp Sci, Evanston, IL 60208 USA

来源：

2012 PROCEEDINGS OF THE 20TH EUROPEAN SIGNAL PROCESSING CONFERENCE (EUSIPCO) | 2012年

关键词：

EEG Source Localization; Bayesian Inference; TV Prior; Variational Methods; Hyperparameters Estimation; RECONSTRUCTION; BRAIN; MEG;

D O I：

暂无

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：

In this work we propose a new Bayesian method for the non-invasive localization of EEG sources. For this problem, most of the existing methods assume that the sources are distributed throughout the brain volume according to smooth 3D patterns. However, this assumption might fail in pathological conditions, such as in an epileptic brain, where it can occur that the neurophysiological generators are localized in a narrow region, highly compacted, what originates abrupt profiles of electrical activity. This new method incorporates a Total Variation (TV) prior which has been used before in image processing for edge detection and applies variational methods to approximate the probability distributions to estimate the unknown parameters and the sources. The procedure is tested and validated on synthetic EEG data.

引用

页码：489 / 493

页数：5

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