Symmetrical EEG/FMRI fusion with spatially adaptive priors using variational distribution approximation

Author

Luessi, Martin ; Babacan, S. Derin ; Molina, Rafael ; Booth, James R. ; Katsaggelos, Aggelos K.

Author_Institution

Dept. of EECS, Northwestern Univ., Evanston, IL, USA

fYear

2010

fDate

14-19 March 2010

Firstpage

638

Lastpage

641

Abstract

In this paper, we propose a symmetrical EEG/fMRI fusion algorithm which combines EEG and fMRI by means of a common generative model. The use of a total variation (TV) prior as well as spatially adaptive temporal priors enables adaptation to the local characteristics of the estimated responses. We utilize an approximate variational Bayesian framework and obtain a fully automatic fusion algorithm. Simulation results demonstrate that the proposed algorithm outperforms existing EEG/fMRI fusion methods.

Keywords

Bayes methods; biomedical MRI; electroencephalography; image fusion; medical image processing; EEG; approximate variational Bayesian framework; common generative model; fMRI; spatially adaptive priors; symmetrical fusion algorithm; variational distribution approximation; Bayesian methods; Brain modeling; Electric variables measurement; Electrodes; Electroencephalography; Fusion power generation; Inference algorithms; Neuroimaging; Spatial resolution; TV; EEG; fMRI; total variation (TV); variational Bayesian methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on

Conference_Location

Dallas, TX

ISSN

1520-6149

Print_ISBN

978-1-4244-4295-9

Electronic_ISBN

1520-6149

Type

conf

DOI

10.1109/ICASSP.2010.5495153

Filename

5495153