DocumentCode :
1682973
Title :
EEG-FMRI integration using a partially constrained tensor factorization
Author :
Ferdowsi, Saideh ; Abolghasemi, Vahid ; Sanei, Saeid
Author_Institution :
Fac. of Eng. & Phys. Sci., Univ. of Surrey, Guildford, UK
fYear :
2013
Firstpage :
6191
Lastpage :
6195
Abstract :
Simultaneous EEG-fMRI recording provides great opportunity to study the relationship between synchronous neuronal activity in EEG and blood oxygenation level dependent (BOLD) in fMRI. In this paper a novel semi-blind technique using PARAFAC2 is proposed to investigate the correlation between post-movement beta rebound (PMBR) in beta band and BOLD. In this method, the instantaneous power of EEG in beta band representing the PMBR is calculated and used as a constraint for PARAFAC2 to detect the fMRI voxels activated during PMBR. The results confirm that the proposed method effectively detects the area in the brain which is responsible for beta rebound. The results are compared with those of general linear model (GLM) that completely relies on the predefined fMRI time-course.
Keywords :
biomedical MRI; blind source separation; blood; brain; electroencephalography; medical signal processing; sensor fusion; BOLD; EEG instantaneous power; EEG-fMRI integration; PARAFAC2; PMBR; beta band; blood oxygenation level dependent activity; brain; partially constrained tensor factorization; post movement beta rebound; predefined fMRI time course; semiblind technique; simultaneous EEG-fMRI recording; synchronous neuronal activity; Algorithm design and analysis; Brain modeling; Computational modeling; Correlation; Electroencephalography; Rhythm; Tensile stress; PARAFAC2; Post-movement beta rebound; Simultaneous EEG-fMRI;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on
Conference_Location :
Vancouver, BC
ISSN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2013.6638855
Filename :
6638855
Link To Document :
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