Title: Analysis of visual cortex-event-related fMRI data using ICA decomposition

Authors: Bulbul Ahmed; Arif Ul Alam; Md. Abdullah-Al-Mamun; Md. Enamul Hoque Chowdhury; Tamnun E. Mursalin

Addresses: Electronics and Telecommunication Engineering, University of Liberal Arts Bangladesh, Dhanmondi, Dhaka 1209, Bangladesh. ' Electronics and Telecommunication Engineering, University of Liberal Arts Bangladesh, Dhanmondi, Dhaka 1209, Bangladesh. ' Electronics and Telecommunication Engineering, University of Liberal Arts Bangladesh, Dhanmondi, Dhaka 1209, Bangladesh. ' Sir Peter Mansfield Magnetic Resonance Center, University of Nottingham, Nottingham NG7 2RD, UK. ' Computer Science and Engineering, University of Liberal Arts Bangladesh, Dhanmondi, Dhaka 1209, Bangladesh

Abstract: Independent Component Analysis (ICA) of Functional Magnetic Resonance Imaging (fMRI) data is commonly carried out under the assumption that each source may be represented as a spatially fixed pattern of activation. In this work, to detect and visualise variations in single-trial Hemodynamic Responses (HR) in event-related fMRI data, Infomax ICA algorithm has been used. Six subjects participated in four fMRI sessions. ICA decomposition of the resulting Blood Oxygenation Level-Dependent (BOLD) data from each session produced an independent component active in primary visual cortex. The BOLD-image plots demonstrated that component HRs varied substantially and often systematically across trials as well as across sessions, subjects, and brain areas.

Keywords: fMRI; functional MRI; magnetic resonance imaging; ICA decomposition; biomedical image processing; infomax ICA; EEG; electroencephalography; PET; positron emission tomography; independent component analysis; blood oxygenation; primary visual cortex; brain areas.

DOI: 10.1504/IJBET.2011.044415

International Journal of Biomedical Engineering and Technology, 2011 Vol.7 No.4, pp.365 - 376

Published online: 21 Jan 2015 *

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