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

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.