Abstract
Application of spatial Independent Component Analysis (ICA) to functional magnetic resonance imaging (fMRI) subject to the simultaneously recorded electroencephalography (EEG) signals as constraint, has been investigated in this work. In this novel approach, the closeness between the time course of spatial independent components of fMRI and EEG signals during epileptic seizure period is introduced as the constraint to the separation process. The performance of the algorithm has been tested on a set of simultaneous EEG and fMRI data and the results show a more accurate localization of the blood-oxygenated level-dependence (BOLD) regions, better algorithm convergence, and a higher correlation between the time course of spatial components and the seizure EEG signals than the conventional ICA method. copyright by EURASIP.