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In this work, a new approach to simultaneous Electroencephalography correlated Functional Magnetic Imaging (EEG-fMRI) data processing in epilepsy is introduced. Independent component analysis decomposition was performed on EEG data and multiple model based metrics were applied to the resulting time courses, these were then used to predict the fMRI data. When compared with the conventional fMRI data analysis based on square waveform descriptions of seizure activity, more significant activations were found with the method proposed here, for the four patients studied. In general, the results were consistent with the neurophysiologist's expectation, but further validation using more direct measurements of seizure activity is necessary. A detailed study on the hemodynamic response function (HRF) to the EEG metrics was performed for one patient. The HRFs estimated were broader than the canonical HRF and the distributions of its delay and dispersion were mapped throughout the subject's brain.