  By computerized analysis of cortical activity recorded via fMRI for pediatric
epilepsy patients, we implement algorithmic localization of epileptic seizure
focus within one of eight cortical lobes. Our innovative machine learning
techniques involve intensive analysis of large matrices of mutual information
coefficients between pairs of anatomically identified cortical regions. Drastic
selection of pairs of regions with significant inter-connectivity provide
efficient inputs for our Multi-Layer Perceptron (MLP) classifier. By imposing
rigorous parameter parsimony to avoid over fitting we construct a small size
MLP with very good percentages of successful classification.
