Recursive independent component analysis (ICA)-decomposition of ictal EEG to select the best ictal component for EEG source imaging

OBJECTIVE This study aimed to present a new ictal component selection technique, named as recursive ICA-decomposition for ictal component selection (RIDICS), for potential application in epileptogenic zone localization. METHODS The proposed technique decomposes ictal EEG recursively, eliminates a few unwanted components in every recursive cycle, and finally selects the most significant ictal component. Back-projected EEG, regenerated from that component, was used for source estimation. Fifty sets of simulated EEGs and 24 seizures in 8 patients were analyzed. Dipole sources of simulated-EEGs were compared with a known dipole location whereas epileptogenic zones of the seizures were compared with their corresponding sites of successful surgery. The RIDICS technique was compared with a conventional technique. RESULTS The RIDICS technique estimated the dipole sources…