Application of Matched-Filtering to Extract EEG Features and Decouple Signal Contributions from Multiple Seizure Foci in Brain Malformations.

Abstract

Developmental brain malformations often cause intractable and in many cases generalized and/or multifocal seizures. Surgical intervention is not possible in these cases as it is difficult to isolate the epileptogenic foci. Scalp EEG signals recorded during such seizures include coupled contributions from different sources. If it was possible to decouple these contributions based on differences in both their signatures and inter-arrival times at different electrodes, it would subsequently be possible to estimate the locations of the seizure foci. For this purpose, we applied matched filtering to scalp EEG data from 3 patients with multifocal seizures, using patient-specific source-related short EEG segments as the template waveforms. These segments were assumed to be seizure-related based on distinct sets of inter-arrival times at different channels and alternating signal polarities. We present preliminary results and demonstrate that matched filtering can be successfully applied to extract decoupled signal components from the EEG, generated by potentially distinct sources, and thus with distinct inter-arrival times but partially overlapping spectra.