Abstract

Identification of seizure sources in the brain is of paramount importance, particularly for drug-resistant epilepsy patients who may require surgical operation. Interictal epileptiform discharges (IEDs), which may or may not be frequent, are known to originate from seizure networks. Delayed responses (DRs) to brain electrical stimulation have been recently discovered. If DRs and IEDs come from the same location and the DRs can be accurately localized, there will be a significant step in identification of the seizure sources. The solution to this important question has been investigated in this paper. For this, we have exploited the morphology of these spike-type events, as well as the variability in their temporal locations, to develop new constraints for an adaptive Bayesian beamformer that outperforms the conventional and recently proposed beamformers even for identifying correlated sources. This beamformer is applied to an array (a.k.a mat) of cortical EEG electrodes. The developed approach has been tested on 300 data segments from five epileptic patients included in this study, which clinically represent a large population of candidates for surgical treatment. As the significant outcome of applying this beamformer, it is very likely (if not certain) that for an epileptic subject, the IEDs and DRs originate from the same location in the brain. This paves the way for a quick identification of the source(s) of seizure in the brain.

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