Abstracts

Rationale: We examined the spatiotemporal dynamics of stochastic behavior of phase synchronization from interictal 256-channel scalp EEG recordings in patients with proven epilepsy to determine if these measures are useful in localizing epileptogenic zones. Methods: We studied four patients with refractory epilepsy who underwent intracranial EEG to establish the localization of seizures. Prior to invasive EEG studies the subjects underwent dense array 256 channel EEG (dEEG) recordings. One minute of interictal dEEG was selected for analysis. The selected segment was at least two hours from an electrographic seizure and, based on visual analysis, free of interictal epileptiform patterns. Excessively noisy channels were removed and replaced with averages of surrounding electrodes. Data were imported into MATLAB for analysis. The EEG data was filtered in the theta (3-7 Hz), alpha (7-12 Hz), beta (12-30 Hz) and low gamma (30-50 Hz) band. The phase synchronization index (SI) was computed after taking Hilbert transform of the EEG data. The SI between a pair of channel was inferred from a statistical tendency to maintain a nearly constant phase difference over a given period of time even though the analytic phase of each channel may change markedly during that time frame. The SI for each electrode was averaged over with the nearby six electrodes. A detrended fluctuation analysis (DFA) was used to find the stochastic behavior of the SI. Contour plots with 5.0 sec intervals were constructed using a montage of the layout of 256 electrode positions. Results: Contour plots displayed over the scalp show that the stochastic behavior of the SI becomes stronger with time in the proven epileptogenic area while in other areas it becomes fragmented and scattered. For two subjects, we were able to identify the epileptogenic area after examining the stochastic behavior for 30 sec. For the third subject it required 45 sec and for the fourth subject, 60 sec to localize the epileptogenic area. Dynamic stochastic behavior was best demonstrated in the low gamma and beta bands, in relation to the epileptic sites. On the other hand, the theta band activity was depressed for all four subjects in the epileptogenic area. The alpha band activity did not show any distinguishable spatiotemporal patterns in regard to the epileptogenic zones. Conclusions: Examination of 60 sec of stochastic behavior of phase synchronization, derived from interictal scalp dEEG that is free of epileptiform discharges, has the potential to assist in localizing epileptic sites in subjects with proven epilepsy.