Abstracts

Rationale: One of the important methods of treatment of intractable epilepsy is to remove the epileptogenic zones after identifying that location in brain.  Multiple approaches are used in determining the epileptogenic zone.  We aim to establish the relationships between epileptiform activity recorded in intracranial and scalp EEG, both in frequency and time domains.  We use the stereo-EEG(sEEG) and scalp EEG recorded from widespread brain regions in identifying these relationships. Methods: We recorded the scalp (a modified 10-20 montage) and intracranial EEG  (Stereo EEG), from approximately 140 electrode sites (implanted at multiple location) simultaneously, in patients undergoing stereo EEG monitoring as part of the presurgical work up for localization of epileptogenic zones for intractable epilepsy.  These patients also had undergone initial EEG evaluation with scalp EEG.   The stereo EEG electrodes were placed on specific locations based on the hypothesis developed based on scalp EEG and brain imaging.  The data was initially recorded in Nihon Kohden and exported in the ‘.eeg’ format and was imported to Matlab (Mathworks) for analysis, using the Brainstorm toolbox.  Further analysis of the signal was done in Matlab in temporal and frequency domains.  The epileptiform activity (n= 20 identified from each patient) including sharp waves and spikes were analyzed for a period of around 2 seconds (+/-1 second) around the peak amplitude, for the frequency and time domain components. Results: The scalp EEG with sEEG (simultaneous recording) captured epileptiform patterns with similar abundance compared to initial scalp-only recording, suggesting that intracranial placement of the electrodes did not significantly affect the epileptiform activity.  The spatial analysis showed that the intracranial EEG shows higher frequency patterns more prominently in the electrodes placed over grey mater regions of the brain compared to that over the white mater.  Also, the epileptiform patterns tended to last longer over the grey mater regions.  In the frequency domain, the intracranial EEG demonstrated a combination of high frequency (20-40 Hz and 50-150hz) and lower frequency (1-3 hz) components, with the higher frequency components showing lower power. It may be noted that the higher frequency components were noted even when the scalp EEG did not show significant epileptiform activity. Conclusions: The components of the epileptiform activity are widely distributed in space, temporal and frequency domains, but specific components may be contributing to the significant pathophysiological processes.  Identifying them cellular level would be important in focused surgical approaches in epilepsy treatment. Funding: None