Comparative analysis of temporal dynamics of EEG and phase synchronization of EEG to localize epileptic sites from high density scalp EEG interictal recordings.
Our objective was to examine if the high-density, 256 channel, scalp interictal EEG data can be used for localizing the epilepsy areas in patients. This was done by examining the long-range temporal correlations (LRTC) of EEGs and also that of the phase synchronization index (SI) of EEGs. It was found that the LRTC of scalp SI plots were better in localizing the seizure areas as compared with the LRTC of EEGs alone. The EEG data of one minute duration was filtered in the low Gamma band of 30-50 Hz. A detrended fluctuation analysis (DFA) was used to find LRTC of the scalp EEG data. Contour plots were constructed using a montage of the layout of 256 electrode positions. The 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. LRTC of the SI was computed and spatial plots were made. It was found that the LRTC of SI was highest at the location of the epileptic sites. A similar pattern was not found in the LRTC of EEGs. This provides a noninvasive way to localize seizure areas from scalp EEG data.
Ramon
Ceon
C
Department of Neurology, University of Washington, Seattle, 98195, USA. ceon@u.washington.edu
Holmes
Mark D
MD
Freeman
Walter J
WJ
McElroy
Ryan
R
Rezvanian
Elham
E
D000465:Algorithms; D003344:Cortical Synchronization / Q000379:methods*; D004566:Electrodes; D004569:Electroencephalography / Q000379:methods*; D001330:Electronic Data Processing; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology; D006801:Humans; D015233:Models, Statistical; D008991:Monitoring, Physiologic; D012535:Scalp / Q000503:physiopathology*; D012640:Seizures / Q000175:diagnosis / Q000503:physiopathology; D012815:Signal Processing, Computer-Assisted