Analysis of epileptogenic network properties during ictal activity.
In the present study, we utilize methods from graph theory to analyze epileptogenic network properties during periods of ictal activity. Using these methods, we analyzed the DTF-based causal information flow in nine seizures recorded from two patients undergoing presurgical monitoring for the treatment of medically intractable epilepsy. From the results, we observed a high degree of correlation between the regions with a high amount of information outflow (termed the outdegree) and the cortical areas identified clinically as the generators of the ictal activity. We furthermore observe a frequency-dependent correlation between the co-localization of these "activated regions" and the clinical foci. These findings suggest that application of network analysis tools to ictal activity could provide clinically useful information concerning these epileptogenic networks.
Wilke
Christopher
C
Department of Biomedical Engineering at the University of Minnesota, Minneapolis, MN 55455, USA. wilk0242@umn.edu
Worrell
Gregory A
GA
He
Bin
B
D000328:Adult; D001698:Biomedical Engineering / Q000379:methods; D001921:Brain / Q000473:pathology; D001931:Brain Mapping / Q000379:methods*; D016000:Cluster Analysis; D004569:Electroencephalography / Q000379:methods*; D004827:Epilepsy / Q000175:diagnosis* / Q000503:physiopathology*; D005260:Female; D006801:Humans; D008297:Male; D008959:Models, Neurological; D015233:Models, Statistical; D009415:Nerve Net; D012640:Seizures; D012815:Signal Processing, Computer-Assisted; D013997:Time Factors