Localization and propagation analysis of ictal source rhythm by electrocorticography.
The purpose of this study was to develop a novel approach for objectively estimating the locations of ictal onset zones by electrocorticography (ECoG). Conventional ECoG analyses have been performed using a 2-D space comprised of intracranial electrodes. Thus, despite the fact that ECoG data have much higher signal-to-noise ratios than electroencephalographic data, ECoG inherently requires a priori information to locate the electrodes, and thus, it is difficult to estimate the depth of epileptogenic foci using this technique. Accordingly, the authors considered that a 3-D approach is needed to determine the presence of an epileptogenic focus in the complex structure of the cortex. However, no source localization procedure has been devised to determine the location of a primary ictal source using ECoG. The authors utilized a spatiotemporal source localization technique using the first principal vectors. A directed transfer function was then employed for the time series of potential ictal sources to compute their causal inter-relationships, from which the primary sources responsible for ictal onset could be localized. Monte-Carlo simulation studies were performed to validate the feasibility and reliability of the proposed ECoG source localization technique, and the obtained results demonstrated that the mean of localization errors with a signal to white Gaussian noise ratio of 5 dB did not exceed 5 mm, even when the source was located approximately 20 mm away from the nearest electrode. This validated ictal source localization approach was applied to a number of ictal ECoG data sets from six successfully operated epilepsy patients. The resultant 3-D ictal source locations were found to coincide with surgical resection areas and with traditional 2-D electrode-based source estimates. The authors believe that this proposed ECoG-based ictal source localization method will be found useful, especially when ictal sources are located in a deep sulcus or beyond recording planes.
Kim
June Sic
JS
MEG Center, Department of Neurosurgery, Seoul National University College of Medicine, Seoul, South Korea.
Im
Chang Hwan
CH
Jung
Young Jin
YJ
Kim
Eun Young
EY
Lee
Sang Kun
SK
Chung
Chun Kee
CK
D000293:Adolescent; D000328:Adult; D000465:Algorithms; D001683:Biological Clocks; D001921:Brain / Q000503:physiopathology*; D003936:Diagnosis, Computer-Assisted; D004569:Electroencephalography / Q000379:methods*; D005260:Female; D006801:Humans; D008297:Male; D009415:Nerve Net / Q000503:physiopathology*; D012640:Seizures / Q000175:diagnosis* / Q000503:physiopathology*; D055815:Young Adult