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측두엽성 간질에서 비선형 교차예측을 이용한 발작의 시공간 분포 : Spatio-temporal distribution & propagation of temporal lobe seizures: application of nonlinear mutual cross prediction

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Authors

정기영; 김재문; 이용만; 손은희; 홍승봉; 유철승; 이상훈

Issue Date
2002-03
Publisher
대한신경과학회
Citation
대한신경과학회지, Vol.20 No.2, pp. 147-152
Keywords
의약학Temporal lobe epilepsyEEGNonlinear interdependeceMutual cross prediction (MCP)Spatio-temporal distribution
Abstract
Background : Nonlinear mutual cross prediction (MCP) characterizes ynamic interdependence among nonlinear systems. MCP also reveal relative strength of the coupling between systems, thus provides information about the direction of interdependence. The aim of this study is to apply MCP algorithm to multi-channel EEG and to characterize spatio-temporal pattern of seizure. M e t h o d s : We analyzed MCP of EEG of three medically intractable temporal lobe epilepsy patients, who underwent temporal lobectomy (left 2, right 1). Asymmetry of nonlinear cross predictability between channels was investigated. Five epochs of interictal EEG free from epileptiform discharge(s) and of ictal EEG were analyzed. R e s u l t s : In interictal period, both frontal and occipital region appeared a weak driving force while awake and this driving force was further weakened during sleep. Before the onset of the seizure (preictal phase), the intensity of driving system became slightly stronger around seizure foci in 3 out of 8 seizures while no significant change was seen on the naked eyes. However this change was dim and not continuous. At the onset of seizure (ictal phase), 5 out of 8 seizures showed strong driving force around seizure foci. Three seizures without significant change initially had strong driving force as synchronous seizure discharges became built-up and spreading to surrounding areas in the middle of seizure. All seizures showed ipsilateral frontotemporal strong driving force and centroparietal response system, which was typical spatio-temporal distribution of MCP. Conclusion : MCP analysis may be a useful method for detecting spatio-temporal distribution and propagation pattern in temporal lobe epilepsy.
Language
Korean
URI
https://hdl.handle.net/10371/91836
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