Localizing Epileptic Focus of Patients with Epilepsy Using Post-Ictal Scalp EEG

M. Yao, Chunsheng Li
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Abstract

Localization of the epileptic focus is crucial for epilepsy surgery. Pre-ictal EEG and interictal epileptic discharges are commonly used to localize the focus. Post-ictal scalp EEG may provide useful information for localizing the epileptic focus. This study proposed a non-invasive procedure to localize the epileptic focus via the EEG source imaging (ESI) and epileptic network analysis. Scalp EEG from two patients with drug-resistant epilepsy were used, and two segments of post-ictal EEG were analyzed. The sLORETA algorithm was applied to obtain signals in source space using the patient specific head model. Then we extracted the representative source signals of each brain area by singular value decomposition (SVD). The epileptic networks of different frequency bands in the source space were constructed by Granger causality analysis. The results showed that the regions identified by in-degree feature of low-frequency post-ictal epileptic network were concordant with surgical resected areas. The preliminary result indicates that post-ictal epileptic network in low frequency may potentially be used to identify the ictal focus for surgical planning.
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颅后脑电图在癫痫患者癫痫病灶定位中的应用
癫痫病灶的定位对癫痫手术至关重要。脑电图和癫痫发作间期放电常用于定位病灶。脑电图可以为癫痫病灶的定位提供有用的信息。本研究提出了一种通过脑电图源成像(ESI)和癫痫网络分析来定位癫痫病灶的无创方法。对2例耐药癫痫患者的头皮脑电图进行分析。采用患者特异性头部模型,采用sLORETA算法在源空间获取信号。然后通过奇异值分解(SVD)提取各脑区的代表性源信号。通过格兰杰因果关系分析,构建了源空间中不同频段的癫痫网络。结果表明,低频癫痫发作后网络的度特征识别的区域与手术切除的区域一致。初步结果表明,低频癫痫发作后网络可能用于确定手术计划的癫痫发作灶。
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