Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in temporal lobe epilepsy
机构:[1]Department of Geriatric Medicine, Beijing Luhe Hospital, Capital Medical University, No. 82, Xinhua South Street, Tongzhou District, Beijing 101149, China[2]Faculty of Information Technology, University of Jyv?skyl?, 40014 Jyvaskyla, Finland[3]School of Biomedical Engineering, Faculty of Electronic Information and Electrical Engineering, Dalian University of Technology, Dalian 116024, China[4]Department of Neurology, Xuanwu Hospital, Capital Medical University, Beijing 100053, China神经内科[5]Beijing Key Laboratory of Neuromodulation, Beijing 100053, China神经变性病教育部重点实验室[6]Center of Epilepsy, Beijing Institute for Brain Disorders, Beijing 100053, China北京市癫痫诊疗中心[7]State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekou Street, Haidian District, Beijing 100875, China
ObjectiveAbnormal and dynamic epileptogenic networks cause difficulties for clinical epileptologists in the localization of the seizure onset zone (SOZ) and the epileptogenic zone (EZ) in preoperative assessments of patients with refractory epilepsy. The aim of this study is to investigate the characteristics of time-varying effective connectivity networks in various non-seizure and seizure periods, and to propose a quantitative approach for accurate localization of SOZ and EZ.MethodsWe used electrocorticogram recordings in the temporal lobe and hippocampus from seven patients with temporal lobe epilepsy to characterize the effective connectivity dynamics at a high temporal resolution using the full-frequency adaptive directed transfer function (ffADTF) measure and five graph metrics, i.e., the out-degree (OD), closeness centrality (CC), betweenness centrality (BC), clustering coefficient (C), and local efficiency (LE). The ffADTF effective connectivity network was calculated and described in five frequency bands (, , , , and ) and five seizure periods (pre-seizure, early seizure, mid-seizure, late seizure, and post-seizure). The cortical areas with high values of graph metrics in the transient seizure onset network were compared with the SOZ and EZ identified by clinical epileptologists and the results of epilepsy resection surgeries.ResultsOrigination and propagation of epileptic activity were observed in the high time resolution ffADTF effective connectivity network throughout the entire seizure period. The seizure-specific transient seizure onset ffADTF network that emerged at seizure onset time remained for approximately 20-50ms with strong connections generated from both SOZ and EZ. The values of graph metrics in the SOZ and EZ were significantly larger than that in the other cortical areas. More cortical areas with the highest mean of graph metrics were the same as the clinically determined SOZ in the low-frequency and bands and in Engel Class I patients than in higher frequency , , and bands and in Engel Class II and III patients. The OD and C were more likely to localize the SOZ and EZ than CC, BC, and LE in the transient seizure onset network.ConclusionThe high temporal resolution ffADTF effective connectivity analysis combined with the graph theoretical analysis helps us to understand how epileptic activity is generated and propagated during the seizure period. The newly discovered seizure-specific transient seizure onset network could be an important biomarker and a promising tool for more precise localization of the SOZ and EZ in preoperative evaluations.
第一作者机构:[1]Department of Geriatric Medicine, Beijing Luhe Hospital, Capital Medical University, No. 82, Xinhua South Street, Tongzhou District, Beijing 101149, China[2]Faculty of Information Technology, University of Jyv?skyl?, 40014 Jyvaskyla, Finland
通讯作者:
通讯机构:[1]Department of Geriatric Medicine, Beijing Luhe Hospital, Capital Medical University, No. 82, Xinhua South Street, Tongzhou District, Beijing 101149, China[7]State Key Laboratory of Cognitive Neuroscience and Learning, IDG/McGovern Institute for Brain Research, Beijing Normal University, No. 19 Xinjiekou Street, Haidian District, Beijing 100875, China
推荐引用方式(GB/T 7714):
Ren Ye,Cong Fengyu,Ristaniemi Tapani,et al.Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in temporal lobe epilepsy[J].JOURNAL OF NEUROLOGY.2019,266(4):844-859.doi:10.1007/s00415-019-09204-4.
APA:
Ren, Ye,Cong, Fengyu,Ristaniemi, Tapani,Wang, Yuping,Li, Xiaoli&Zhang, Ruihua.(2019).Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in temporal lobe epilepsy.JOURNAL OF NEUROLOGY,266,(4)
MLA:
Ren, Ye,et al."Transient seizure onset network for localization of epileptogenic zone: effective connectivity and graph theory-based analyses of ECoG data in temporal lobe epilepsy".JOURNAL OF NEUROLOGY 266..4(2019):844-859