University of Debrecen, Kenézy Gyula University Hospital, Department of Neurology, Bartók Béla út 3., 4031 Debrecen, Hungary.
University of Debrecen, Department of Medical Imaging, Nagyerdei krt. 98., 4032 Debrecen, Hungary.
Clin Neurophysiol. 2019 Feb;130(2):251-258. doi: 10.1016/j.clinph.2018.11.022. Epub 2018 Dec 16.
OBJECTIVE: Aim of the study was to explore the inter-ictal, resting-state EEG network in patients with focal epilepsy (FE) and to specify clinical factors that influence network activity. METHODS: Functional EEG connectivity (EEGfC) differences were computed between 232 FE patients (FE group) and 77 healthy controls. EEGfC was computed among 23 cortical regions within each hemisphere, for 25 very narrow bands from 1 to 25 Hz. We computed independent effects for six clinical factors on EEGfC in the FE group, by ANOVA and post-hoc t-statistics, corrected for multiple comparisons by false discovery rate method. RESULTS: Robust, statistically significant EEGfC differences emerged between the FE and the healthy control groups. Etiology, seizure type, duration of the illness and antiepileptic treatment were independent factors that influenced EEGfC. Statistically significant results occurred selectively in one or a few very narrow bands and outlined networks. Most abnormal EEGfC findings occurred at frequencies that mediate integrative and motor activities. CONCLUSIONS: FE patients have abnormal resting-state EEGfC network activity. Clinical factors significantly modify EEGfC. SIGNIFICANCE: Delineation of the FE network and modifying factors can open the way for targeted investigations and introduction of EEGfC into epilepsy research and practice.
目的:研究旨在探讨局灶性癫痫(FE)患者发作间期静息状态 EEG 网络,并明确影响网络活动的临床因素。
方法:对 232 名 FE 患者(FE 组)和 77 名健康对照者的功能 EEG 连接(EEGfC)差异进行了计算。在每个半球的 23 个皮质区域之间,计算了 25 个非常窄的频带(1-25 Hz)的 EEGfC。通过方差分析和事后 t 检验,我们计算了 6 个临床因素对 FE 组 EEGfC 的独立影响,通过假发现率方法校正了多次比较的影响。
结果:FE 组和健康对照组之间出现了稳健的、具有统计学意义的 EEGfC 差异。病因、发作类型、病程和抗癫痫治疗是影响 EEGfC 的独立因素。统计上显著的结果选择性地发生在一个或几个非常窄的频带和概述网络中。大多数异常 EEGfC 发现发生在介导整合和运动活动的频率上。
结论:FE 患者存在异常的静息状态 EEGfC 网络活动。临床因素显著改变了 EEGfC。
意义:FE 网络和调节因素的描绘可以为有针对性的研究和将 EEGfC 引入癫痫研究和实践开辟道路。
Clin Neurophysiol. 2018-12-16
Ideggyogy Sz. 2019-3-30
Epilepsia. 2010-12-3
Epilepsia. 2017-5-20