Department of Neurology, Manchester Centre for Clinical Neurosciences, United Kingdom; Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom.
Division of Neuroscience and Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, University of Manchester, United Kingdom; Manchester Academic Health Sciences Centre, United Kingdom.
Epilepsy Behav. 2020 May;106:107013. doi: 10.1016/j.yebeh.2020.107013. Epub 2020 Mar 16.
The evaluation of the role of anomalous neuronal networks in epilepsy using a graph theoretical approach is of growing research interest. There is currently no consensus on optimal methods for performing network analysis, and it is possible that variations in study methodology account for diverging findings. This review focuses on global functional and structural interictal network characteristics in people with idiopathic generalized epilepsy (IGE) with the aim of appraising the methodological approaches used and assessing for meaningful consensus. Thirteen studies were included in the review. Data were heterogenous and not suitable for meta-analysis. Overall, there is a suggestion that the cerebral neuronal networks of people with IGE have different global structural and functional characteristics to people without epilepsy. However, the nature of the aberrations is inconsistent with some studies demonstrating a more regular network configuration in IGE, and some, a more random topology. There is greater consistency when different data modalities and connectivity subtypes are compared separately, with a tendency towards increased small-worldness of networks in functional electroencephalography/magnetoencephalography (EEG/MEG) studies and decreased small-worldness of networks in structural studies. Prominent variation in study design at all stages is likely to have contributed to differences in study outcomes. Despite increasing literature surrounding neuronal network analysis, systematic methodological studies are lacking. Absence of consensus in this area significantly limits comparison of results from different studies, and the ability to draw firm conclusions about network characteristics in IGE.
使用图论方法评估癫痫中的异常神经元网络的作用是越来越受到关注的研究领域。目前，对于执行网络分析的最佳方法还没有共识，并且研究方法的差异可能导致研究结果的分歧。本综述重点关注特发性全面性癫痫（IGE）患者的局灶间网络的全局功能和结构特征，旨在评估所使用的方法学方法，并评估是否存在有意义的共识。本综述共纳入了 13 项研究。数据存在异质性，不适合进行荟萃分析。总体而言，有研究表明，IGE 患者的大脑神经元网络具有与无癫痫患者不同的全局结构和功能特征。然而，异常的性质与一些研究中表明的 IGE 中更规则的网络结构不一致，而另一些研究则表明网络拓扑更随机。当分别比较不同的数据模态和连接亚型时，一致性更高，功能脑电图/脑磁图（EEG/MEG）研究中的网络小世界性增加，结构研究中的网络小世界性降低。在各个阶段，研究设计的显著变化可能导致了研究结果的差异。尽管有关神经元网络分析的文献不断增加，但系统的方法学研究却缺乏。该领域缺乏共识极大地限制了对不同研究结果的比较，也限制了对 IGE 中网络特征的得出确定结论的能力。
