Department of Orthopaedic Surgery and Biomedical Engineering, University of Tennessee Health Science Center, Memphis, Tennessee, USA.
Department of Biomedical Engineering, University of Memphis, Memphis, Tennessee, USA.
Hum Brain Mapp. 2020 Aug 1;41(11):2964-2979. doi: 10.1002/hbm.24990. Epub 2020 May 13.
Focal epilepsy originates within networks in one hemisphere. However, previous studies have investigated network topologies for the entire brain. In this study, magnetoencephalography (MEG) was used to investigate functional intra-hemispheric networks of healthy controls (HCs) and patients with left- or right-hemispheric temporal lobe or temporal plus extra-temporal lobe epilepsy. 22 HCs, 25 left patients (LPs), and 16 right patients (RPs) were enrolled. The debiased weighted phase lag index was used to calculate functional connectivity between 246 brain regions in six frequency bands. Global efficiency, characteristic path length, and transitivity were computed for left and right intra-hemispheric networks. The right global graph measures (GGMs) in the theta band were significantly different (p < .005) between RPs and both LPs and HCs. Right and left GGMs in higher frequency bands were significantly different (p < .05) between HCs and the patients. Right GGMs were used as input features of a Naïve-Bayes classifier to classify LPs and RPs (78.0% accuracy) and all three groups (75.5% accuracy). The complete theta band brain networks were compared between LPs and RPs with network-based statistics (NBS) and with the clustering coefficient (CC), nodal efficiency (NE), betweenness centrality (BC), and eigenvector centrality (EVC). NBS identified a subnetwork primarily composed of right intra-hemispheric connections. Significantly different (p < .05) nodes were primarily in the right hemisphere for the CC and NE and primarily in the left hemisphere for the BC and EVC. These results indicate that intra-hemispheric MEG networks may be incorporated in the diagnosis and lateralization of focal epilepsy.
局灶性癫痫起源于一个半球的网络内。然而，以前的研究已经调查了整个大脑的网络拓扑结构。在这项研究中，使用脑磁图 (MEG) 来研究健康对照组 (HCs) 和左或右颞叶或颞叶加颞叶外癫痫患者的功能性半球内网络。共纳入 22 名 HCs、25 名左患者 (LPs) 和 16 名右患者 (RPs)。使用无偏加权相位滞后指数计算六个频带中 246 个脑区之间的功能连接。计算左、右半球内网络的全局效率、特征路径长度和传递性。theta 波段的右全局图测度 (GGMs) 在 RPs 与 LPs 和 HCs 之间差异显著 (p <.005)。高频带的右和左 GGMs 在 HCs 和患者之间差异显著 (p <.05)。将右 GGMs 作为朴素贝叶斯分类器的输入特征，用于分类 LPs 和 RPs (78.0%准确率) 和所有三组 (75.5%准确率)。使用基于网络的统计学 (NBS) 和聚类系数 (CC)、节点效率 (NE)、介数中心性 (BC) 和特征向量中心性 (EVC) 比较 LPs 和 RPs 之间的完整 theta 波段脑网络。NBS 确定了一个主要由右半球内连接组成的子网。CC 和 NE 的差异显著 (p <.05) 的节点主要位于右半球，BC 和 EVC 的节点主要位于左半球。这些结果表明，半球内 MEG 网络可能被纳入局灶性癫痫的诊断和定位。
