Ke Ming, Wang Changliang, Liu Guangyao
School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China.
Department of Magnetic Resonance, Lanzhou University Second Hospital, Lanzhou, China.
Front Behav Neurosci. 2023 Mar 10;17:1123534. doi: 10.3389/fnbeh.2023.1123534. eCollection 2023.
It is indisputable that the functional connectivity of the brain network in juvenile myoclonic epilepsy (JME) patients is abnormal. As a mathematical extension of the traditional network model, the multilayer network can fully capture the fluctuations of brain imaging data with time, and capture subtle abnormal dynamic changes. This study assumed that the dynamic structure of JME patients is abnormal and used the multilayer network framework to analyze the change brain community structure in JME patients from the perspective of dynamic analysis. First, functional magnetic resonance imaging (fMRI) data were obtained from 35 JME patients and 34 healthy control subjects. In addition, the communities of the two groups were explored with the help of a multilayer network model and a multilayer community detection algorithm. Finally, differences were described by metrics that are specific to the multilayer network. Compared with healthy controls, JME patients had a significantly lower modularity degree of the brain network. Furthermore, from the level of the functional network, the integration of the default mode network (DMN) and visual network (VN) in JME patients showed a significantly higher trend, and the flexibility of the attention network (AN) also increased significantly. At the node level, the integration of seven nodes of the DMN was significantly increased, the integration of five nodes of the VN was significantly increased, and the flexibility of three nodes of the AN was significantly increased. Moreover, through division of the core-peripheral system, we found that the left insula and left cuneus were core regions specific to the JME group, while most of the peripheral systems specific to the JME group were distributed in the prefrontal cortex and hippocampus. Finally, we found that the flexibility of the opercular part of the inferior frontal gyrus was significantly correlated with the severity of JME symptoms. Our findings indicate that the dynamic community structure of JME patients is indeed abnormal. These results provide a new perspective for the study of dynamic changes in communities in JME patients.
无可争议的是，青少年肌阵挛性癫痫（JME）患者脑网络的功能连接异常。作为传统网络模型的数学扩展，多层网络可以充分捕捉脑成像数据随时间的波动，并捕捉细微的异常动态变化。本研究假设JME患者的动态结构异常，并使用多层网络框架从动态分析的角度分析JME患者脑社区结构的变化。首先，从35例JME患者和34名健康对照者中获取功能磁共振成像（fMRI）数据。此外，借助多层网络模型和多层社区检测算法探索两组的社区。最后，用多层网络特有的指标描述差异。与健康对照相比，JME患者脑网络的模块化程度显著降低。此外，从功能网络层面来看，JME患者默认模式网络（DMN）和视觉网络（VN）的整合呈现出显著更高的趋势，注意力网络（AN）的灵活性也显著增加。在节点层面，DMN的七个节点的整合显著增加，VN的五个节点的整合显著增加，AN的三个节点的灵活性显著增加。此外，通过核心 - 外周系统划分，我们发现左侧岛叶和左侧楔叶是JME组特有的核心区域，而JME组特有的外周系统大多分布在额叶前部皮质和海马体。最后，我们发现额下回岛盖部的灵活性与JME症状的严重程度显著相关。我们的研究结果表明，JME患者的动态社区结构确实异常。这些结果为研究JME患者社区的动态变化提供了新的视角。
