Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration
Dynamic functional connectivity and graph theory metrics in a rat model of temporal lobe epilepsy reveal a preference for brain states with a lower functional connectivity, segregation and integration
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DOI：
10.1016/j.nbd.2020.104808
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发表时间：
2020-06-01
影响因子：
6.1
通讯作者：
Vanhove, Christian
中科院分区：
文献类型：
--
作者：
Christiaen, Emma;Goossens, Marie-Gabrielle;Vanhove, Christian
癫痫是一种以反复发作为特征的神经系统疾病。癫痫患者的电生理和神经影像学研究证实了异常功能脑网络参与癫痫及其合并症的发展。本研究采用kainic acid （IPKA）腹腔注射颞叶癫痫（TLE）大鼠模型，研究癫痫发展过程中动态功能连接（dFC）和网络拓扑结构的变化。采用7 T MRI系统获取20只IPKA动物和7只健康对照动物在美托咪定麻醉前及麻醉后1、3、6、10和16周的静息状态功能磁共振图像（rsfMRI）。从se后17周开始，记录海马脑电图，以确定每只动物的平均每日癫痫发作频率。动态FC通过在50秒的滑动窗口内使用2秒的步长计算预定义感兴趣区域的fMRI时间序列之间的相关矩阵来评估。使用k-means聚类将矩阵分为6个FC状态，每个状态由一个相关矩阵表征。此外，从时变相关矩阵中计算出若干时变图理论网络度量，并将其划分为功能网络拓扑的6种状态，每种状态以网络度量的组合为特征。我们的研究结果表明，与对照动物相比，IPKA动物中具有较低平均功能连通性，较低分离和整合的FC状态更常发生。在癫痫发生过程中，功能连通性也变得较少变化。此外，平均每日癫痫发作频率与高平均功能连通性、高隔离和高整合状态的百分比停留时间（即状态发生的频率）以及状态之间的转换次数呈正相关，而与低平均功能连通性、低隔离和低整合状态的百分比停留时间负相关。这表明，生活在功能连接程度更高、隔离程度更高、整合程度更高、状态之间切换更频繁的动物，癫痫发作次数更多。
Epilepsy is a neurological disorder characterized by recurrent epileptic seizures. The involvement of abnormal functional brain networks in the development of epilepsy and its comorbidities has been demonstrated by electrophysiological and neuroimaging studies in patients with epilepsy. This longitudinal study investigated changes in dynamic functional connectivity (dFC) and network topology during the development of epilepsy using the intraperitoneal kainic acid (IPKA) rat model of temporal lobe epilepsy (TLE). Resting state functional magnetic resonance images (rsfMRI) of 20 IPKA animals and 7 healthy control animals were acquired before and 1, 3, 6, 10 and 16 weeks after status epilepticus (SE) under medetomidine anaesthesia using a 7 T MRI system. Starting from 17 weeks post-SE, hippocampal EEG was recorded to determine the mean daily seizure frequency of each animal. Dynamic FC was assessed by calculating the correlation matrices between fMRI time series of predefined regions of interest within a sliding window of 50 s using a step length of 2 s. The matrices were classified into 6 FC states, each characterized by a correlation matrix, using k-means clustering. In addition, several time-variable graph theoretical network metrics were calculated from the time-varying correlation matrices and classified into 6 states of functional network topology, each characterized by a combination of network metrics. Our results showed that FC states with a lower mean functional connectivity, lower segregation and integration occurred more often in IPKA animals compared to control animals. Functional connectivity also became less variable during epileptogenesis. In addition, average daily seizure frequency was positively correlated with percentage dwell time (i.e. how often a state occurs) in states with high mean functional connectivity, high segregation and integration, and with the number of transitions between states, while negatively correlated with percentage dwell time in states with a low mean functional connectivity, low segregation and low integration. This indicates that animals that dwell in states of higher functional connectivity, higher segregation and higher integration, and that switch more often between states, have more seizures.