The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, School of Life Science and Technology, University of Electronic Science and Technology of China, Qingshuihe Campus: No.2006, Xiyuan Ave, West Hi-Tech Zone, Chengdu, 611731, People's Republic of China.
Department of Neurology, First Affiliated Hospital of Hainan Medical University, Haikou, China.
Brain Struct Funct. 2021 Jun;226(5):1423-1435. doi: 10.1007/s00429-021-02248-1. Epub 2021 Mar 17.
This study aims to characterize the connective profiles and the coupling relationship between dynamic and static functional connectivity (dFC and sFC) in large-scale brain networks in patients with generalized epilepsy (GE). Functional, structural and diffuse MRI data were collected from 83 patients with GE and 106 matched healthy controls (HC). Resting-state BOLD time course was deconvolved to neural time course using a blind hemodynamic deconvolution method. Then, five connective profiles, including the structural connectivity (SC) and BOLD/neural time course-derived sFC/dFC networks, were constructed based on the proposed whole brain atlas. Network-level weighted correlation probability (NWCP) were proposed to evaluate the association between dFC and sFC. Both the BOLD signal and neural time course showed highly concordant findings and the present study emphasized the consistent findings between two functional approaches. The patients with GE showed hypervariability and enhancement of FC, and notably decreased SC in the subcortical network. Besides, increased dFC, weaker anatomic links, and complex alterations of sFC were observed in the default mode network of GE. Moreover, significantly increased SC and predominantly increased sFC were found in the frontoparietal network. Remarkably, antagonism between dFC and sFC was observed in large-scale networks in HC, while patients with GE showed significantly decreased antagonism in core epileptic networks. In sum, our study revealed distinct connective profiles in different epileptic networks and provided new clues to the brain network mechanism of epilepsy from the perspective of antagonism between dynamic and static functional connectivity.
本研究旨在描述广泛性癫痫（GE）患者大脑网络中动态功能连接（dFC）和静态功能连接（sFC）的连接特征及其耦合关系。从 83 名 GE 患者和 106 名匹配的健康对照者（HC）中采集功能、结构和弥散 MRI 数据。使用盲血液动力学反卷积方法对静息态 BOLD 时间序列进行神经时间序列反卷积。然后，基于提出的全脑图谱构建了五种连接特征，包括结构连接（SC）和 BOLD/神经时间序列衍生的 sFC/dFC 网络。提出网络级加权相关概率（NWCP）来评估 dFC 和 sFC 之间的关联。BOLD 信号和神经时间序列均显示出高度一致的结果，本研究强调了两种功能方法的一致结果。GE 患者表现出 FC 的高可变性和增强，以及皮质下网络中 SC 的明显减少。此外，GE 默认模式网络中观察到 dFC 增加、解剖学联系减弱以及 sFC 的复杂变化。此外，在额顶网络中发现了明显增加的 SC 和主要增加的 sFC。值得注意的是，HC 中的大尺度网络中存在 dFC 和 sFC 之间的拮抗作用，而 GE 患者在核心癫痫网络中表现出明显降低的拮抗作用。总之，本研究揭示了不同癫痫网络中不同的连接特征，并从 dFC 和 sFC 之间的拮抗作用的角度为癫痫的脑网络机制提供了新的线索。
