Klugah-Brown Benjamin, Luo Cheng, He Hui, Jiang Sisi, Armah Gabriel Kofi, Wu Yu, Li Jianfu, Yin Wenjie, Yao Dezhong
The Clinical Hospital of Chengdu Brain Science Institute, MOE Key Lab for Neuroinformation, Center for Information in Medicine, School of life Science and technology, University of Electronic Science and Technology of China, No. 4, Section 2, North Jianshe Road, Chengdu, 610054, People's Republic of China.
Navrongo Campus, Computer Science Department, University for Development studies, P. O. Box 1350, Tamale, Ghana.
Brain Topogr. 2019 May;32(3):394-404. doi: 10.1007/s10548-018-0678-z. Epub 2018 Sep 25.
Frontal lobe epilepsy has recently been associated with disrupted brain functional connectivity; variations among various resting-state networks (RSNs) across time remains largely unclear. This study applied dynamic functional network connectivity (dFNC) analysis to investigate functional patterns in the temporal and spatial domains of various functional systems in FLE. Resting-state fMRI data were acquired from 19 FLE patients and 18 controls. Independent component analysis was used to decompose RSNs, which were grouped into seven functional systems. Sliding windows and clustering approach were used to identify the dFNC patterns. Then, state-specific connectivity pattern and dynamic functional state interactions (dFSIs) were evaluated. Compared with healthy controls, FLE patients exhibited decreased dFNC in almost all four patterns, changes that were mostly related to the frontoparietal system, suggesting a disturbed communication of the frontoparietal system with other systems in FLE. Additionally, regarding the fundamental connectivity pattern (state 3 in this study), FLE showed decreased time spent in this state. Moreover, the duration positively correlated with seizure onset. Furthermore, significantly reduced dynamic connections in this state were observed in the frontoparietal system linked to the cerebellar and subcortical systems. These findings imply abnormal fundamental dynamic interactions and dysconnectivity associated with the subcortical and cerebellar regulation of dysfunctions in frontoparietal regions in FLE. Finally, based on the developed FSI analysis, temporal dynamic abnormalities among states were observed in FLE. Therefore, this altered dynamic FNC extended our understanding of the abnormalities in the frontoparietal system in FLE. The dynamic FNC provided novel insight into the fundamental pathophysiological mechanisms in FLE.
额叶癫痫最近被认为与大脑功能连接中断有关；不同静息态网络（RSN）随时间的变化在很大程度上仍不清楚。本研究应用动态功能网络连接（dFNC）分析来研究额叶癫痫中各种功能系统在时间和空间域的功能模式。从19例额叶癫痫患者和18名对照者获取静息态功能磁共振成像数据。使用独立成分分析来分解RSN，将其分为七个功能系统。采用滑动窗口和聚类方法来识别dFNC模式。然后，评估特定状态的连接模式和动态功能状态相互作用（dFSI）。与健康对照相比，额叶癫痫患者在几乎所有四种模式下的dFNC均降低，这些变化大多与额顶叶系统有关，提示额叶癫痫中额顶叶系统与其他系统的通信受到干扰。此外，关于基本连接模式（本研究中的状态3），额叶癫痫患者在该状态下花费的时间减少。而且，该持续时间与癫痫发作起始呈正相关。此外，在与小脑和皮质下系统相连的额顶叶系统中观察到该状态下动态连接显著减少。这些发现意味着额叶癫痫中额顶叶区域功能障碍的皮质下和小脑调节存在异常的基本动态相互作用和连接障碍。最后，基于所开发的FSI分析，在额叶癫痫中观察到不同状态之间的时间动态异常。因此，这种改变的动态FNC扩展了我们对额叶癫痫中额顶叶系统异常的理解。动态FNC为额叶癫痫的基本病理生理机制提供了新的见解。
