Institute of Biomedical Engineering and Nanomedicine, National Health Research Institutes, Miaoli, Taiwan.
Department of Neurology, Ditmanson Medical Foundation Chia-Yi Christian Hospital, Chia-Yi, Taiwan.
Brain Connect. 2024 Sep;14(7):382-390. doi: 10.1089/brain.2024.0004. Epub 2024 Jul 25.
Essential tremor (ET) comprises motor and non-motor-related features, whereas the current neuro-pathogenetic basis is still insufficient to explain the etiologies of ET. Although cerebellum-associated circuits have been discovered, the large-scale cerebral network connectivity in ET remains unclear. This study aimed to characterize the ET in terms of functional connectivity as well as network. We hypothesized that the resting-state network (RSN) within cerebrum could be altered in patients with ET. Resting-state functional magnetic resonance imaging (fMRI) was used to evaluate the inter- and intra-network connectivity as well as the functional activity in ET and normal control. Correlation analysis was performed to explore the relationship between RSN metrics and tremor features. Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group ( < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs ( < 0.05). The ET group generally has higher degree centrality over normal control. Correlation analysis has revealed that tremor features are associated with inter-network connectivity (|r| = 0.135-0.506), ALFF (|r| = 0.313-0.766), and degree centrality (|r| = 0.523-0.710). Alterations in the cerebral network of ET were detected by using resting-state fMRI, demonstrating a potentially useful approach to explore the cerebral alterations in ET.
特发性震颤（ET）包括运动和非运动相关的特征，而目前的神经发病机制基础仍不足以解释 ET 的病因。虽然已经发现了与小脑相关的回路，但 ET 中的大规模大脑网络连接仍不清楚。本研究旨在从功能连接和网络的角度来描述 ET。我们假设 ET 患者的大脑静息状态网络（RSN）可能会发生改变。使用静息态功能磁共振成像（fMRI）来评估 ET 和正常对照组的网络间和网络内连接以及功能活动。进行相关性分析以探讨 RSN 指标与震颤特征之间的关系。网络间连接的比较表明 ET 组默认模式网络和腹侧注意网络之间的连接减少（<0.05）。参与各种 RSN 的几个脑区的功能活动（通过低频波动幅度评估，ALFF）存在差异（<0.05）。ET 组的节点度普遍高于正常对照组。相关性分析表明，震颤特征与网络间连接（|r|=0.135-0.506）、ALFF（|r|=0.313-0.766）和节点度（|r|=0.523-0.710）相关。使用静息态 fMRI 检测到 ET 的大脑网络改变，这表明这是一种探索 ET 大脑改变的潜在有用方法。
