Neurobiology of disease · 2026
Disrupted dynamic brain network and its functional topological underpinning in essential tremor.
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Yuan Weijin, Duanmu Xiaojie, Zheng Qianshi, Zhou Cheng, Zeng Qingze, Zhu Zihao, Guo Tao, Wen Jiaqi, Wu Chenqing, Wu Haoting, Qin Jianmei, Fang Yuelin, Zhu Bingting, Wang Lifang, Zhu Ziyi, Yan Yaping, Tian Jun, Zhang Baorong, Zhao Guohua, Zhang Minming, Guan Xiaojun, Xu Xiaojun
Аннотация
BACKGROUND: Essential tremor (ET) is one of the most prevalent neurological diseases and is recognized as a disorder involving multiple neural network dysfunctions. Previous resting-state fMRI studies in ET ignored brain network important dynamic nature. This study aimed to investigate the alterations of dynamic functional connectivity (DFC) and its functional topology in ET.
METHODS: Resting-state fMRI data were collected from 144 ET and 131 normal controls (NC). Sliding-window approach with K-means clustering algorithm was used to identify dynamic functional states and graph theory analysis was performed to explore related topological organization of each state in ET.
RESULTS: Two distinct and switchable DFC states (State 1: "cerebrum-dominant" state, with hyperconnected functional architecture in cerebrum; State 2: "cerebellum-dominant" state, with higher functional independence in cerebellum) were identified. Compared to NC, higher fractional windows and longer mean dwell time of cerebellum-dominant state, and fewer state transitions were observed in ET. Higher fractional windows and longer dwell time of cerebellum-dominant state were correlated with more severe tremor. In the topological analysis, compared to NC, ET demonstrated decreased nodal degree centrality and nodal efficiency in cerebrum regions (e.g., orbital inferior frontal gyrus and temporal pole) within two states, but increased nodal betweenness centrality in cerebellum regions (e.g., Cerebellum Crus 2 and Vermis) within cerebellum-dominant state.
CONCLUSIONS: These findings revealed that ET was characterized by prolonged cerebellum-dominant state and disrupted functional topology within both states, providing novel insights for better understanding the fundamental neurobiological mechanisms in ET.
METHODS: Resting-state fMRI data were collected from 144 ET and 131 normal controls (NC). Sliding-window approach with K-means clustering algorithm was used to identify dynamic functional states and graph theory analysis was performed to explore related topological organization of each state in ET.
RESULTS: Two distinct and switchable DFC states (State 1: "cerebrum-dominant" state, with hyperconnected functional architecture in cerebrum; State 2: "cerebellum-dominant" state, with higher functional independence in cerebellum) were identified. Compared to NC, higher fractional windows and longer mean dwell time of cerebellum-dominant state, and fewer state transitions were observed in ET. Higher fractional windows and longer dwell time of cerebellum-dominant state were correlated with more severe tremor. In the topological analysis, compared to NC, ET demonstrated decreased nodal degree centrality and nodal efficiency in cerebrum regions (e.g., orbital inferior frontal gyrus and temporal pole) within two states, but increased nodal betweenness centrality in cerebellum regions (e.g., Cerebellum Crus 2 and Vermis) within cerebellum-dominant state.
CONCLUSIONS: These findings revealed that ET was characterized by prolonged cerebellum-dominant state and disrupted functional topology within both states, providing novel insights for better understanding the fundamental neurobiological mechanisms in ET.