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Resting-State Network Analysis Reveals Altered Functional Brain Connectivity in Essential Tremor.

Sheng-Min HuangCheung-Ter OngYu-Ching HuangNan-Hao ChenTing-Kai LeungChun-Ying ShenLi-Wei Kuo
Published in: Brain connectivity (2024)
Introduction: 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. Methods: 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. Results: Comparison of inter-network connectivity indicated a decreased connectivity between default mode network and ventral attention network in the ET group ( p < 0.05). Differences in functional activity (assessed by amplitude of low-frequency fluctuation, ALFF) were found in several brain regions participating in various RSNs ( p < 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). Conclusion: 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.
Keyphrases
  • resting state
  • functional connectivity
  • network analysis
  • magnetic resonance imaging
  • deep brain stimulation
  • parkinson disease
  • computed tomography
  • magnetic resonance
  • spinal cord injury
  • single cell