Treatment Enhances Betweenness Centrality of Fronto-Parietal Network in Parkinson’s Patients

Qing Liu, Zhong Yan Shi, Kexin Wang, Tiantian Liu, Shintaro Funahashi, Jinglong Wu, Jian Zhang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


Previous studies have demonstrated a close relationship between early Parkinson’s disease and functional network abnormalities. However, the pattern of brain changes in the early stages of Parkinson’s disease has not been confirmed, which has important implications for the study of clinical indicators of Parkinson’s disease. Therefore, we investigated the functional connectivity before and after treatment in patients with early Parkinson’s disease, and further investigated the relationship between some topological properties and clinicopathological indicators. We included resting state-fMRI (rs-fMRI) data from 27 patients with early Parkinson’s disease aged 50–75 years from the Parkinson’s Disease Progression Markers Initiative (PPMI). The results showed that the functional connectivity of 6 networks, cerebellum network (CBN), cingulo_opercular network (CON), default network (DMN), fronto-parietal network (FPN), occipital network (OCC), and sensorimotor network (SMN), was significantly changed. Compared to before treatment, the main functional connections were concentrated in the CBN after treatment. In addition, the coefficients of these nodes have also changed. For betweenness centrality (BC), the FPN showed a significant improvement in treatment (p < 0.001). In conclusion, the alteration of functional networks in early Parkinson’s patients is critical for clarifying the mechanisms of early diagnosis of the disease.

Original languageEnglish
Article number891384
JournalFrontiers in Computational Neuroscience
Publication statusPublished - May 26 2022
Externally publishedYes


  • Parkinson’s disease
  • fronto_parietal network
  • functional connectivity
  • graph theory
  • resting state-fMRI

ASJC Scopus subject areas

  • Neuroscience (miscellaneous)
  • Cellular and Molecular Neuroscience


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