Study on Brain Functional Network Characteristics of Parkinson’s Disease Patients Based on Beta Burst Period
10.16476/j.pibb.2024.0318
- VernacularTitle:基于beta爆发期的帕金森病患者脑功能网络特征研究
- Author:
Yu-Jie HAO
1
;
Shuo YANG
1
;
Shuo LIU
1
;
Xu LOU
1
;
Lei WANG
1
Author Information
1. Health Sciences and Biomedical Engineering College, Hebei University of Technology, Tianjin 300130, China
- Publication Type:Journal Article
- Keywords:
electroencephalogram;
brain functional network;
phase synchronization;
Parkinson’s disease
- From:
Progress in Biochemistry and Biophysics
2025;52(5):1279-1289
- CountryChina
- Language:Chinese
-
Abstract:
ObjectiveThe central symptom of Parkinson’s disease (PD) is impaired motor function. Beta-band electrical activity in the motor network of the basal ganglia is closely related to motor function. In this study, we combined scalp electroencephalography (EEG), brain functional network, and clinical scales to investigate the effects of beta burst-period neural electrical activity on brain functional network characteristics, which may serve as a reference for clinical diagnosis and treatment. MethodsThirteen PD patients were included in the PD group, and 13 healthy subjects were included in the healthy control group. Resting-state EEG data were collected from both groups, and beta burst and non-burst periods were extracted. A phase synchronization network was constructed using weighted phase lag indices, and the topological feature parameters of phase synchronization network were compared between the two groups across different periods and four frequency bands. Additionally, the correlation between changes in network characteristics and clinical symptoms was analyzed. ResultsDuring the beta burst period, the topological characteristic parameters of phase synchronization network in all four frequency bands were significantly higher in PD patients compared to healthy controls. The average clustering coefficient of the phase synchronization network in the beta band during the beta burst period was negatively correlated with UPDRS-III scores. In the low gamma band during the non-burst period, the average clustering coefficient of phase synchronization network was positively correlated with UPDRS and UPDRS-III scores, while UPDRS-III scores were positively correlated with global efficiency and average degree. ConclusionThe brain functional network features of PD patients were significantly enhanced during the beta burst period. Moreover, the beta-band brain functional network characteristics during the beta burst period were negatively correlated with clinical scale scores, whereas low gamma-band functional network features during the non-burst period were positively correlated with clinical scale scores. These findings indicate that motor function impairment in PD patients is associated with the beta burst period. This study provides valuable insights for the diagnosis of PD.
