Changes of dynamic functional brain network connectivity in Parkinson disease patients based on Hidden Markov model
10.3760/cma.j.cn371468-20240829-00395
- VernacularTitle:帕金森病患者动态功能脑网络连接改变的隐马尔科夫模型研究
- Author:
Changhui LI
1
;
Hang QU
;
Yu PAN
;
Wei WANG
;
Yi ZHAO
Author Information
1. 扬州大学附属医院影像科，扬州 225000
- Keywords:
Parkinson disease;
Hidden Markov model;
Dynamic functional brain network connectivity;
Functional magnetic resonance imaging
- From:
Chinese Journal of Behavioral Medicine and Brain Science
2024;33(9):790-795
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the changes of dynamic functional brain network connectivity in patients with Parkinson disease(PD) using Hidden Markov model(HMM), and to analyze the correlation between dynamic functional parameters and clinical parameters.Methods:Forty-eight PD patients(PD group) and thirty-three healthy controls(HC group) were included from 2019 to 2023. The cognitive function was assessed using the Montreal cognitive assessment (MoCA), and motor status was assessed using the unified Parkinson's disease rating scale Ⅲ(UPDRS-Ⅲ) in PD group.HMM technique was used to analyze the dynamic functional brain network connectivity, and the dynamic higher-order index fractional occupancy(FO), switching rate(SR), and mean dwell time(MDT) were obtained. Two independent samples t-test was used to calculate the differences between groups of functional connectivity matrices in different states, and Mann-Whitney U test was used to calculate the differences between groups of dynamic higher-order indicators in different states. Spearman correlation analysis was used to calculate the correlation between dynamic higher-order parameters and clinical parameters in the PD group. Results:The HMM was used to construct 6 spatial states for all subjects.MDT was significantly higher in PD group(24.93(19.73)) in state 1 sparse junctions than that in HC group(17.63(14.80)) ( Z=-2.030, P=0.042), but significantly lower MDT was showed in PD group(6.00(3.00)) in state 5 tight junctions than that in HC group(9.75(7.70)) ( Z=-2.210, P=0.027).FO in state 3 was negatively correlated with MoCA score in PD group( r=-0.331, P=0.022).FO in state 5 was positively correlated with UPDRS-Ⅲ score in PD patients( r=0.412, P=0.004), and MDT in state 5 was positively correlated with UPDRS-Ⅲ score( r=0.448, P=0.001). Conclusion:HMM can capture the transient changes of dynamic brain network, which can provide some value for the study of dynamic brain network in patients with Parkinson disease.
