Altered Dynamic Functional Connectivity in de novo Parkinson’s Disease Patients With Depression - Xu, Jianxia; Yu, Miao; Wang, Hui; Li, Yuqian; Li, Lanting; Ren, Jingru; Pan, Chenxi; Liu, Weiguo (Frontiers in Aging Neuroscience, 2022)
Background: Depression is one of the most prevalent and disturbing non-motor symptoms in Parkinson’s disease (PD), with few dynamic functional connectivity (dFC) features measured in previous studies. Our aim was to investigate the alterations of the dynamics in de novo PD patients with depression. Methods: We performed dFC analysis on the data of resting state functional magnetic resonance imaging from 21 de novo PD patients with depression (dPD), 34 de novo PD patients without depression (ndPD), and 43 healthy controls (HCs). Group independent component analysis, a sliding window approach followed by k-means clustering were conducted to assess functional connectivity states (which represented highly structured connectivity patterns reoccurring over time), and temporal properties for comparison between groups. We further performed dynamic graph-theoretical analysis to examine variability of topological metrics. Results: Four distinct functional connectivity states were clustered via dFC analysis. Compared to ndPD patients and HCs, dPD patients showed increased fractional time and mean dwell time in state 2, characterized by default mode network (DMN)-dominated and cognitive executive network (CEN)-disconnected patterns. Besides, compared to HCs, dPD patients and ndPD patients both showed weaker dynamic connectivity within the sensorimotor network (SMN) in state 4, a regionally densely connected state. We additionally observed that dPD patients presented less variability in the local efficiency of network. Conclusions: Our study demonstrated that altered network connection over time, mainly involving the DMN and CEN, with abnormal dynamic graph properties may contribute to the presence of depression in patients with PD.