期刊
FRONTIERS IN NEUROSCIENCE
卷 14, 期 -, 页码 -出版社
FRONTIERS MEDIA SA
DOI: 10.3389/fnins.2020.573538
关键词
Parkinson’ s disease; depression; independent component analysis; triple-network model; resting state
资金
- National Natural Science Foundation of China [81471646]
- Natural Science Foundation of Hunan Province [14JJ2027, 2019JJ40450]
In this study, researchers investigated the differences in intra-network and inter-network brain connectivity in Parkinson's disease patients with and without depression. They found abnormal functional connectivity values within and between several large-scale networks in patients with Parkinson's disease and depression, suggesting that these network aberrations could serve as biomarkers for distinguishing between depressed and non-depressed Parkinson's disease patients.
Background Disturbance of networks was recently proposed to be associated with the occurrence of depression in Parkinson's disease (PD). However, the neurobiological mechanism of depression underlying PD remains unclear. Objective This study was conducted to investigate whether intra-network and inter-network brain connectivity is differently changed in PD patients with and without depression (PDD and PDND patients, respectively). Methods Forty-one PDD patients, 64 PDND patients, and 55 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (fMRI). The default mode network (DMN), executive control network (ECN), salience network (SN), precuneus network (PCUN), and sensorimotor network (SMN) were extracted using independent component analysis (ICA), and then the functional connectivity (FC) values within and between these networks were measured. Results PDD patients exhibited abnormal FC values within the DMN, ECN, SN, PCUN, and SMN. In addition, PDD patients demonstrated decreased connectivity between anterior SN (aSN) and bilateral ECN, between posterior SN (pSN) and dorsal DMN (dDMN), and between PCUN and dDMN/SMN/bilateral ECN. Connectivity within the left hippocampus of dDMN and the right medial superior frontal gyrus of aSN was a significant predictor of depression level in PD patients. Conclusions Aberrant intra- and inter-network FC is involved in several important hubs in the large-scale networks, which can be a biomarker for distinguishing PDD from PDND.
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