Open AccessCharacterizing resting‐state networks in Parkinson’s disease: A multi‐aspect functional connectivity study
Author(s) -
Ghasemi Mahdieh,
Foroutannia Ali,
BabajaniFeremi Abbas
Publication year - 2021
Publication title -
brain and behavior
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.915
H-Index - 41
ISSN - 2162-3279
DOI - 10.1002/brb3.2101
Subject(s) - default mode network , resting state fmri , independent component analysis , functional magnetic resonance imaging , voxel , hierarchical clustering , neuroscience , cluster analysis , functional connectivity , pattern recognition (psychology) , medicine , computer science , psychology , artificial intelligence
Purpose Resting‐state functional magnetic resonance imaging (Rs‐fMRI) can be used to investigate the alteration of resting‐state brain networks (RSNs) in patients with Parkinson's disease (PD) when compared with healthy controls (HCs). The aim of this study was to identify the differences between individual RSNs and reveal the most important discriminatory characteristic of RSNs between the HCs and PDs. Methods This study used Rs‐fMRI data of 23 patients with PD and 18 HCs. Group independent component analysis (ICA) was performed, and 23 components were extracted by spatially overlapping the components with a template RSN. The extracted components were used in the following three methods to compare RSNs of PD patients and HCs: (1) a subject‐specific score based on group RSNs and a dual‐regression approach (namely RSN scores); (2) voxel‐wise comparison of the RSNs in the PD patient and HC groups using a nonparametric permutation test; and (3) a hierarchical clustering analysis of RSNs in the PD patient and HC groups. Results The results of RSN scores showed a significant decrease in connectivity in seven ICs in patients with PD compared with HCs, and this decrease was particularly striking on the lateral and medial posterior occipital cortices. The results of hierarchical clustering of the RSNs revealed that the cluster of the default mode network breaks down into the three other clusters in PD patients. Conclusion We found various characteristics of the alteration of the RSNs in PD patients compared with HCs. Our results suggest that different characteristics of RSNs provide insights into the biological mechanism of PD.