Dynamic Alterations of Spontaneous Neural Activity in Parkinson's Disease: A Resting-State fMRI Study

• Published in: Frontiers in neurology 2019-10, Vol.10, p.1052-1052
• Main Authors: Zhang, Chao, Dou, Binru, Wang, Jiali, Xu, Kai, Zhang, Haiyan, Sami, Muhammad Umair, Hu, Chunfeng, Rong, Yutao, Xiao, Qihua, Chen, Nan, Li, Kuncheng
• Format: Article
• Language: English
• Subjects: amplitude of low-frequency fluctuations; dynamic brain activity; Neurology; Parkinson's disease; resting-state fMRI; support vector machine
• ISSN: 1664-2295; 1664-2295
• DOI: 10.3389/fneur.2019.01052

Objective: To investigate the dynamic amplitude of low-frequency fluctuations (dALFFs) in patients with Parkinson's disease (PD) and healthy controls (HCs) and further explore whether dALFF can be used to test the feasibility of differentiating PD from HCs. Methods: Twenty-eight patients with PD and 28 demographically matched HCs underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans and neuropsychological tests. A dynamic method was used to calculate the dALFFs of rs-fMRI data obtained from all subjects. The dALFF alterations were compared between the PD and HC groups, and the correlations between dALFF variability and disease duration/neuropsychological tests were further calculated. Then, the statistical differences in dALFF between both groups were selected as classification features to help distinguish patients with PD from HCs through a linear support vector machine (SVM) classifier. The classifier performance was assessed using a permutation test (repeated 5,000 times). Results: Significantly increased dALFF was detected in the left precuneus in patients with PD compared to HCs, and dALFF variability in this region was positively correlated with disease duration. Our results show that 80.36% ( p < 0.001) subjects were correctly classified based on the SVM classifier by using the leave-one-out cross-validation method. Conclusion: Patients with PD exhibited abnormal dynamic brain activity in the left precuneus, and the dALFF variability could distinguish PD from HCs with high accuracy. Our results showed novel insights into the pathophysiological mechanisms of PD.