作者: Delong Zhang , Jinhui Wang , Xian Liu , Jun Chen , Bo Liu
关键词: Parkinson's disease 、 Magnetic resonance imaging 、 Network analysis 、 Neuroscience 、 Brain activity and meditation 、 Multivariate analysis 、 Psychology 、 Brain network 、 Local area network 、 Text mining
摘要: The coordination of spontaneous brain activity is widely enhanced relative to compensation in Parkinson’s disease (PD) with tremor; however, the associated topological organization remains unclear. Here, we collected magnetic resonance imaging (MRI) data from 16 patients and 20 matched normal controls (NCs) constructed wavelet-based functional morphological networks for individual participants. Graph-based network analysis indicated that information translation efficiency was disrupted within wavelet scale 2 (i.e., .063–.125 Hz) PD patients. Compared NCs, local decreased global increased Network could effectively discriminate NCs using multivariate pattern (MVPA), also describe variability tremor based on a multiple linear regression model (MLRM). However, these observations were not identified efficiency. Notably, both significantly Further showed performed well classifications MVPA) clinical performance descriptions MLRM). More importantly, highly terms These findings provide comprehensive view disorganization have important implications understanding neural substrates underlying this specific type PD.