Antagonistic network signature of motor function in Parkinson's disease revealed by connectome-based predictive modeling.

ABSTRACT: Motor impairment is a core clinical feature of Parkinson's disease (PD). Although the decoupled brain connectivity has been widely reported in previous neuroimaging studies, how the functional connectome is involved in motor dysfunction has not been well elucidated in PD patients. Here we developed a distributed brain signature by predicting clinical motor scores of PD patients across multicenter datasets (total n = 236). We decomposed the Pearson's correlation into accordance and discordance via a temporal discrete procedure, which can capture coupling and anti-coupling respectively. Using different profiles of functional connectivity, we trained candidate predictive models and tested them on independent and heterogeneous PD samples. We showed that the antagonistic model measured by disco

SUBMITTER: Wang X 

PROVIDER: S-EPMC9033778 | biostudies-literature | 2022 Apr

REPOSITORIES: biostudies-literature