Functional connectivity-based searchlight multivariate pattern analysis for discriminating Parkinson’s disease patients and predicting clinical variables

This study introduces a novel approach for identifying distributed FC subnetworks patterns relevant to PD and PD-MCI. While predictive performance was modest, the detected subnetworks nonetheless contained measurable predictive signals related to both diagnostic status and clinical severity, highlighting the potential utility of whole-brain multivariate FC analyses for future mechanistic research and therapeutic interventions in PD.