Research on dynamic functional connectivity and graph theoretic features of different motor subtypes in Parkinson's disease based on ICA

Objective

This study combined independent component analysis (ICA)-derived dynamic functional connectivity (dFNC) with dynamic graph theory analysis methods to analyze the changes in dFNC and dynamic graph theoretic indicators in different motor subtypes of Parkinson's disease (PD)-tremor-dominant (TD) subtype and postural instability/gait difficulty (PIGD) subtype-and healthy controls (HC). We aimed to explore the neural circuitry abnormal mechanisms and differences between the two subtypes.