Investigation of symptom-specific functional connectivity patterns in Parkinson's disease

Abstract

Parkinson's disease (PD) is a complex neurodegenerative disease, characterized by pronounced heterogeneity in symptoms. This study investigates the functional connectivity (FC) patterns associated with distinct symptom clusters, aiming to elucidate the heterogeneity in PD and uncover the neural mechanisms underlying its motor and cognitive symptoms. Resting-state functional MRI (rs-fMRI) data from 55 non-demented PD patients and 24 healthy controls (HC) were used to perform seed-to-seed FC analyses. A clustering algorithm was applied to the cognitive and motor scores of all PD patients to generate relatively homogeneous symptomatic subgroups. PD patients exhibited a general decrease in FC within a network comprising the sensorimotor network (SMN) and the visual network (VN) regions. Symptom-based clustering revealed three relatively homogeneous subgroups, exhibiting a gradient pattern: patients with greater motor deficits showed significant disconnection within the SMN, whereas patients with greater visuospatial deficits exhibited reduced FC in an extended subnetwork, with pronounced disconnections between the VN and SMN areas. Our study demonstrated a notable disconnection between the SMN and VN, indicating impaired visual-motor integration in PD. Stronger disconnection within the SMN was associated with greater motor dysfunction, and stronger visual-sensorimotor disconnections were associated with greater visuospatial deficits. These findings suggest that at least two separate routes of functional disconnection may be responsible for the inhomogeneous symptom distribution in PD.