Altered functional connectivity in inter-effector and effector-specific subregions of the primary motor cortex in...

Parkinson's disease (PD) involves large-scale network disruptions, yet functional connectivity (FC) alterations specific to distinct primary motor cortex (M1) subregions and their subcortical targets remain poorly characterized. We aimed to investigate subregion-specific resting-state FC alterations in PD and their clinical associations.

Resting-state fMRI data from 37 PD patients and 37 matched healthy controls were analyzed. Seed-to-voxel and expanded ROI-to-ROI analyses (incorporating subcortical nuclei) mapped FC patterns of two M1 subregions: inter-effector and effector-specific. A System Segregation index quantitatively assessed large-scale network boundaries.

PD patients exhibited local intra-M1 hyperconnectivity and subsystem-specific cortico-subcortical hyperconnectivity, particularly involving the putamen and thalamus for the effector-specific region. Seed-to-voxel analyses revealed divergent long-range dysconnectivity: the inter-effector region showed hypoconnectivity with sensorimotor and limbic areas, whereas the effector-specific region exhibited sensorimotor hypoconnectivity and a pathological loss of anti-correlation with cerebellar and frontoparietal networks. Quantitative evaluation confirmed a significant collapse in the System Segregation index, validating network boundary breakdown. Clinically, inter-effector hypoconnectivity to the right Rolandic operculum correlated with freezing of gait severity, while aberrant effector-specific-cerebellar positive FC correlated with tremor severity.

This study delineates a multilayered network pathology in PD, involving local hyperconnectivity, cortico-subcortical desegregation, and quantitatively verified impairment of large-scale network segregation. These subregion-specific alterations, particularly maladaptive cortico-cerebellar and cortico-striatal coupling, reframe PD as a disorder of network dedifferentiation, highlighting M1 subcircuits as targets for symptom-specific neuromodulation.