Altered Functional Connectivity of the Subthalamic Nucleus in Parkinson's Disease and Implications for Deep Brain Stimulation

Introduction: The subthalamic nucleus (STN) is a critical target in deep brain stimulation (DBS) for Parkinson’s disease (PD), as its connectivity patterns influence motor and non-motor symptoms. Alterations in STN connectivity in PD patients may impact the efficacy of DBS and guide patient selection for optimal outcomes. This study examines functional connectivity differences in the STN between DBS candidates and non-candidates to identify connectivity markers associated with DBS suitability.

Methods: Using resting-state functional MRI (fMRI) data from 60 PD patients, divided into DBS candidates and non-candidates, we analyzed functional connectivity patterns of the STN. Python was employed for data preprocessing, including motion correction and spatial normalization, while R facilitated statistical modeling of connectivity differences. Seed-based connectivity analysis identified regions with altered connectivity to the STN in DBS candidates, with group comparisons assessing the impact of connectivity strength on motor symptom severity.

Results: DBS candidates showed reduced connectivity between the STN and bilateral sensorimotor cortex compared to non-candidates (p < 0.05), with additional connectivity increases in thalamic and cerebellar circuits. Altered STN connectivity correlated significantly with motor rigidity and bradykinesia scores, where weaker sensorimotor-STN connectivity was associated with greater symptom severity. Enhanced cerebellar connectivity in candidates suggested compensatory mechanisms relevant to DBS response.

Conclusion : This study reveals distinct functional connectivity profiles in the STN of PD patients, with reduced STN-sensorimotor cortex connectivity emerging as a marker for DBS candidacy. The findings underscore the importance of connectivity-based criteria in patient selection, as well as potential avenues for optimizing DBS programming to target connectivity alterations. Leveraging Python and R for rigorous connectivity analysis, this research offers a framework for refining DBS strategies based on individualized brain network profiles.