Dysconnectivity of the parafascicular nucleus in Parkinson's disease: A dynamic causal modeling analysis

Abstract

Background: Recent animal model studies have suggested that the parafascicular nucleus has the potential to be an effective deep brain stimulation target for Parkinson's disease. However, our knowledge on the role of the parafascicular nucleus in Parkinson's disease patients remains limited.

Objective: We aimed to investigate the functional alterations of the parafascicular nucleus projections in Parkinson's disease patients.

Methods: We enrolled 72 Parkinson's disease patients and 60 healthy controls, then utilized resting-state functional MRI and spectral dynamic causal modeling to explore the effective connectivity of the bilateral parafascicular nucleus to the dorsal putamen, nucleus accumbens, and subthalamic nucleus. The associations between the effective connectivity of the parafascicular nucleus projections and clinical features were measured with Pearson partial correlations.

Results: Compared with controls, the effective connectivity from the parafascicular nucleus to dorsal putamen was significantly increased, while the connectivity to the nucleus accumbens and subthalamic nucleus was significantly reduced in Parkinson's disease patients. There was a significantly positive correlation between the connectivity of parafascicular nucleus-dorsal putamen projection and motor deficits. The connectivity from the parafascicular nucleus to the subthalamic nucleus was negatively correlated with motor deficits and apathy, while the connectivity from the parafascicular nucleus to the nucleus accumbens was negatively associated with depression.

Conclusion: The present study demonstrates that the parafascicular nucleus-related projections are damaged and associated with clinical symptoms of Parkinson's disease. Our findings provide new insights into the impaired basal ganglia-thalamocortical circuits and give support for the parafascicular nucleus as a potential effective neuromodulating target of the disease.

Keywords: Dynamic causal modeling; Motor deficits; Non-motor symptoms; Parafascicular nucleus; Parkinson's disease.