ArticleFrontiers in neuroscience2025
Individualized cortico-basal ganglia network effective connectivity predicts outcomes of STN-DBS in patients with Parkinson's disease.
Article in Frontiers in neuroscience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for Parkinson's disease (PD) patients. However, postoperative outcomes vary with no reliable predictive method. Methods: Our study involves 43 PD patients undergoing STN-DBS. Preoperative resting-state functional magnetic resonance imagings (rs-fMRI) were collected. The volume of tissue activated (VTA) was defined based on contact points and stimulation parameters. A model of the cortico-basal ganglia network was established using dynamic causal modeling. The correlation between the UPDRS-III and the network edges was determined through Pearson correlation analysis. Furthermore, a generalized linear model was employed to predict the post-DBS motor improvement. Results: Individual STN-VTA intersections were found to be important to UPDRS-III improvement induced by DBS (R = 0.59, Conclusion: Our study confirmed the relationship between clinical improvements in STN-DBS and target location as well as the stimulation parameters. By constructing personalized cortical-basal ganglia network models based on target location as well as the stimulation parameters, we discovered that the effective connection strength in STN-THA-M1 can predict motor improvement in PD patients undergoing STN-DBS.
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