Optimal Stimulation Sites and Connectomes for GPi and STN-DBS in Cervical Dystonia

Abstract

Aims: To map optimal stimulation targets (sweet spots) and neural networks for globus pallidus internus (GPi)- and subthalamic nucleus (STN)-deep brain stimulation (DBS) in cervical dystonia (CD), and compare their structural/functional connectivity profiles and predictive validity for clinical outcomes.

Methods: Retrospective analysis of 76 stimulation settings from 38 CD patients across four centers. Volume of tissue activated was reconstructed; connectivity-based sweet spots were identified. Structural/functional connectivity models were developed using normative connectomes and validated externally. Clinical outcomes were assessed using validated scales.

Results: Optimal targets localized to the posterior ventral medial GPi and dorsolateral STN. The ideal probabilistic stimulation maps of STN-DBS exhibited predictive clinical improvement. Both targets showed beneficial connections to the motor cortex, with GPi-DBS negatively connected to the occipital lobe and STN-DBS positively connected to the premotor cortex and cerebellum. Functional connectivity patterns further highlighted shared and distinct regions linked to CD symptoms. Moreover, the structural and functional connectivity models predicted postoperative improvement through internal and external validation.

Conclusion: GPi- and STN-DBS engage distinct but overlapping networks in CD. Connectivity-based models robustly predict clinical improvement, offering tools for personalized targeting and programming. These findings clarify network mechanisms of DBS in dystonia and advance precision neuromodulation strategies.