# Deep Brain Stimulation: Mechanisms, Cost-Effectiveness, and Precision Applications Across Neurology and Psychiatry

## TL;DR

Deep Brain Stimulation (DBS) is advancing from treating Parkinson's to a broader, personalized therapy in neurology and psychiatry, with a focus on cost-effectiveness and new technologies.

## Contribution

The paper reviews recent advancements in DBS, emphasizing new targets, adaptive technologies, and cost-effectiveness across neurological and psychiatric applications.

## Key findings

- DBS is expanding beyond Parkinson's to treat psychiatric and metabolic conditions like depression and anorexia nervosa.
- Rechargeable DBS devices show cost-effectiveness in treatment-resistant depression and OCD.
- New DBS targets and adaptive technologies like closed-loop systems are improving patient outcomes and personalization.

## Abstract

In less than 30 years, Deep Brain Stimulation (DBS) has evolved from an antiparkinsonian rescue intervention into a flexible neuromodulatory therapy with the potential for personalized, adaptive, and enhancement-focused interventions. In this review we collected evidence from seven areas: (i) modern eligibility criteria, and ways to practically improve on these, outside of ‘Core Assessment Program of Surgical Interventional Therapies in Parkinson’s Disease’ (CAPSIT-PD); (ii) cost-effectiveness, where long-horizon models now show positive incremental net monetary benefit for Parkinson’s disease, and rechargeable-devices lead the way in treatment-resistant depression and obsessive–compulsive disorder; (iii) anatomical targets, from canonical subthalamic nucleus (STN) / globus pallidus internus (GPi) sites, to new dual-node and cortical targets; (iv) mechanistic theories from informational lesions, antidromic cortical drive, and state-dependent network modulation made possible by optogenetics and computational modeling; (v) psychiatric and metabolic indications, and early successes in subcallosal and nucleus-accumbens stimulation for depression, obsessive–compulsive disorder (OCD), anorexia nervosa, and schizophrenia; (vi) procedure- and hardware-related safety, summarized through five reviews, showing that the risks were around 4% for infection, 4–5% for revision surgery, 3% for lead malposition or fracture, and 2% for intracranial hemorrhage; and (vii) future directions in connectomics, closed-loop sensing, and explainable machine learning pipelines, which may change patient selection, programming, and long-term stewardship. Overall, the DBS is entering a “third wave” focused on a better understanding of neural circuits, the integration of AI-based adaptive technologies, and an emphasis on cost-effectiveness, in order to extend the benefits of DBS beyond the treatment of movement disorders, while remaining sustainable for healthcare systems.