Control Systems and Adaptive Neurostimulation in Deep Brain Stimulation (DBS) for Treatment-Resistant Obsessive-Compulsive Disorder (TR-OCD): Architecture, Brain-Sensing, and Closed-Loop Strategies
TL;DR
The integration of neural biomarkers, adaptive control algorithms, and connectomic DBS approaches is expected to establish the foundation for next-generation intelligent neuromodulation systems and support the implementation of precision psychiatry in the management of TR-OCD.
Abstract
Deep Brain Stimulation (DBS) is an implantable neuromodulation system that integrates electronic components, intracranial electrodes, and biological neural networks into a bioelectronic control system designed to therapeutically modulate brain activity. The development of DBS technology for treatment-resistant obsessive-compulsive disorder (TR-OCD) has evolved from a purely anatomical target-based stimulation approach toward the integration of system architecture, control strategies, and biomarker-driven adaptive neurostimulation. This narrative review examines the architecture of DBS systems, open-loop and closed-loop control strategies, brain-sensing technologies, neural biomarkers, and recent advances in adaptive neurostimulation for TR-OCD. The review was conducted through an appraisal of contemporary literature addressing the intersection of neuroscience, electrical engineering, and biomedical engineering in the implementation of DBS. The findings indicate that a DBS system comprises an implantable pulse generator (IPG), stimulation electrodes, signal transmission components, and target neural networks that collectively form a neuromodulation control system. Conventional DBS remains predominantly based on an open-loop paradigm, in which continuous stimulation is delivered according to predefined parameters without real-time neurophysiological feedback. In contrast, advances in brain-sensing technologies have enabled the recording of neural biomarkers, particularly local field potentials (LFPs), which serve as the foundation for the development of closed-loop DBS systems. These systems allow automatic adjustment of stimulation parameters through feedback-driven mechanisms, thereby offering the potential to enhance therapeutic efficacy, improve device energy efficiency, and facilitate personalized treatment. The integration of neural biomarkers, adaptive control algorithms, and connectomic DBS approaches is expected to establish the foundation for next-generation intelligent neuromodulation systems and support the implementation of precision psychiatry in the management of TR-OCD.