A multicenter crossover study is proposed for adults with levodopa-responsive Parkinson’s disease and motor fluctuations despite optimized conventional stimulation, which combines blinded motor-state improvement with reduced troublesome dyskinesia and off time.
Abstract
AbstractBackground. Conventional deep brain stimulation provides continuous therapy for Parkinson’s disease, but fixed stimulation cannot accommodate medication cycles, sleep–wake transitions, gait freezing, dyskinesia, or biomarker drift. Adaptive deep brain stimulation offers closed- loop neuromodulation by adjusting stimulation according to sensed neural or behavioral signals.Materials and methods. A structured narrative review used randomized and nonrandomized trials, prospective cohorts, documents, neurophysiological studies, and investigations published through July 2026. Evidence was organized by biomarker validity, control architecture, programming feasibility, effectiveness, safety, energy efficiency, generalizability, and human-factor integration. A multicenter crossover study is proposed for adults with levodopa-responsive Parkinson’s disease and motor fluctuations despite optimized conventional stimulation.Results. Subthalamic beta amplitude and beta-burst duration remain the most mature control variables, whereas stimulation-entrained gamma activity, cortical signals, wearable-derived gait events, and multimodal decoders may better capture dyskinesia, freezing, and naturalistic behavior. Chronic studies suggest that personalized adaptive stimulation can improve residual motor symptoms and quality of life, while gait-synchronized and activity-dependent paradigms may address axial disability. Major limitations include sensing artifacts, unstable biomarkers, heterogeneous programming, small samples, insufficient blinding, and limited evidence regarding cognition, speech, falls, and device burden. The proposed primary endpoint combines blinded motor-state improvement with reduced troublesome dyskinesia and off time. Secondary endpoints include falls, gait freezing, speech, cognition, quality of life, stimulation energy, programming time, adverse events, calibration, and subgroup performance.Conclusion. Adaptive deep brain stimulation is transitioning from experimental physiology to regulated clinical therapy. Its durable value will depend on biomarker personalization, transparent algorithms, standardized outcomes, and independent multicenter validation.Keywords: Parkinson’s disease, adaptive deep brain stimulation, closed-loop neuromodulation, beta oscillations, local field potentials, gait freezing, neural biomarkers, personalized neurostimulation.
Parkinson's disease (PD) involves not only dopaminergic degeneration but also pathological changes in cortico-basal ganglia-thalamocortical circuits and broader disease-relevant biological processes. Deep-brain neuromodulation has emerged as an important therapeutic strategy for motor dysfunction. Among the available approaches, deep brain stimulation (DBS) is the most established modality, whereas low-intensity focused ultrasound (LIFUS), a form of transcranial ultrasound stimulation, represents a promising but earlier-stage, non-invasive platform. This review discusses DBS and LIFUS from a shared mechanistic and translational perspective. Current evidence suggests that the two modalities may engage partially overlapping mechanistic domains associated with motor deficit improvement, including modulation of abnormal network activity, promotion of synaptic and axonal remodeling, attenuation of neuroinflammation and cellular stress, and possible interaction with α-synuclein-related pathology. At the same time, they differ substantially in evidentiary depth, clinical maturity and translational readiness. DBS remains the clinical benchmark, with durable motor benefits and an expanding mechanistic framework that now extends beyond circuit correction to neurotrophic, proteinopathic, neuroimmune and adaptive biomarker-guided mechanisms. By contrast, LIFUS offers non-invasive access to deep brain targets and shows encouraging pre-clinical effects on inflammation, apoptosis, synaptic integrity and neurovascular function, but its clinical evidence remains limited. Overall, deep-brain neuromodulation in PD should be viewed as a multi-dimensional therapeutic framework rather than a group of isolated technologies. Future progress will depend on tighter integration of circuit physiology, pathology-relevant biomarkers, model selection and standardized translational endpoints.
Jin Peng, Yu Liu, Xiaohui Wang· Ultrasound in Medicine and B...· 0 citations
Deep brain stimulation is an established treatment for Parkinson's disease but does not adapt to dynamic changes in brain state. Here, in four patients with sensing-enabled DBS systems, we evaluated a movement-responsive DBS (mDBS) paradigm that modulated subthalamic stimulation based on volitional motion decoded from cortical activity. During structured motor tasks, mDBS improved average forearm speed and mitigated the progressive bradykinetic slowing observed under constant-amplitude DBS (cDBS), accompanied by a cumulative increase in sensorimotor cortical beta activity and connectivity. In unconstrained, daily activities, mDBS lowered average bradykinesia severity and demonstrated progressive symptom reduction over hours of therapy, which gradually reversed upon switching to cDBS. These findings highlight the enhanced therapeutic benefit of mDBS and its potential to reinforce functional motor circuits in disorders of movement.
D. Lawrence, J. Suh, V. Chang et al.· medRxiv· 0 citations
Recent studies show that pallidal and subthalamic local field potentials (LFPs) encode locomotor state and can guide adaptive deep brain stimulation (DBS) for gait impairment in Parkinson's disease. Here, in one participant implanted with the Picostim DyNeuMo-2c, we demonstrate a simpler and more direct approach for inferring locomotor state using the device's onboard accelerometer. Triaxial acceleration was classified independently on each axis to select among preconfigured stimulation programs. Using a cranially mounted digital twin, we characterized inertial signatures across medication and activity states, developed a classifier that distinguished walking from rest while rejecting tremor, and verified the intended stimulation switches during walking. In an exploratory comparison, a gait-adaptive program improved objective gait measures relative to open-loop stimulation optimised for resting tremor. These findings provide a first-in-human demonstration of the feasibility of device-embedded inertial sensing for gait-responsive DBS. They establish a practical framework for further evaluation in larger cohorts.
A. Oswal, S. Santoloce, M. Zamora et al.· medRxiv· 0 citations
Volitional DBS (vDBS)--a paradigm in which patients use brain-computer interface (BCI) training to learn self-regulation of a neural signal that then controls closed-loop DBS)--is demonstrated, establishing that volitional control of intracranial neurostimulation is achievable without the need of an externalized manual controller.
J.-X. Zhang, J. Suh, P. Daniel et al.· medRxiv· 0 citations
This review provides a comprehensive synthesis of TI's mechanistic foundations, safety profiles, and therapeutic trajectory, while critically discussing the integration of closed-loop systems, multi-target paradigms, and patient-specific optimization as the next frontiers in non-invasive deep brain stimulation.
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.
Hedya Nadhrati Surura, Rina Hastuti Lubis, Nashrul Fazli Mohd Nasir et al.· JET (Journal of Electrical T...· 0 citations
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