DBS therapy for Parkinson Disease [PD], the primary, FDA-approved surgical approach, has proven efficacious in clinical trials. However, this continuous stimulation therapy is limited to treatment of a subset of motor symptoms (i.e., tremor, rigidity, bradykinesia and dyskinesias) and requires considerable postoperative clinical adjustment to treat symptoms. Improvements to DBS for PD are being tested, including changes in patterns of stimulation, additional targets, and multiple electrodes. However, a critical new approach involves autonomous parameter adjustment [adaptive DBS] using surrogate physiological biomarkers relevant to clinical symptoms. These biomarkers and autonomous control may be useful for dynamic adjustment, subsequent programming, and long-term optimization of parameters. Adaptive DBS involves recording surrogate signals and developing a control policy that relates these signals to activity through parameter adjustments. This approach could improve DBS therapy across multiple time scales, including short-term dynamics (i.e., over minutes), initial programming (over weeks to months), and long-term, depending on the time course of response to DBS. However, which biomarkers are useful at these various time scales and appropriate, multi- layered control policy, will require testing in comparison to continuous DBS for relative efficacy and efficiency. We hypothesize that integrating multiple biomarkers (in addition to beta band oscillations) across multiple time scales will provide more efficacious adaptive DBS control. To test this hypothesis we will perform long-term recordings of multiple, relevant biomarkers from humans with implanted, advanced implantable pulse generators [IPGs], comparing internal control modes to highly complex external control modes. These clinical experiments will focus on a small, pilot clinical study (n = 6 PD patients) who have undergone implantation of bilateral subthalamic nucleus [STN] and globus pallidus [GP] DBS electrodes, with all 4 electrodes connected to a single Medtronic Summit RC+S recording and stimulating IPG. We have formally analyzed this cohort for efficacy at 1 year, showing that combined STN + GP stimulation is both preferred and better compared to either site alone. We will analyze the comparative efficacy of internal (embedded, available within the IPG) simple adaptive DBS to external (distributed) adaptive DBS, which allows both integrating multiple biomarkers and using a complex, multiple time scale control policy. We will further develop a proportional control feedback program, which specifically integrates the time multiple time constants of PD symptoms, to optimally control PD symptom. These clinical experiments in a unique cohort of research patients will lead to multiple novel outcomes, continuing a direct, within-person comparison of STN, GP, and combined DBS efficacy, analyzing an optimal mix of surrogate biomarkers for enhancing DBS efficacy, and defining an optimal, scalar feedback, proportional control system for treatment on various time scales.

This project seeks to help people with severe Parkinson disease improve their treatment options and therapy through novel approaches including both dual deep brain stimulation electrode treatment and advanced closed loop medical device technology. The adaptive control of Parkinson symptoms will be based on local field potentials, internal and external accelerometers, and wearable measurement devices. These studies will make important contributions to public health, building upon rapid advances in technology to give subjects improved surgical and symptomatic therapy for a common illness, Parkinson disease. Additionally, this clinical research will also help improve our understanding of how a combination of intrinsic brain signals and wearable device information can be used as part of a novel surgical treatment to provide better clinical solutions to the affected subjects through automatic, dynamic device adjustments.