Simplified, Scalable, 24-hour Adaptive DBS in Parkinson's Disease

Overview

The purpose of this study is to test a new way to treat Parkinson's disease (PD). Subjects will be implanted with deep brain stimulator (DBS) devices and electrodes placed under the scalp. The main questions it aims to answer are: * Is there a less invasive method to collect useful brain signals? Find out if these brain signals can be related to movement and/or sleep symptoms. * How to use these brain signals to tailor adaptive deep brain stimulation settings for movement and/or sleep symptoms Researchers will compare study derived adaptive DBS settings to subject's clinically programmed continuous DBS settings to see which is better at treating patients PD symptoms.

Parkinson's disease (PD) affects 1% of people over 60 years old, is highly disabling and represents a large economic burden. Therapeutic options include dopaminergic replacement and conventional DBS (cDBS) for advanced disease. However, cDBS therapy is currently unresponsive to the dynamic clinical states of patients, resulting in suboptimal control of symptoms during the day. Adaptive DBS (aDBS) seeks to solve this through personalized dynamic modulation of stimulation according to neural signals. Early studies of aDBS (completed by Drs Little, Starr and other research groups) provide proof-of-principle that aDBS can improve motor symptoms and reduce side-effects. Our team has also tested fully embedded, chronic naturalistic aDBS in a randomized, blinded study to show improvements in daytime motor symptoms and quality of life compared to cDBS. Further, the investigators have also recently validated sleep stage specific Non Rapid Eye Movement (NREM) aDBS, that increased cortical slow waves (linked to slowed disease progression). However, full leveraging of these highly promising therapies is currently limited by: 1) Lack of practical (minimally invasive) methods for chronic cortical recordings. 2) Complexity of programming aDBS due to a large parameter space. 3) Fluctuations in neural signals on multiple time scales, including circadian changes and long-term non-stationarity of signals. Our long-term goal is to advance aDBS from specialist research laboratories to real-world clinics through efficient, scalable implementation with the following advances: 1) Reduce risk and complexity of chronic cortical sensing by placing cortical leads in the subgaleal space rather than inside the cranium. 2) Utilize machine learning (ML) and data-driven biomarker and optimization techniques to minimize aDBS programming complexity. 3) Optimize aDBS across the full 24hr cycle - including sleep, with methods for long-term updating of aDBS settings. The study device will be the rechargeable, sensing and aDBS enabled, newly commercially available Medtronic Percept RC DBS system; connected to subgaleal frontal cortex leads and to directional basal ganglia leads. Our UG3 stage will support regulatory approval for Percept RC subgaleal aDBS. In UH3- 1, the investigators will implant 24 PD patients, optimize cDBS, and identify subgroups for daytime and nighttime aDBS. In UH3-2 the investigators will obtain in-clinic and at-home daytime naturalistic neural recordings and perform a blinded evaluation of data-driven chronic aDBS versus cDBS, for treatment of daytime motor fluctuations. In UH3-3, the investigators will obtain in-clinic (sleep lab) and at-home nighttime naturalistic recordings and perform a blinded evaluation of chronic sleep aDBS versus cDBS, to improve NREM sleep duration and increase slow wave amplitude. The investigators anticipate that these techniques will be the basis for a simple "turnkey" aDBS controller, to enable widespread, simple, scaleable and personalized aDBS for the full 24 hr cycle in PD, and provide a rational foundation for adaptive neuromodulation in other neurological and psychiatric diseases.