Optimizing Adaptive DBS for Parkinson's Disease

Parkinson's disease (PD) affects more than 10 million people worldwide and causes progressive motor symptoms such as slowness, stiffness and tremor. For patients whose symptoms are no longer adequately controlled with medication, deep brain stimulation (DBS) can substantially improve motor function. More recently, adaptive DBS (aDBS) has become available. Unlike conventional DBS, which delivers continuous stimulation, aDBS automatically adjusts stimulation in response to brain activity recorded by the implanted device. Current clinical aDBS programming is based primarily on brief recordings obtained during clinic visits. However, Parkinson's symptoms and the underlying brain signals change throughout the day in response to medication, daily activities and other factors. As a result, recordings collected during a single clinic visit may not fully capture the neural activity that best reflects a patient's symptoms in everyday life. The purpose of this study is to determine whether incorporating long-term brain recordings collected during daily life improves adaptive DBS programming and clinical outcomes. Participants will first undergo in-clinic testing to identify brain signals associated with their symptoms. Brain activity and symptoms will then be monitored during everyday life using the sensing capabilities of the implanted DBS device. Participants with suitable brain signals will enter a randomized, blinded crossover study comparing three stimulation approaches: conventional continuous DBS, adaptive DBS programmed using the current clinic-based approach and adaptive DBS programmed using both clinic and at-home recordings. The study will compare the effects of these approaches on motor fluctuations and quality of life. It will also determine how frequently different brain signals occur in people with Parkinson's disease and how well they reflect motor symptoms, providing information that may improve future adaptive DBS therapies.