Decoding the Neural Mechanisms Underlying Postural Instability and Gait Dysfunction in Parkinson's Disease

Overview

The purpose of this study is to learn how brain signals are related to freezing of gait (FOG) and balance problems in Parkinson's disease (PD) and to study how different deep brain stimulation (DBS) settings may affect these symptoms.

PD is a progressive neurodegenerative disorder characterized by motor symptoms including tremor, rigidity, and bradykinesia. While DBS is an effective treatment for many of these motor symptoms, postural instability and gait dysfunction (PIGD), including FOG, frequently persist and are a major source of falls, loss of independence, and reduced quality of life. The neural mechanisms underlying PIGD and FOG remain poorly understood, particularly in real-world conditions where these symptoms are most likely to occur. Conventional clinical assessments often fail to reliably provoke these gait disturbances, limiting the ability to study their underlying neurophysiology. At the same time, recent advances in DBS technology - specifically systems capable of recording brain signals, or neural activity - provide a unique opportunity to directly examine brain signals associated with gait impairment. This study is designed to characterize the neural mechanisms associated with PIGD and FOG in individuals with PD who have an implanted sensing-enabled DBS system (Medtronic Percept™). By integrating neural recordings from the subthalamic nucleus (STN) with detailed biomechanical measurements during walking tasks, the study aims to identify patterns of neural activity that precede, accompany, and follow gait disturbances. To address the challenge of eliciting ecologically valid gait disturbances, participants will complete walking and balance tasks within a fully immersive virtual reality platform. This system simulates real-world scenarios that are meant to provoke FOG and PIGD, including situations involving environmental constraints, anxiety-inducing contexts, and dual-task cognitive demands. Additional assessments will include stair ambulation and functional mobility tasks using an instrumented gait platform which provides quantitative measures of temporal, kinematic, and kinetic aspects of walking and balance. During these tasks, neural activity recorded from the DBS device will be synchronized with motion capture and biomechanical data. This integrated dataset will allow investigators to examine how neural activity relates to gait performance and to identify neural patterns associated with FOG episodes. Participants will undergo multiple testing sessions under varying DBS conditions, including their clinically optimized DBS therapy and other programmed conditions. These comparisons will enable evaluation of how different stimulation approaches influence neural activity and gait performance. The knowledge gained from this study is expected to advance understanding of the neural mechanisms underlying gait dysfunction in PD and may inform the development of more personalized and adaptive neuromodulation strategies to better treat these disabling symptoms in the future.

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