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Completed NON-SBIR/STTR RPGS NIH (US)

Biophysical Characterization of Subthalamic Local Field Potentials in Parkinson's Disease

$4.58M USD

Funder NATIONAL INSTITUTE OF NEUROLOGICAL DISORDERS AND STROKE
Recipient Organization Duke University
Country United States
Start Date Feb 01, 2021
End Date Jan 31, 2025
Duration 1,460 days
Number of Grantees 1
Roles Principal Investigator
Data Source NIH (US)
Grant ID 10543713
Grant Description

PROJECT SUMMARY Subthalamic deep brain stimulation (DBS) can significantly improve the motor symptoms and quality of life of patients with Parkinson’s disease (PD). Recent advances in DBS technology are providing new opportunities to interrogate and characterize the pathophysiology of PD using local field potential (LFP)

recordings. Previous LFP investigations brought to light the important role of beta-band (12-30 Hz) activity in PD. However, we are still faced with a wide range of questions on the biophysics of subthalamic LFPs. For example, How many subthalamic nucleus (STN) neurons need to be synchronized to generate a clinically

measurable LFP signal? What are the synaptic input characteristics responsible for that synchronization? Where are those neurons located in the STN? The McIntyre lab has spent the last decade developing the computational infrastructure to address these questions within the context of the human STN implanted with

clinical DBS electrodes. Therefore, we propose the integration of those advanced modeling tools with ongoing human studies (directional STN LFP recordings – Dr. Walker, and chronic STN LFP recordings – Dr. Bronte- Stewart) that are defining the clinical cutting edge of DBS LFP studies. The goal of this Bioengineering Research Grant (PAR-19-158) is to apply the latest advances in patient-

specific LFP modeling to the analysis of directional STN recordings and chronic STN recordings in PD patients. These analyses will allow us to address fundamental questions on the size and location of synchronous neural populations in the STN, which have important implications for understanding the pathophysiology of PD. In

addition, our models will enable us to evaluate the variance in STN neural synchrony across populations of patients, and over long periods of time within the same patient, both of which have important implications for the engineering design of LFP-based DBS algorithms. The first step of this project will focus on evolving the

patient-specific LFP modeling infrastructure to accommodate directional DBS electrodes and adapt to different electrode positions in each patient-specific STN volume. The second step of this project will use the patient- specific LFP model system to identify the size and location of beta synchrony in 10 PD patients using

directional DBS recordings acquired during intra-operative experiments. Finally, we will quantify the modulation of the size and location of the beta synchrony in 5 PD patients using chronic LFP recordings and measurements taken at 4 different time points over a 1-year period.

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Duke University

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