# Closed Loop Deep Brain Stimulation for Parkinson's Disease

> **NIH NIH UH3** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2020 · $655,534

## Abstract

Abstract
Deep brain stimulation (DBS) has a major role in the management of movement disorders, and is under
investigation for the treatment of disorders of mood and memory. In Parkinson's disease (PD), DBS of basal
ganglia nuclei can improve motor signs and reduce medication-induced motor fluctuations and dyskinesia,
characterized by frequent transitions between a hypokinetic state (too little movement) and a hyperkinetic state
(too much movement). However, since the introduction of DBS for PD 25 years ago, there have been no major
improvements in this therapy. Existing DBS devices deliver “open loop” stimulation, continuously stimulating
their target structures regardless of changes in the brain circuits related to disease expression. Device
programming is a labor-intensive process based on “trial and error” requiring significant clinical expertise,
which is a barrier to widespread application. In PD, continuous open-loop stimulation may result in suboptimal
control of fluctuating motor signs, stimulation-induced adverse effects, and short battery life. DBS could be
significantly improved by delivering “closed-loop” stimulation, in which stimulation parameters are automatically
adjusted based on brain signals that reflect the patient's clinical state. Using both intraoperative and chronic
invasive recording techniques, we and others have identified abnormal patterns of oscillatory activity that may
provide physiological signatures or “biomarkers” of hypokinetic and hyperkinetic states in PD. Here, we plan to
develop closed-loop DBS algorithms based on these brain signals, using an investigational neural interface
(Medtronic Activa RC+S) that can sense and store brain activity as well as delivering DBS. We will determine
which brain signals are the most appropriate to optimize DBS therapy and answer critical questions including
the site of control signal detection (cortical versus subcortical) and the required complexity of control signals
(single frequency power versus cross frequency interactions). Ten PD patients with motor fluctuations and
dyskinesia will be implanted bilaterally with Activa RC+S attached to a subthalamic nucleus (STN) DBS lead
and an electrocorticography (ECoG) lead placed over motor cortex. We will collect ECoG and subcortical local
field potential (LFP) recordings to characterize “personalized” physiological signatures for each subject and
prototype stimulation paradigms by data streaming through an external computer in a clinical setting (Aims 1
and 2). We will then embed algorithms in the pulse generator to implement chronic and fully closed-loop DBS
in a small double-blinded clinical trial (Aim 3). Motor function will be assessed by wearable automated
detectors as well as rating scales from videotapes and self-report instruments. The study will define the
technical characteristics required for the design of future DBS devices. “Self programming” DBS devices offer
the potential to simplify the therapy and allow many mor...

## Key facts

- **NIH application ID:** 9980507
- **Project number:** 5UH3NS100544-04
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** PHILIP Andrew STARR
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $655,534
- **Award type:** 5
- **Project period:** 2016-09-30 → 2022-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9980507

## Citation

> US National Institutes of Health, RePORTER application 9980507, Closed Loop Deep Brain Stimulation for Parkinson's Disease (5UH3NS100544-04). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/9980507. Licensed CC0.

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