# Oscillatory Neural Correlates of Motor Phenotypes in Parkinson Disease

> **NIH NIH R01** · UNIVERSITY OF HOUSTON · 2022 · $536,426

## Abstract

PROJECT SUMMARY
PD is a complex neurodegenerative disease with a broad spectrum of motor and non-motor features. The
cardinal motor features include resting tremor, rigidity, bradykinesia (or akinesia), and postural instability. Over
the past decade, deep brain stimulation (DBS) has largely replaced ablative techniques in the surgical
Although clinical phenotypes of PD such as tremor dominant (TD) and postural instability and
gait difficulty (PIGD) subtypes have been identified since the mid-1990s, to our knowledge, no
neurobiomarkers have been identified to describe them and assist with decision-making regarding the DBS
therapeutic target.
treatment of PD.
Very limited data exists regarding the electrophysiological abnormalities within the basal
ganglia and associated structures which likely accompany the symptom severity or the phenotypic subtypes of
PD.
This proposal seeks to overcome these limitations by investigating the spatio-spectral dynamics of local field
potentials (LFPs) and single unit activity recorded from the subthalamic nucleus (STN) and globus pallidus
internus (GPi) and relate them to symptom manifestations, in an attempt to define the differences in PD motor
phenotypes. In our preliminary studies and to the best of our knowledge, we are the first to show initial
evidence that high frequency oscillations of microelectrode LFPs and their nonlinear interaction with the beta
band in the form of phase amplitude coupling can distinguish PD motor phenotypes in the territories of STN.
Based on our preliminary observations, this project will investigate these phenotypic LFP patterns in large
patient populations in STN and GPi. Specifically, by employing machine learning techniques, neural signatures
in STN and GPi will be discovered to differentiate motor phenotypes in PD. The project will investigate to what
extent the extracted neural patterns can serve as objective neurobiomarkers to identify the territories of basal
ganglia causing symptom differences. In addition, retrospectively, the project will also explore to what extent
localization of these phenotypic LFP patterns with directional macro electrodes can describe the efficacy of
chronic DBS. If successful, these advancements will provide unique opportunities to understand symptom
manifestation and personalization of DBS in patients with PD.

## Key facts

- **NIH application ID:** 10521378
- **Project number:** 1R01NS124650-01A1
- **Recipient organization:** UNIVERSITY OF HOUSTON
- **Principal Investigator:** Nuri Firat Ince
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $536,426
- **Award type:** 1
- **Project period:** 2022-09-01 → 2027-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10521378

## Citation

> US National Institutes of Health, RePORTER application 10521378, Oscillatory Neural Correlates of Motor Phenotypes in Parkinson Disease (1R01NS124650-01A1). Retrieved via AI Analytics 2026-05-28 from https://api.ai-analytics.org/grant/nih/10521378. Licensed CC0.

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