# Functional reorganization of reticulospinal drive in hemiparetic stroke

> **NIH NIH R21** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2020 · $206,250

## Abstract

Reticulospinal pathways are likely key contributors to bilateral disability and recovery that
remain understudied.
This proposal breaks new conceptual ground by integrating across neuroanatomical,
neurophysiological & behavioral domains in stroke. The reticulospinal tract receives input from
both hemi-spheres and projects bilaterally, and undergoes neuroanatomical changes in chronic
hemiparetic stroke. Neurophysiologically, alpha-band (10-20 Hz) neural drive is exaggerated or
redistributed across muscles of both arms after stroke, and this frequency of neural drive is
thought to be of reticulospinal, but not corticospinal, origin. We link this to behavior as alpha-band
neural drive is especially exacerbated in muscles involved in the pathologic synergies that
disrupt motor control.
We will demonstrate muscle-muscle coherence is a valid neurophysiological assay to
characterize mechanisms of bilateral motor impairment at the level of the reticulospinal tract.
Interventions exploiting these mechanisms for recovery of the more-affected arm have a greater
chance at being restorative and promoting brain repair than simply improving function through
practice of compensatory strategies.

## Key facts

- **NIH application ID:** 10017345
- **Project number:** 5R21NS113613-02
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Francisco J Valero-Cuevas
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $206,250
- **Award type:** 5
- **Project period:** 2019-09-15 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017345

## Citation

> US National Institutes of Health, RePORTER application 10017345, Functional reorganization of reticulospinal drive in hemiparetic stroke (5R21NS113613-02). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10017345. Licensed CC0.

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