# Combining myoelectric training with sleep-based memory reactivation to improve motor recovery after stroke

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2020 · $516,639

## Abstract

Stroke is the largest cause of major disability. This disability most often results from persistent
arm impairment. A significant portion of arm impairment is caused not by weakness or
spasticity, but by abnormal co-activation among arm muscles. This coordination dysfunction is
pervasive in the most severely impaired patients, who are most in need of new therapies. To
treat abnormal muscle co-activation, we developed a myoelectric-computer interface (MyoCI). In
addition, we pioneered the use of targeted memory reactivation (TMR) to enhance memory
consolidation during sleep. The long-term goal of this research is to develop an affordable, non-
invasive, and easy-to-use combination of MyoCI and TMR that improves control of arm
movements by reducing abnormal co-activation. Our preliminary studies show that TMR
enhances consolidation of MyoCI learning in a single nap in a group of healthy individuals, and
across several nights in three stroke survivors. Accordingly, we propose to determine whether
this training-plus-sleep combination will generalize to improve motor function over an extended
training protocol in stroke survivors. The objectives of this proposal are 1) to determine whether
TMR can augment motor learning after stroke, and 2) to determine optimal parameters for the
MyoCI+TMR paradigm to enhance motor function in stroke survivors. Our central hypothesis is
that supplementing MyoCI training with TMR will augment learning considerably and thereby
improve arm movement. We will test this hypothesis via the following specific aims: 1) Test the
extent to which TMR during SWS enhances MyoCI learning after stroke, 2) Assess the ability of
TMR across all sleep stages to enhance MyoCI learning after stroke, and 3) Assess the
influence of TMR dose and stroke location on MyoCI learning. This proposal’s innovative
combination of wearable, inexpensive, and noninvasive MyoCI+TMR will enable us to test the
effects of TMR on motor learning after stroke. Achieving our objectives will be significant
because it will facilitate the development of an enhanced rehabilitative therapy to improve
function after stroke that could be used widely and could help the most severely impaired stroke
survivors. We expect that the paradigm will be synergistic with other therapies, given its novel
mechanism of action (reducing co-activation using myoelectric signals). The research will also
provide basic information about what brain areas are critical for consolidating motor learning.
We further expect that TMR could be applied to other types of stroke rehabilitation in addition to
MyoCI. Finally, this project will provide critical information needed to plan larger clinical trials to
assess efficacy of this and related approaches.

## Key facts

- **NIH application ID:** 9974587
- **Project number:** 5R01NS112942-02
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** KEN A PALLER
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $516,639
- **Award type:** 5
- **Project period:** 2019-07-15 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9974587

## Citation

> US National Institutes of Health, RePORTER application 9974587, Combining myoelectric training with sleep-based memory reactivation to improve motor recovery after stroke (5R01NS112942-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9974587. Licensed CC0.

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