# CRCNS: MOVE!-MOdeling of fast Movement for Enhancement via neuroprosthetics

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2021 · $67,688

## Abstract

PROJECT SUMMARY
Tracking fast unpredictable movements is a valuable skill, applicable in many situations. In the animal kingdom,
the context includes the action of a predator chasing its prey that is running and dodging at high speeds, like a
cheetah chasing a gazelle. The sensorimotor control system (SCS) is responsible for such actions and its
performance clearly depends on the computing power of neurons, delays between brain and muscles, and the
dynamics of muscles involved. Despite these obvious factors that set the limits on how fast an animal can track
a moving object, tracking performance of the SCS and its dependence on neural computing, delays, and muscle
dynamics have not been explicitly quantified. In this program, we will build upon new theory developed using
feedback control principles and an appropriately simplified model of the SCS to identify how neural computing,
delays, and muscles interact during the generation of fast movements. Therefore if one component is
compromised, we can take advantage of the other components to restore motor performance with assistive
neuroprosthetic devices.
The program objectives are to first parameterize the major factors (brain and body) limiting fast movements and
to derive how these parameters must interact to achieve tracking of fast movements in the SCS. Then, the
parameterization and quantified interactions will be tested experimentally in subjects through manipulation of (i)
neural computing power, (ii) transmission delays, and (iii) muscle dynamics. If discrepancies emerge between
experiments and theory, the SCS model and theory will be modified to explain observation data. Finally, the
theoretical model of interactions required to achieve tracking of fast movements will be exploited to apply
compensation to account for degradation of some parameters by “boosting” others. More specifically, we will
design assistive neuroprosthetic devices for subjects having compromised neural real estate to restore
performance of fast movements. For example, if primary motor cortex is compromised due to disease or damage,
we can manipulate muscle dynamics by adding the necessary compensatory forces to restore motor
performance, and more importantly restore fast and agile movements. Just how one should compensate will be
informed by our SCS model and theory.

## Key facts

- **NIH application ID:** 10352692
- **Project number:** 3R01NS110423-04S1
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** Sridevi V. Sarma
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $67,688
- **Award type:** 3
- **Project period:** 2018-07-01 → 2023-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10352692

## Citation

> US National Institutes of Health, RePORTER application 10352692, CRCNS: MOVE!-MOdeling of fast Movement for Enhancement via neuroprosthetics (3R01NS110423-04S1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10352692. Licensed CC0.

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