# A primate model of an intra-cortically controlled FES prosthesis for grasp

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2020 · $612,051

## Abstract

Project Summary
In the space of barely over ten years, Brain Computer Interfaces (BCIs) used to restore movement have
developed from the stuff of science fiction to clinically relevant devices. However, most existing BCIs, while
technically remarkable, require the user to be wired to stationary equipment, and allow only intermittent control
of a computer cursor or disembodied robotic limb. They require that the algorithm linking brain activity to the
restored movement be frequently recalibrated. We have developed a wireless BCI that will operate 24 hours a
day, restoring voluntarily movement to monkeys despite paralysis of their hand, for a broad range of their
normal motor behaviors, such as foraging, feeding, or playing with enrichment toys. By using “autoencoding
neural networks” we will be able to greatly extend the period over which the BCI will work without recalibration.
 We have developed a unique model of spinal cord injury (SCI) using a chronically implanted infusion pump
that delivers a potent drug (tetrodotoxin) to cuffs placed around two key nerves in the arm. The drug causes a
nerve block that produces the acute effects of spinal cord injury for indefinite periods of time, yet with full
recovery within a day of stopping the drug. Prior to the nerve block, we will record wirelessly not only neural
signals from the brain, but also electromyograms (EMGs) from a large number of muscles in the arm and hand.
We will make these recordings not only during typical, constrained motor behaviors in the lab, but also during
completely unconstrained behaviors while the monkey is in its home cage. We will use the data to develop
algorithms (“decoders”) that transform the neural signals into predicted EMG signals. Following the onset of
paralysis, our BCI will use these EMG predictions as control signals for Functional Electrical Stimulation (FES),
causing contractions of the paralyzed muscles that the monkey can control voluntarily through the computer
interface. We will study the gradually changing brain activity as the monkeys learn to use this FES BMI. In
addition, we will attempt to augment the monkey's performance by developing “adaptive” decoders that
improve their performance in parallel with the monkey's own adaptation, as well as “teacher” decoders that
coach the monkeys, pushing them toward desired control strategies and away from counterproductive ones.
 This technology gives us the ability to study the brain's representation of movement across a range of
motor behaviors that has never been possible before. During paralysis, it will allow us to study motor learning
and adaption without the limitations imposed by the intermittent availability of current BCIs. Finally, it provides
a platform close to that necessary for clinical translation, with which we will be able to study the limits of current
decoders and to develop nonlinear and adaptive decoders designed to assist the monkey's own adaptive
processes. While this application is focus...

## Key facts

- **NIH application ID:** 9978136
- **Project number:** 5R01NS053603-14
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** FERDINANDO Alessandro MUSSA-IVALDI
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $612,051
- **Award type:** 5
- **Project period:** 2006-01-01 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9978136

## Citation

> US National Institutes of Health, RePORTER application 9978136, A primate model of an intra-cortically controlled FES prosthesis for grasp (5R01NS053603-14). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/9978136. Licensed CC0.

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