# Biomimetic Somatosensory Feedback through Intracorticalmicrostimulation

> **NIH NIH R01** · NORTHWESTERN UNIVERSITY · 2020 · $615,717

## Abstract

Spinal cord injury causes both paralysis and loss of sensation from the limbs. The past 15 years have seen
remarkable advances in “Brain Machine Interfaces” (BMIs) that allow paralyzed persons to move
anthropomorphic limbs using signals recorded directly from their brains. However, these movements remain
slow, clumsy, and effortful, looking remarkably like those of individuals who have lost sensation from their
arms due to peripheral neuropathy. Brain-controlled prosthetic limbs are unlikely to achieve high levels of
performance in the absence of artificial sensory feedback. Early attempts at restoring somatosensation used
intracortical microstimulation (ICMS) to activate somatosensory cortex (s1), requiring animals to learn largely
arbitrary patterns of stimulation to represent two or three virtual objects or to navigate in two-dimensional
space. While an important beginning, this approach seems unlikely to scale to the broad range of limb
movements and interactions with objects that we experience in daily life.
 To move the field past this hurdle, we propose to replace both touch and proprioception by using multi-
electrode ICMS to produce naturalistic patterns of neuronal activity in S1 of monkeys. In Aim 1, we will develop
model-optimized mappings between limb state (pressure on the fingertip, or motion of the limb) and the
patterns of ICMS required to evoke S1 activation that mimics that of natural inputs. These maps will account
for both the dynamics of neural responses and the biophysics of ICMS. We anticipate that this biomimetic
approach will evoke intuitive sensations that require little or no training to interpret. We will validate the maps
by comparing natural and ICMS-evoked S1 activity using novel hardware that allows for concurrent ICMS and
neural recording. In Aim 2, we will test the ability of monkeys to recognize objects using artificial touch. Having
learned to identify real objects by touch, animals will explore virtual objects with an avatar that shadows their
own hand movements, receiving artificial touch sensations when the avatar contacts objects. We will test their
initial performance on the virtual stereognosis task without learning, as well as their improvements in
performance over time. Aim 3 will be similar, but will focus on proprioception. We will train monkeys to report
the direction of brief force bumps applied to their hand. After training, we will replace the actual bumps with
virtual bumps created by patterned ICMS, again asking the monkeys to report their perceived sense of the
direction and magnitude of the perturbation. Finally, in Aim 4, we will temporarily paralyze the monkey's arm,
thereby removing both touch and proprioception, mimicking the essential characteristics of a paralyzed
patient. The avatar will be controlled based on recordings from motor cortex and guided by artificial
somatosensation. The monkey will reach to a set of virtual objects, find one with a particular shape, grasp it,
and move it ...

## Key facts

- **NIH application ID:** 9932509
- **Project number:** 5R01NS095251-05
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** SLIMAN BENSMAIA
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $615,717
- **Award type:** 5
- **Project period:** 2016-06-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9932509

## Citation

> US National Institutes of Health, RePORTER application 9932509, Biomimetic Somatosensory Feedback through Intracorticalmicrostimulation (5R01NS095251-05). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9932509. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*