# Visuomotor Prosthetic for Paralysis

> **NIH EY UG1** · CALIFORNIA INSTITUTE OF TECHNOLOGY · 2026 · $1,355,439

## Abstract

The proposed research aims to obtain scientific knowledge on the visuomotor transformations in
posterior parietal cortex (PPC) and motor cortex (MC) by characterizing the functional similarities
and differences between both regions in tetraplegic participants enrolled in a clinical trial designed
to advance the development of neural prosthetics. In experiments from the last grant period, we
demonstrated that the functional characteristics of these brain regions remain intact over time,
even following spinal cord injury and prolonged use of brain-machine interfaces (BMIs). We
identified overlapping neural populations in both areas that encode motor variables for effectors
throughout the body using mixed selectivity, a coding scheme that combines multiple variables
within the same neurons. Despite these similarities, we found that the encoding properties of MC
and PPC exhibit essential differences. While MC preferentially encodes the contralateral hand, PPC
shows similar encoding strength for all effectors across the body. Furthermore, PPC is actively
involved in planning and executing motor actions, whereas MC shows mainly activation during the
execution of movements. PPC also shows a compositional code for observed and felt
somatosensory stimuli.
This renewal proposal seeks to broaden our understanding of the neural encoding mechanisms
within PPC and MC by exploring how context affects the previously unexamined sensorimotor
processes of navigation, drawing, and simultaneous, coordinated movements . In Aim 1, we will
study the neural representations of allocentric and egocentric cognitive maps during two virtual
reality navigation tasks performed under BMI control. We hypothesize that PPC encodes both
allocentric and egocentric cognitive maps, while MC only encodes egocentric motor execution
during these navigational tasks. Aim 2 will examine whether the brain uses compositional
encoding of visuomotor variables for drawing. Our hypothesis is that PPC uses compositional

## Key facts

- **NIH application ID:** 11266028
- **Project number:** 2UG1EY032039-06
- **Recipient organization:** CALIFORNIA INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** RICHARD A ANDERSEN
- **Activity code:** UG1 (R01, R21, SBIR, etc.)
- **Funding institute:** EY
- **Fiscal year:** 2026
- **Award amount:** $1,355,439
- **Award type:** 2
- **Project period:** 2021-05-01T00:00:00 → 2031-03-31T00:00:00

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/11266028

## Citation

> US National Institutes of Health, RePORTER application 11266028, Visuomotor Prosthetic for Paralysis (2UG1EY032039-06). Retrieved via AI Analytics 2026-07-09 from https://api.ai-analytics.org/grant/nih/11266028. Licensed CC0.

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