# Adaptive high-resolution electrical stimulation for retinal implant design

> **NIH NIH R01** · STANFORD UNIVERSITY · 2024 · $403,349

## Abstract

Project Summary/Abstract
The goal of our work is to develop a high-resolution electronic epiretinal implant for treating
incurable blindness from retinal degeneration. To further this goal, we propose here to develop
novel techniques for adaptive, high-resolution, multi-electrode recording and stimulation of
retinal ganglion cells (RGCs) in the isolated macaque and human retina as an experimental lab
prototype for the future device. The major goals of this project are to (1) adaptively use current
steering with electrode triplets to enhance selective targeting of RGCs, (2) adaptively use
spatio-temporal dithering and multiplexing to produce naturalistic activity in large RGC
populations that can support high-quality visual coding, and (3) test the fidelity of electrically
evoked visual signals in RGCs of the central human retina. Tackling these aims will allow us to
emulate the neural code for vision, cell-by-cell and spike-by-spike, over a region of the central
retina. Our unique technical approach involves large-scale, high-resolution electrical recording
and stimulation, combined with novel computational approaches to adjust device function to the
complex circuitry in which it is embedded, including the degenerated retina, and thus to optimize
vision restoration.

## Key facts

- **NIH application ID:** 10802229
- **Project number:** 2R01EY021271-11A1
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** EDUARDO CHICHILNISKY
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $403,349
- **Award type:** 2
- **Project period:** 2011-08-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10802229

## Citation

> US National Institutes of Health, RePORTER application 10802229, Adaptive high-resolution electrical stimulation for retinal implant design (2R01EY021271-11A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10802229. Licensed CC0.

---

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