# Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies

> **NIH NIH R01** · UNIVERSITY OF WASHINGTON · 2021 · $351,622

## Abstract

ABSTRACT
The field of sight restoration has made dramatic progress over the last decade. Two types of
retinal implants have been commercially approved, and several other designs are in development
worldwide. In addition, two groups are actively implanting and developing cortical electronic
implants. The first optogenetic clinical trial has begun, with many others likely in the next two
years. Within a decade, many blind individuals are likely to be offered a wide range of options
for sight restoration that depend on widely different technologies.
Interactions between implant electronics and the underlying neurophysiology of the retina or
cortex mean that the vision provided by most of these technologies will differ substantially from
normal sight. The question of this proposal is – What role can cortical plasticity play in helping
patients make use of this artificial visual input?
Over the past 15 years our research group has been generating computational models, developed
using a combination of physiological and psychophysical data, which can predict the percepts
that patients might experience for a variety of sight recovery technologies. We propose to use
these models to simulate, within visually normal participants, four critical neurophysiological
distortions inherent in sight restoration technologies:
Aim 1. Abnormal neuronal population responses during retinal stimulation: Simultaneous stimulation of
on and off cells.
Aim 2. Spatial distortions: Stimulation of retinal ganglion cell axons.
Aim 3. Abnormal cortical neuronal population responses: Distortions induced by the V1 neural
architecture.
Aim 4. Temporal blurring due to slow optogenetic kinetics.
Our goal is to use normally sighted participants, viewing distorted visual input, as ‘virtual
patients’ to learn which spatiotemporal distortions can be compensated for by plasticity, and
which must be compensated for in device design. This will provide device manufacturers with a
more nuanced understanding of the abilities and limits of visual perceptual adaptability.
Finally, this work will provide novel insights regarding the fundamental mechanisms of cortical
plasticity by asking whether, in adulthood, it is possible to reconfigure the fundamental building blocks
of visual perception?

## Key facts

- **NIH application ID:** 10207233
- **Project number:** 1R01EY031312-01A1
- **Recipient organization:** UNIVERSITY OF WASHINGTON
- **Principal Investigator:** GEOFFREY M BOYNTON
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $351,622
- **Award type:** 1
- **Project period:** 2021-05-01 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10207233

## Citation

> US National Institutes of Health, RePORTER application 10207233, Learning to see again: biological constraints on cortical plasticity and the implications for sight restoration technologies (1R01EY031312-01A1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10207233. Licensed CC0.

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