# Using the principles of synaptic plasticity to promote recovery from amblyopia

> **NIH NIH R01** · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · 2020 · $630,418

## Abstract

Amblyopia is a prevalent form of visual disability that arises during infancy and early
childhood when inputs to the visual cortex from the two eyes are poorly balanced (for
example, by misalignment of the eyes, asymmetric refraction, or opacities and
obstructions of one eye). Characteristics of amblyopia are very poor acuity in one eye,
and an attendant loss of stereopsis. The need for improved treatments for amblyopia is
widely acknowledged.
Animal studies over the past 50 years have uncovered the pathophysiology of
amblyopia. It is well documented that temporary monocular deprivation alters the
strength of synapses in primary visual cortex that renders cortical neurons unresponsive
to stimulation of the deprived eye. However, much less is known about the mechanisms
that serve recovery from amblyopia. We recently discovered that temporarily inactivating
the retinas with a local anesthetic sets in motion changes in the brain that enable
complete recovery from the effect of early life monocular deprivation when the anesthetic
wears off. Our objectives are to uncover the mechanism for how this recovery occurs,
and to determine if this knowledge can be translated into new and better treatments for
amblyopia.

## Key facts

- **NIH application ID:** 10017243
- **Project number:** 5R01EY029245-03
- **Recipient organization:** MASSACHUSETTS INSTITUTE OF TECHNOLOGY
- **Principal Investigator:** Mark F Bear
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $630,418
- **Award type:** 5
- **Project period:** 2018-09-30 → 2022-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10017243

## Citation

> US National Institutes of Health, RePORTER application 10017243, Using the principles of synaptic plasticity to promote recovery from amblyopia (5R01EY029245-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10017243. Licensed CC0.

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