June 2022
Volume 63, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2022
Modeling amblyopia treatment responses through principles of synaptic plasticity
Author Affiliations & Notes
  • Brian Blais
    Science, Bryant University, Smithfield, Rhode Island, United States
  • Eric Gaier
    Picower Institute for Learning and Memory, Massachusetts Institute of Technology, Cambridge, Massachusetts, United States
  • Scott Xiao
    Luminopia, Massachusetts, United States
  • Footnotes
    Commercial Relationships   Brian Blais None; Eric Gaier Luminopia, Stoke Therapeutics Inc., Code C (Consultant/Contractor), Luminopia, Code P (Patent); Scott Xiao Luminopia, Code O (Owner), Luminopia, Code P (Patent)
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2022, Vol.63, 1236 – A0344. doi:
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      Brian Blais, Eric Gaier, Scott Xiao; Modeling amblyopia treatment responses through principles of synaptic plasticity. Invest. Ophthalmol. Vis. Sci. 2022;63(7):1236 – A0344.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Amblyopia is a common cause of visual impairment that results from unequal visual inputs during development. The imbalance is known to manifest through synaptic alterations in visual cortex that shift ocular dominance. Understanding the effects of amblyogenic drivers and their reversal with synaptic plasticity could enable improvements in amblyopia treatment efficacy. This study uses a specific model of activity-dependent neural plasticity, the Bienenstock, Cooper, and Munro (BCM) model, to compare the dynamics of amblyopia recovery at the neuronal level under several treatment protocols, including optical correction, patching, atropine penalization, and binocular therapies.

Methods : We use a model of the single cortical cell receiving natural scene stimuli from two channels representing each eye. Thalamocortical synaptic modification obeys the BCM learning rule where competition between the two eyes drives changes in ocular dominance. Anisometropic amblyopia is modeled by blurring input to the affected eye, and the fix (with glasses) rebalances the structure of inputs. Patching is modeled with unstructured activity (noise) in the fellow eye, and atropine penalization uses both noise and blurred input to the fellow eye. Binocular therapies involving contrast modification and dichoptic masks are modeled with established input filters.

Results : Imbalanced structure of inputs produce a long-lasting ocular dominance shift in favor of the fellow eye that recovers partially when input is re-balanced. We can drive recovery by shifting the difference between inputs in favor of the affected eye, and the rate of recovery increases with greater input disparity. The rate of recovery is greater with patch and atropine treatment models as compared to contrast disparity alone. Addition of dichoptic masks enhances the rate of recovery with the binocular treatment model, comparable to traditional therapies. The efficacy of binocular therapy is directly dependent on the size of the dichoptic masks and level of contrast disparity.

Conclusions : The BCM principles of activity-dependent synaptic plasticity are sufficient to model the ocular dominance shifts underlying the development of and recovery from amblyopia. The importance of the dichoptic masks and contrast disparity levels on the efficacy of the binocular therapy model suggests that these parameters require precise refinement to optimize amblyopia recovery.

This abstract was presented at the 2022 ARVO Annual Meeting, held in Denver, CO, May 1-4, 2022, and virtually.

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