ArticleProceedings of the National Academy of Sciences of the United States of America2020
Active efficient coding explains the development of binocular vision and its failure in amblyopia.
Article in Proceedings of the National Academy of Sciences of the United States of America, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.
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13 citing papers in PubMed.
- Efficacy of binocular vision training and Fresnel press-on prism on children with esotropia and amblyopia.International ophthalmology · 2023Trial
- Multiple mechanisms of response suppression to self-induced sensation during pursuit eye movements.Royal Society open science · 2025Article
- Sequential effects in reaching reveal efficient coding in motor planning.Science advances · 2025Article
- Sequential Effects in Reaching Reveal Efficient Coding in Motor Planning.bioRxiv : the preprint server for biology · 2024Article
- A spiking neural network for active efficient coding.Frontiers in robotics and AI · 2024Article
- Predictive coding is a consequence of energy efficiency in recurrent neural networks.Patterns (New York, N.Y.) · 2022Article
- Article
- Efficient Temporal Coding in the Early Visual System: Existing Evidence and Future Directions.Frontiers in computational neuroscience · 2022Review
- Recurrent processing improves occluded object recognition and gives rise to perceptual hysteresis.Journal of vision · 2021Article
- Binocular Integration of Perceptually Suppressed Visual Information in Amblyopia.Investigative ophthalmology & visual science · 2021Article
- The development of active binocular vision under normal and alternate rearing conditions.eLife · 2021Article
- Active head rolls enhance sonar-based auditory localization performance.PLoS computational biology · 2021Article
- Active efficient coding explains the development of binocular vision and its failure in amblyopia.Proceedings of the National Academy of Sciences of the United States of America · 2020Article
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4 authors.
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Abstract
The development of vision during the first months of life is an active process that comprises the learning of appropriate neural representations and the learning of accurate eye movements. While it has long been suspected that the two learning processes are coupled, there is still no widely accepted theoretical framework describing this joint development. Here, we propose a computational model of the development of active binocular vision to fill this gap. The model is based on a formulation of the active efficient coding theory, which proposes that eye movements as well as stimulus encoding are jointly adapted to maximize the overall coding efficiency. Under healthy conditions, the model self-calibrates to perform accurate vergence and accommodation eye movements. It exploits disparity cues to deduce the direction of defocus, which leads to coordinated vergence and accommodation responses. In a simulated anisometropic case, where the refraction power of the two eyes differs, an amblyopia-like state develops in which the foveal region of one eye is suppressed due to inputs from the other eye. After correcting for refractive errors, the model can only reach healthy performance levels if receptive fields are still plastic, in line with findings on a critical period for binocular vision development. Overall, our model offers a unifying conceptual framework for understanding the development of binocular vision.
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