scholarly journals Active Efficient Coding Explains the Development of Binocular Vision and its Failure in Amblyopia

2019 ◽  
Author(s):  
Samuel Eckmann ◽  
Lukas Klimmasch ◽  
Bertram E. Shi ◽  
Jochen Triesch
Keyword(s):  
Eye Movements ◽  
Computational Model ◽  
Binocular Vision ◽  
Receptive Fields ◽  
Refractive Errors ◽  
Efficient Manner ◽  
Efficient Coding ◽  
Neural Representations ◽  
Active Binocular Vision ◽  
New Formulation

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 new 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 co-ordinated 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.Significance StatementBrains must operate in an energy-efficient manner. The efficient coding hypothesis states that sensory systems achieve this by adapting neural representations to the statistics of sensory input signals. Importantly, however, these statistics are shaped by the organism’s behavior and how it samples information from the environment. Therefore, optimal performance requires jointly optimizing neural representations and behavior, a theory called Active Efficient Coding. Here we test the plausibility of this theory by proposing a computational model of the development of binocular vision. The model explains the development of accurate binocular vision under healthy conditions. In the case of refractive errors, however, the model develops an amblyopia-like state and suggests conditions for successful treatment.

scholarly journals Active efficient coding explains the development of binocular vision and its failure in amblyopia

2020 ◽  
Vol 117 (11) ◽  
pp. 6156-6162
Author(s):  
Samuel Eckmann ◽  
Lukas Klimmasch ◽  
Bertram E. Shi ◽  
Jochen Triesch
Keyword(s):  
Eye Movements ◽  
Binocular Vision ◽  
Coding Theory ◽  
Critical Period ◽  
Receptive Fields ◽  
Efficient Coding ◽  
Coding Efficiency ◽  
Vision Development ◽  
Neural Representations ◽  
Active Binocular Vision

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.

scholarly journals Learning of Active Binocular Vision in a Biomechanical Model of the Oculomotor System

2017 ◽  
Author(s):  
Lukas Klimmasch ◽  
Alexander Lelais ◽  
Alexander Lichtenstein ◽  
Bertram E. Shi ◽  
Jochen Triesch
Keyword(s):  
Eye Movements ◽  
Binocular Vision ◽  
Biomechanical Model ◽  
Oculomotor System ◽  
High Fidelity ◽  
Active Perception ◽  
Efficient Coding ◽  
Antagonistic Muscle ◽  
Metabolic Costs ◽  
Active Binocular Vision

AbstractWe present a model for the autonomous learning of active binocular vision using a recently developed biome-chanical model of the human oculomotor system. The model is formulated in the Active Efficient Coding (AEC) framework, a recent generalization of classic efficient coding theories to active perception. The model simultaneously learns how to efficiently encode binocular images and how to generate accurate vergence eye movements that facilitate efficient encoding of the visual input. In order to resolve the redundancy problem arising from the actuation of the eyes through antagonistic muscle pairs, we consider the metabolic costs associated with eye movements. We show that the model successfully learns to trade off vergence accuracy against the associated metabolic costs, producing high fidelity vergence eye movements obeying Sherrington’s law of reciprocal innervation.

scholarly journals The Development of Active Binocular Vision under Normal and Alternate Rearing Conditions

2020 ◽  
Author(s):  
Lukas Klimmasch ◽  
Johann Schneider ◽  
Alexander Lelais ◽  
Bertram E. Shi ◽  
Jochen Triesch
Keyword(s):  
Visual Cortex ◽  
Binocular Vision ◽  
Cortical Neurons ◽  
Orientation Tuning ◽  
Active Perception ◽  
Efficient Coding ◽  
Rearing Conditions ◽  
Active Binocular Vision ◽  
Experimental Findings ◽  
Visual Cortical

AbstractThe development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereogramms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.

scholarly journals The development of active binocular vision under normal and alternate rearing conditions

eLife ◽  
2021 ◽  
Vol 10 ◽  
Author(s):  
Lukas Klimmasch ◽  
Johann Schneider ◽  
Alexander Lelais ◽  
Maria Fronius ◽  
Bertram Emil Shi ◽  
...  
Keyword(s):  
Binocular Vision ◽  
Cortical Neurons ◽  
Orientation Tuning ◽  
Active Perception ◽  
Efficient Coding ◽  
Rearing Conditions ◽  
Random Dot Stereograms ◽  
Active Binocular Vision ◽  
Experimental Findings ◽  
Visual Cortical

The development of binocular vision is an active learning process comprising the development of disparity tuned neurons in visual cortex and the establishment of precise vergence control of the eyes. We present a computational model for the learning and self-calibration of active binocular vision based on the Active Efficient Coding framework, an extension of classic efficient coding ideas to active perception. Under normal rearing conditions with naturalistic input, the model develops disparity tuned neurons and precise vergence control, allowing it to correctly interpret random dot stereograms. Under altered rearing conditions modeled after neurophysiological experiments, the model qualitatively reproduces key experimental findings on changes in binocularity and disparity tuning. Furthermore, the model makes testable predictions regarding how altered rearing conditions impede the learning of precise vergence control. Finally, the model predicts a surprising new effect that impaired vergence control affects the statistics of orientation tuning in visual cortical neurons.

Distributed spatial coding in the superior colliculus: A review

1991 ◽  
Vol 6 (1) ◽  
pp. 3-13 ◽  
Author(s):  
James T. McIlwain
Keyword(s):  
Eye Movements ◽  
Superior Colliculus ◽  
Receptive Fields ◽  
Saccadic Eye Movements ◽  
Visual Direction ◽  
Saccade Amplitude ◽  
Spatial Coding ◽  
Distributed Coding

AbstractThis paper reviews evidence that the superior colliculus (SC) of the midbrain represents visual direction and certain aspects of saccadic eye movements in the distribution of activity across a population of cells. Accurate and precise eye movements appear to be mediated, in part at least, by cells of the SC that have large sensory receptive fields and/or discharge in association with a range of saccades. This implies that visual points or saccade targets are represented by patches rather than points of activity in the SC. Perturbation of the pattern of collicular discharge by focal inactivation modifies saccade amplitude and direction in a way consistent with distributed coding. Several models have been advanced to explain how such a code might be implemented in the colliculus. Evidence related to these hypotheses is examined and continuing uncertainties are identified.

scholarly journals Visual Impairment Caused by Monovision Surgical Design

2021 ◽  
Author(s):  
Humberto Dória Silva ◽  
Rostan Silvestre da Silva ◽  
Eduardo Dória Silva ◽  
Maria Tamires Dória Silva ◽  
Cristiana Pereira Dória ◽  
...  
Keyword(s):  
Visual Field ◽  
Binocular Vision ◽  
Trabecular Meshwork ◽  
Human Vision ◽  
Implantation Technique ◽  
Refractive Errors ◽  
Mobile Mass ◽  
Surgical Implantation ◽  
The Brain ◽  
Continuous Progression

Neurophysiological anatomy of natural binocular vision shows the need to focus with both eyes to jointly produce the two corneas accommodation, correcting, in a compensatory way, the divergences inherent in the two different images, of the same visual field projected in the two distinct spaces, the two retinas. Corneal accommodation is part of the forced convection mechanism for the transfer of mobile mass in the cornea, trabecular meshwork and retina, to inhibit the accumulation of dehydrated intraocular metabolic residue, which can cause refractive errors in the cornea, obstruction of the trabecular meshwork and reduction of the amplitude of the signals produced by the phototransducers and sent to the brain. The IOL monovision surgical implantation technique differs from the physiology of natural binocular vision, which can cause after surgery disorders, described in this chapter, in that it imposes a different adaptation from the neurophysiological anatomy of human vision in addition to favoring the continuous progression of residue accumulation dehydrated intraocular metabolic and stimulate ocular.

Eye Position Compensation Improves Estimates of Response Magnitude and Receptive Field Geometry in Alert Monkeys

2007 ◽  
Vol 97 (5) ◽  
pp. 3439-3448 ◽  
Author(s):  
Yamei Tang ◽  
Alan Saul ◽  
Moshe Gur ◽  
Stephanie Goei ◽  
Elsie Wong ◽  
...  
Keyword(s):  
Eye Movements ◽  
Receptive Field ◽  
Receptive Fields ◽  
Eye Position ◽  
Stimulus Position ◽  
Fixational Eye Movements ◽  
Field Geometry ◽  
Receptive Field Subregions ◽  
Movement Compensation ◽  
Definition Of

Studies of visual function in behaving subjects require that stimuli be positioned reliably on the retina in the presence of eye movements. Fixational eye movements scatter stimuli about the retina, inflating estimates of receptive field dimensions, reducing estimates of peak responses, and blurring maps of receptive field subregions. Scleral search coils are frequently used to measure eye position, but their utility for correcting the effects of fixational eye movements on receptive field maps has been questioned. Using eye coils sutured to the sclera and preamplifiers configured to minimize cable artifacts, we reexamined this issue in two rhesus monkeys. During repeated fixation trials, the eye position signal was used to adjust the stimulus position, compensating for eye movements and correcting the stimulus position to place it at the desired location on the retina. Estimates of response magnitudes and receptive field characteristics in V1 and in LGN were obtained in both compensated and uncompensated conditions. Receptive fields were narrower, with steeper borders, and response amplitudes were higher when eye movement compensation was used. In sum, compensating for eye movements facilitated more precise definition of the receptive field. We also monitored horizontal vergence over long sequences of fixation trials and found the variability to be low, as expected for this precise behavior. Our results imply that eye coil signals can be highly accurate and useful for optimizing visual physiology when rigorous precautions are observed.

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