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.

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 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.

Peripheral Facial Features Guiding Eye Movements and Reducing Fixational Variability

2021 ◽  
Author(s):  
Nicole X Han ◽  
Puneeth N. Chakravarthula ◽  
Miguel P. Eckstein
Keyword(s):  
Eye Movements ◽  
Spatial Configuration ◽  
Oculomotor System ◽  
Facial Features ◽  
Robust Solution ◽  
The Face ◽  
And Gender ◽  
Social Importance ◽  
Fixation Variability

Face processing is a fast and efficient process due to its evolutionary and social importance. A majority of people direct their first eye movement to a featureless point just below the eyes that maximizes accuracy in recognizing a person's identity and gender. Yet, the exact properties or features of the face that guide the first eye movements and reduce fixational variability are unknown. Here, we manipulated the presence of the facial features and the spatial configuration of features to investigate their effect on the location and variability of first and second fixations to peripherally presented faces. Results showed that observers can utilize the face outline, individual facial features, and feature spatial configuration to guide the first eye movements to their preferred point of fixation. The eyes have a preferential role in guiding the first eye movements and reducing fixation variability. Eliminating the eyes or altering their position had the greatest influence on the location and variability of fixations and resulted in the largest detriment to face identification performance. The other internal features (nose and mouth) also contribute to reducing fixation variability. A subsequent experiment measuring detection of single features showed that the eyes have the highest detectability (relative to other features) in the visual periphery providing a strong sensory signal to guide the oculomotor system. Together, the results suggest a flexible multiple-cue approach that might be a robust solution to cope with how the varying eccentricities in the real world influence the ability to resolve individual feature properties and the preferential role of the eyes.

scholarly journals Unrestricted eye movements strengthen causal connectivity from hippocampal to oculomotor regions during scene construction

2021 ◽  
Author(s):  
Natalia Ladyka-Wojcik ◽  
Zhong-Xu Liu ◽  
Jennifer D. Ryan
Keyword(s):  
Eye Movements ◽  
Visual Processing ◽  
Oculomotor System ◽  
Visual Input ◽  
Causal Modeling ◽  
Oculomotor Control ◽  
Visual Stream ◽  
Functional Connections ◽  
Free Viewing ◽  
Scene Construction

Scene construction is a key component of memory recall, navigation, and future imagining, and relies on the medial temporal lobes (MTL). A parallel body of work suggests that eye movements may enable the imagination and construction of scenes, even in the absence of external visual input. There are vast structural and functional connections between regions of the MTL and those of the oculomotor system. However, the directionality of connections between the MTL and oculomotor control regions, and how it relates to scene construction, has not been studied directly in human neuroimaging. In the current study, we used dynamic causal modeling (DCM) to investigate this relationship at a mechanistic level using a scene construction task in which participants' eye movements were either restricted (fixed-viewing) or unrestricted (free-viewing). By omitting external visual input, and by contrasting free- versus fixed- viewing, the directionality of neural connectivity during scene construction could be determined. As opposed to when eye movements were restricted, allowing free viewing during construction of scenes strengthened top-down connections from the MTL to the frontal eye fields, and to lower-level cortical visual processing regions, suppressed bottom-up connections along the visual stream, and enhanced vividness of the constructed scenes. Taken together, these findings provide novel, non-invasive evidence for the causal architecture between the MTL memory system and oculomotor system associated with constructing vivid mental representations of scenes.

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