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Visual System

Visual System

Light enters the eye through the cornea, a transparent, dome-shaped surface covering the surface of the eyeball that helps to direct and focus incoming light. This light is then channeled toward the pupil, an adjustable opening whose size is controlled by the iris. The iris, a pigmented muscle, regulates the amount of light entering the eye by contracting or dilating the pupil, thereby ensuring optimal light levels for clear vision.
Once through the pupil, the light passes through the lens, a...

Vision

Vision

Vision is the result of light being detected and transduced into neural signals by the retina of the eye. This information is then further analyzed and interpreted by the brain. First, light enters the front of the eye and is focused by the cornea and lens onto the retina—a thin sheet of neural tissue lining the back of the eye. Because of refraction through the convex lens of the eye, images are projected onto the retina upside-down and reversed.

Depth Perception and Spatial Vision

Depth Perception and Spatial Vision

Depth perception is the ability to perceive objects three-dimensionally. It relies on two types of cues: binocular and monocular. Binocular cues depend on the combination of images from both eyes and how the eyes work together. Since the eyes are in slightly different positions, each eye captures a slightly different image. This disparity between images, known as binocular disparity, helps the brain interpret depth. When the brain compares these images, it determines the distance to an object.

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Related Experiment Video

Updated: Mar 6, 2026

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Computational Modeling of Retinal Neurons for Visual Prosthesis Research - Fundamental Approaches

Published on: June 21, 2022

Simplification of Visual Rendering in Simulated Prosthetic Vision Facilitates Navigation.

Victor Vergnieux¹, Marc J-M Macé¹, Christophe Jouffrais¹

¹Université de Toulouse and CNRS, IRIT, UMR5505, Toulouse, France.

Artificial Organs

|March 22, 2017

Summary

This summary is machine-generated.

Simulated prosthetic vision using computer vision algorithms significantly improved navigation and reduced cognitive load for low-resolution implants. Specific rendering strategies, like distance-based or wireframe, enhance wayfinding and cognitive mapping in unknown environments.

Keywords:

Blind Computer vision Navigation Retinal implant Spatial cognition Visual neuroprostheses Wayfinding

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Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Integrating Visual Psychophysical Assays within a Y-Maze to Isolate the Role that Visual Features Play in Navigational Decisions

Published on: May 2, 2019

Area of Science:

Neuroscience
Computer Vision
Biomedical Engineering

Background:

Visual neuroprostheses aim to restore vision but face limitations in resolution and functionality.
Simulated prosthetic vision (SPV) is crucial for evaluating implant capabilities, including navigation.
Current electrode arrays lack the resolution for effective navigation without advanced visual processing.

Purpose of the Study:

To evaluate navigation abilities with simulated low-resolution prosthetic vision.
To compare the effectiveness of different computer vision algorithms for enhancing visual rendering in a wayfinding task.
To assess the impact of rendering strategies on navigation performance and cognitive load.

Main Methods:

Simulated a low-resolution electrode array (15 × 18 electrodes).
Compared four visual rendering strategies: control (average brightness), limited vision distance (3, 6, 9m), distance-based rendering, and wireframe rendering.
Assessed navigation performance and cognitive load in a wayfinding task within an unknown environment.

Main Results:

All tested rendering strategies, except the 3m vision distance limitation, improved navigation performance.
Tested renderings significantly decreased cognitive load compared to the control.
Distance-based and wireframe renderings enhanced cognitive mapping of the environment.

Conclusions:

Low-resolution visual neuroprostheses can support wayfinding tasks with appropriate computer vision algorithms.
Optimized visual rendering strategies are essential for effective navigation with prosthetic vision.
Future visual neuroprosthetic development should incorporate advanced computer vision for enhanced spatial awareness and navigation.