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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.

The Retina

The Retina

The retina is a layer of nervous tissue at the back of the eye that transduces light into neural signals. This process, called phototransduction, is carried out by rod and cone photoreceptor cells in the back of the retina.

Anatomy of the Eyeball

Anatomy of the Eyeball

The eye is a spherical, hollow structure composed of three tissue layers. The outer layer — the fibrous tunic, comprises the sclera — a white structure — and the cornea, which is transparent. The sclera encompasses some of the ocular surface, most of which is not visible. However, the 'white of the eye' is distinctively visible in humans compared to other species. The cornea, a clear covering at the front of the eye, enables light penetration. The eye's middle layer, the vascular tunic,...

Photoreceptors and Visual Pathways

Photoreceptors and Visual Pathways

At the molecular level, visual signals trigger transformations in photopigment molecules, resulting in changes in the photoreceptor cell's membrane potential. The photon's energy level is denoted by its wavelength, with each specific wavelength of visible light associated with a distinct color. The spectral range of visible light, classified as electromagnetic radiation, spans from 380 to 720 nm. Electromagnetic radiation wavelengths exceeding 720 nm fall under the infrared category, whereas...

Color Vision

Color Vision

Color perception begins in the retina, the light-sensitive layer at the back of the eye. Two main theories explain how colors are seen: the trichromatic theory and the opponent-process theory. The trichromatic theory, proposed by Thomas Young in 1802 and extended by Hermann von Helmholtz in 1852, suggests that color vision is based on three types of cone receptors in the retina. These cones are sensitive to different but overlapping ranges of wavelengths corresponding to red, blue, and green.

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Related Experiment Video

Updated: Jun 24, 2026

Using Looming Visual Stimuli to Evaluate Mouse Vision

Using Looming Visual Stimuli to Evaluate Mouse Vision

Published on: June 13, 2019

Visual system based on artificial retina for motion detection.

Francisco Barranco¹, Javier Díaz, Eduardo Ros

¹Department of Computer Architecture and Technology, University of Granada, 18071 Granada, Spain. fbarranco@atc.ugr.es

IEEE Transactions on Systems, Man, and Cybernetics. Part B, Cybernetics : a Publication of the IEEE Systems, Man, and Cybernetics Society

|April 14, 2009

Summary

This summary is machine-generated.

This study introduces a bioinspired model for spatiotemporal feature detection using an artificial retina. The developed system enhances motion processing accuracy and offers a versatile attention operator for focusing on various visual cues.

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Area of Science:

Computational neuroscience
Artificial intelligence
Computer vision

Background:

Traditional computer vision systems often struggle with real-time processing of dynamic visual information.
Bio-inspired approaches offer novel solutions by mimicking biological sensory systems like the retina.

Purpose of the Study:

To develop a bioinspired computational model for detecting spatiotemporal features.
To enhance motion processing accuracy and system stability using artificial retina principles.

Main Methods:

Utilized artificial retina response models with event-driven processing and specialized cells for contrast and temporal information.
Implemented a multiscale, rank-order coding scheme to optimize motion detection based on local contrast.
Developed an improved bioinspired matching algorithm by integrating temporal features.

Main Results:

Demonstrated that motion processing accuracy is significantly influenced by local contrast levels.
Achieved a bioinspired matching algorithm with high stability, low error rates, and reduced computational cost.
Introduced a dynamic multimodal attention operator for adaptive focus on motion, color, and texture.

Conclusions:

The bioinspired model effectively detects spatiotemporal features, improving upon existing methods.
The system's performance in motion processing is robust and adaptable to different visual targets.
This research provides a foundation for advanced event-driven visual processing systems.