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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.

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...

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.

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.

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...

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,...

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Related Experiment Video

Updated: Nov 9, 2025

Using Looming Visual Stimuli to Evaluate Mouse Vision

Using Looming Visual Stimuli to Evaluate Mouse Vision

Published on: June 13, 2019

The Hierarchical Evolution in Human Vision Modeling.

Dana H Ballard¹, Ruohan Zhang¹

¹Department of Computer Science, The University of Texas at Austin.

Topics in Cognitive Science

|April 10, 2021

Summary

This summary is machine-generated.

Computational models of primate vision advanced with David Marr's framework. This review details how algorithm descriptions evolved into distinct levels, forming a hierarchical organization.

Keywords:

Active vision Bayes hierarchies Human gaze behaviors Marr's paradigm Reinforcement learning Visual routines

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Last Updated: Nov 9, 2025

Using Looming Visual Stimuli to Evaluate Mouse Vision

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Creating Objects and Object Categories for Studying Perception and Perceptual Learning

Published on: November 2, 2012

Author Spotlight: Insights into Visual Cortex Research Through Wide-View fMRI Mapping

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Published on: December 8, 2023

Area of Science:

Computational Neuroscience
Computer Vision
Artificial Intelligence

Background:

David Marr's tripartite framework (problem formulation, algorithm, neural implementation) significantly advanced computational models of primate vision.
Subsequent developments in robotics and computational modeling refined algorithmic descriptions into distinct, complementary levels.

Purpose of the Study:

To trace the historical development of computational vision models.
To illustrate the evolution of algorithmic descriptions in computational vision.
To explain the emergence of hierarchical organizational perspectives in vision science.

Main Methods:

Historical review of computational vision research.
Analysis of the evolution of algorithmic levels in vision modeling.
Examination of the conceptual shifts leading to hierarchical organization.

Main Results:

Marr's framework provided an initial structure for understanding vision computation.
Parallel advancements in robotics and modeling introduced multi-level algorithmic descriptions.
These developments led to a more nuanced, hierarchical understanding of visual processing.

Conclusions:

The field has moved beyond Marr's initial framework to a more complex, hierarchical model of vision.
Understanding the evolution of these models is crucial for future research in computational neuroscience and AI.