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Related Concept Videos

Color Vision01:24

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.
Vision01:24

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.
Perceptual Constancy01:12

Perceptual Constancy

Perceptual constancy is the ability to recognize that objects remain consistent and unchanged even when their appearance varies due to changes in sensory input. There are four main types of perceptual constancy: size constancy, shape constancy, color constancy, and brightness constancy.
Size constancy is the recognition that an object remains the same size, even when its image on the retina changes. For instance, a bus is perceived to be large enough to carry people, even if it looks tiny from...
Photoreceptors and Visual Pathways01:22

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...

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Related Experiment Video

Updated: Jun 18, 2026

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior
09:49

Methods to Explore the Influence of Top-down Visual Processes on Motor Behavior

Published on: April 16, 2014

Predictive networks generate motion-induced color illusions.

Kyohei Ueda1,2, Lana Sinapayen3,4, Eiji Watanabe5,6,7

  • 1Laboratory of Neurophysiology, National Institute for Basic Biology, Higashiyama 5-1, Myodaiji, Okazaki, 444-8787, Aichi, Japan.

Scientific Reports
|June 16, 2026
PubMed
Summary
This summary is machine-generated.

Artificial neural networks explain subjective color (SC) perception. Models trained on natural videos show that moving object colors influence SC, suggesting predictive learning in the brain generates these visual experiences.

Keywords:
Cerebral cortexComputer modelsDeep learningSubjectivityVisual illusion

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Area of Science:

  • Neuroscience
  • Computational Vision
  • Artificial Intelligence

Background:

  • Subjective color (SC) is chromatic perception from achromatic stimuli, like Benham's top.
  • The neural basis of SC generation remains largely unknown despite extensive research.

Purpose of the Study:

  • To investigate the neural mechanisms underlying subjective color generation using artificial neural network (ANN) models.
  • To determine how predictive learning and visual input characteristics contribute to SC phenomena.

Main Methods:

  • Developed ANNs trained on natural videos using predictive learning principles.
  • Tested ANN ability to generate artificial subjective color (ASC) from achromatic stimuli.
  • Analyzed the influence of training data, including object colors and motion, on ASC characteristics.

Main Results:

  • ANN models successfully reproduced ASC from achromatic stimuli lacking chromatic information.
  • ASC properties were significantly modulated by the colors of moving objects in the training data.
  • Simplified stimuli confirmed that moving object colors are primary determinants of ASC.

Conclusions:

  • Predictive learning in ANNs can establish associations between motion patterns and colors, mimicking SC.
  • Cortical predictive mechanisms, informed by learned associations, may play a key role in generating SC phenomena.
  • Findings suggest a computational framework for understanding SC beyond purely retinal explanations.