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Related Concept Videos

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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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Visualizing Visual Adaptation
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Object knowledge changes visual appearance: semantic effects on color afterimages.

Gary Lupyan1

  • 1University of Wisconsin-Madison, Madison, United States.

Acta Psychologica
|September 21, 2015
PubMed
Summary
This summary is machine-generated.

Prior knowledge influences color perception, making expected colors appear more vivid, especially with unreliable visual input. This effect is moderated by input certainty, impacting how we process visual information.

Keywords:
AfterimagesPerceptionPredictive codingTop-down effectsVisual knowledge

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Area of Science:

  • Cognitive Science
  • Neuroscience
  • Visual Perception

Background:

  • Predictive coding models suggest perception integrates current sensory input with prior experiences and expectations.
  • The same visual input can be perceived differently based on the influence of established priors.

Purpose of the Study:

  • To investigate how prior knowledge (priors) affects the vividness of color perception.
  • To determine if expected colors are perceived more vividly than unexpected colors, particularly under conditions of unreliable input.

Main Methods:

  • Utilized a modified 'Spanish Castle Illusion' to study color afterimages.
  • Compared afterimage strength for objects with intrinsic colors versus arbitrarily colored objects.
  • Manipulated the association between images and color priors (e.g., image orientation) and varied input certainty.

Main Results:

  • Expected (diagnostic) colors produced stronger afterimages than arbitrary colors, especially when color input was unreliable.
  • Afterimage strength differences diminished when the link between image and color priors was weakened (e.g., upside-down images).
  • Increased input certainty made unexpected colors easier to detect, aligning with predictive coding principles.

Conclusions:

  • Color appearance is modulated by prior knowledge and expectations, consistent with predictive coding frameworks.
  • The influence of priors on visual perception is dynamic and depends on the reliability and certainty of sensory input.
  • Phenomenological discounting of conflicting visual information is moderated by input certainty.