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Related Concept Videos

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...
The Wave Nature of Light02:12

The Wave Nature of Light

The nature of light has been a subject of inquiry since antiquity. In the seventeenth century, Isaac Newton performed experiments with lenses and prisms and was able to demonstrate that white light consists of the individual colors of the rainbow combined together. Newton explained his optics findings in terms of a "corpuscular" view of light, in which light was composed of streams of extremely tiny particles traveling at high speeds according to Newton's laws of motion.
Gestalt Principles of Perception01:21

Gestalt Principles of Perception

Gestalt principles provide a framework for understanding how humans perceive objects as unified wholes within their context. These principles are essential in explaining the cognitive processes that make sense of complex visual stimuli by organizing them into coherent groups. One fundamental principle is proximity, which posits that objects located close to each other are perceived as a collective group. For instance, when dots are positioned near one another, the visual system interprets them...
Cause and Effect01:53

Cause and Effect

While variables are sometimes correlated because one does cause the other, it could also be that some other factor, a confounding variable, is actually causing the systematic movement in our variables of interest. For instance, as sales in ice cream increase, so does the overall rate of crime. Is it possible that indulging in your favorite flavor of ice cream could send you on a crime spree? Or, after committing crime do you think you might decide to treat yourself to a cone?
Depth Perception and Spatial Vision01:15

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.
Interference and Diffraction02:18

Interference and Diffraction

Interference is a characteristic phenomenon exhibited by waves. When two electromagnetic waves interact with their peaks and troughs coinciding, a resulting wave with enhanced amplitude is produced. This is known as constructive interference. In this case, the two waves interacting are in phase with each other.

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Related Experiment Video

Updated: Jul 11, 2026

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

What are lightness illusions and why do we see them?

David Corney1, R Beau Lotto

  • 1UCL Institute of Ophthalmology, University College London, London, United Kingdom.

Plos Computational Biology
|October 3, 2007
PubMed
Summary

Visual illusions like brightness contrast arise because the brain learns to interpret ambiguous visual data from the natural world. This study shows artificial neural networks replicate human illusions by modeling this learning process.

Area of Science:

  • * Computational neuroscience and visual perception.
  • * Investigates the fundamental mechanisms underlying visual illusions.

Background:

  • * Lightness illusions are a key aspect of human perception, yet their origins remain under investigation.
  • * Traditional research often focuses on human physiology or perception directly.

Purpose of the Study:

  • * To model the natural visual world and the necessity for robust behavior to understand visual illusions.
  • * To determine if artificial systems trained on ecological visual statistics exhibit human-like illusions.

Main Methods:

  • * Artificial neural networks were trained to predict surface reflectance in synthetic 3D "dead-leaves" scenes under varied illumination.
  • * The models processed ambiguous visual data, simulating real-world visual input.

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

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Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
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Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

Published on: May 23, 2019

Related Experiment Videos

Last Updated: Jul 11, 2026

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation
06:53

Creating Virtual-hand and Virtual-face Illusions to Investigate Self-representation

Published on: March 1, 2017

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

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback
05:43

Applying Incongruent Visual-Tactile Stimuli during Object Transfer with Vibro-Tactile Feedback

Published on: May 23, 2019

Main Results:

  • * Trained networks accurately and robustly predicted reflectance, demonstrating effective learning from ambiguous data.
  • * Networks exhibited systematic "errors" mirroring human illusions, including brightness contrast and assimilation (White's illusion in 3D scenes).
  • * Observed subtle illusion variations, such as asymmetric brightness contrast, consistent with human perception.

Conclusions:

  • * Visual illusions stem from the ambiguity of natural stimuli and the brain's empirical resolution through learned statistical relationships.
  • * Illusions are a consequence of optimizing perception for real-world visual statistics, not unique to human neural machinery.
  • * Proposes a formal definition of illusion as a discrepancy between a stimulus's true and perceived source based on likelihood.