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Weight illusions explained by efficient coding based on correlated natural statistics.

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The Size-Weight Illusion (SWI), where smaller objects seem heavier, is explained by efficient sensory coding. This model shows how our brains adapt to common object properties, predicting perceptual biases like the SWI and Material-Weight Illusion (MWI).

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Area of Science:

  • Cognitive Neuroscience
  • Perception Science
  • Computational Neuroscience

Background:

  • Human perception often relies on integrating visual and haptic information.
  • The Size-Weight Illusion (SWI) contradicts naive Bayesian predictions, where smaller objects of equal weight are perceived as heavier.
  • Existing models struggle to fully explain the SWI and related illusions.

Purpose of the Study:

  • To provide a normative explanation for the Size-Weight Illusion (SWI) based on efficient coding principles.
  • To demonstrate how the joint distribution of object properties in the environment influences perceptual fidelity.
  • To quantitatively predict the SWI using Bayesian estimation informed by efficient encoding.

Main Methods:

  • Developed an efficient coding model based on the natural statistics of object properties (mass and volume).
  • Analyzed human observers' weight estimation precision as a function of object mass and volume.
  • Used Bayesian estimation, incorporating efficient encoding's discriminability gradients, to predict perceptual biases.

Main Results:

  • Perceptual precision in weight estimation aligns with the natural joint distribution of object mass and volume.
  • The SWI is quantitatively predicted by Bayesian inference under efficient encoding constraints.
  • The Material-Weight Illusion (MWI) is also explained by this framework, considering visual cues about density.

Conclusions:

  • Efficient coding provides a unifying framework for understanding the SWI and MWI.
  • Perceptual biases arise from the brain's optimal encoding of statistically prevalent environmental properties.
  • This model generalizes to other sensory modalities and perceptual phenomena influenced by natural correlations.