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On Bayesian Simplicity in Human Visual Perceptual Organization.

Peter A van der Helm1

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Summary
This summary is machine-generated.

The idea that surprisal equals complexity in visual perception is wishful thinking. This Bayesian concept lacks formal support and conflates distinct principles of perceptual organization.

Keywords:
Bayes’ rule and Occam’s razorclassical and modern information theoryhuman visual perceptual organizationlikelihood and simplicity principles

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Area of Science:

  • Cognitive Science
  • Computational Neuroscience
  • Visual Perception

Background:

  • Bayesian approaches are increasingly used in visual perception research.
  • A recurring hypothesis posits that surprisal (negative log probability) quantifies perceptual complexity (shortest description length).
  • This idea attempts to unify the simplicity and likelihood principles in perceptual organization.

Purpose of the Study:

  • To critically re-examine and debunk the hypothesis equating surprisal with complexity in human visual perception.
  • To investigate the formal underpinnings and conceptual validity of this Bayesian idea.
  • To trace the potential origins of this misconception within Bayesian literature.

Main Methods:

  • Step-by-step deconstruction of the surprisal-complexity hypothesis.
  • Analysis of the relationship between Bayesian principles, descriptive simplicity, and perceptual organization.
  • Examination of a specific Bayesian textbook for potential errors and overinterpretations.

Main Results:

  • The hypothesis that surprisal directly expresses perceptual complexity is formally unsupported.
  • The idea conflates distinct concepts of simplicity and likelihood, despite some apparent rapprochement.
  • A likely origin of the misconception is identified in a pivotal mistake within a standard Bayesian textbook, which was subsequently overinterpreted.

Conclusions:

  • The proposed unification of surprisal and complexity in visual perception is not formally valid.
  • Researchers should carefully distinguish between surprisal, complexity, and principles of perceptual organization.
  • Clarifying the origins of this misconception is crucial for advancing Bayesian models of perception.