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Perceptual dominance time distributions in multistable visual perception.

Y H Zhou1, J B Gao, K D White

  • 1Department of Electrical and Computer Engineering, EB 559, University of Florida, Gainesville, FL 32611, USA.

Biological Cybernetics
|April 16, 2004
PubMed
Summary
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Perceptual multistability, where perception shifts with unchanging stimuli, is often best modeled by lognormal distributions. Minor adjustments suggest random fractal theory may explain these neural dynamics.

Area of Science:

  • Cognitive Neuroscience
  • Computational Neuroscience
  • Psychophysics

Background:

  • Perceptual multistability offers insights into neural dynamics.
  • Understanding the statistical properties of perceptual dominance is key.

Purpose of the Study:

  • To statistically analyze perceptual dominance time series.
  • To compare fits of lognormal, gamma, and Weibull distributions to these data.
  • To explore potential underlying theoretical frameworks.

Main Methods:

  • Collected 56 perceptual dominance time series for Necker cube, ambiguous motion, and binocular rivalry.
  • Generated histograms of perceptual dominance durations.
  • Applied Kolmogorov-Smirnov goodness-of-fit tests to compare data with theoretical distributions.

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Main Results:

  • Lognormal distribution provided an acceptable fit in 40 out of 56 cases, being the sole fit in 24.
  • Gamma and Weibull distributions were acceptable in fewer cases and never the sole fit.
  • Adjustments to the lognormal model improved fits when initially rejected.

Conclusions:

  • Lognormal distributions are a strong candidate for modeling perceptual dominance durations.
  • Random fractal theory may offer a framework for understanding the mechanisms of multistable perception.