Research article summary (published 30 Jan 2002):

A stochastic model of multistable visual perception.

Full Abstract

Multistability in vision is an intriguing phenomenon that is currently not well understood. In this paper, we present a new, stochastic model for multistable visual perception. It is based on results of time series analysis of experimental data, yielding evidence for it being a linear, stochastic process. This is the outcome of testing for unstable periodic orbits and comparing the correlation dimension of the data to that of white noise. In the model, all degrees of freedom but one can be determined by general knowledge, thus resulting in a high degree of parsimony. The remaining parameter is used to model the individual characteristics that vary between subjects. Fitting simulations to the experimental data proves the parameter to be in a physiologically highly plausible range.

Author information

Author/s: Merk, I (I); Schnakenberg, J (J);

Affiliation: Gerling Global Reinsurance Company, Cologne, Germany.

Journal and publication information

Publication Type: Journal Article

Journal: Biological cybernetics (Biol Cybern), published in Germany. (Language: eng)

Reference: 2002-Feb; vol 86 (issue 2) : pp 111-6

Dates: Created 2002/03/22; Completed 2002/09/03; Revised 2004/11/17;

PMID: 11908839, status: MEDLINE (last retrieved date: 2/18/2009)

Sourced from the National Library of Medicine. Abstract text and other information may be subject to copyright.

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MeSH headings (categories)

This article was linked to the MeSH Headings (categories) shown below.

Depth Perception - physiology Humans Markov Chains Models, Neurological

Models, Neurological Optical Illusions Photic Stimulation Stochastic Processes

Note: Bold headings indicate primary MeSH headings or qualifiers.

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