Alternation rate in perceptual bistability is maximal at and symmetric around equi-dominance.

When an ambiguous stimulus is viewed for a prolonged time, perception alternates between the different possible interpretations of the stimulus. The alternations seem haphazard, but closer inspection of their dynamics reveals systematic properties in many bistable phenomena. Parametric manipulations result in gradual changes in the fraction of time a given interpretation dominates perception, often over the entire possible range of zero to one. The mean dominance durations of the competing interpretations can also vary over wide ranges (from less than a second to dozens of seconds or more), but finding systematic relations in how they vary has proven difficult. Following the pioneering work of W. J. M. Levelt (1968) in binocular rivalry, previous studies have sought to formulate a relation in terms of the effect of physical parameters of the stimulus, such as image contrast in binocular rivalry. However, the link between external parameters and "stimulus strength" is not as obvious for other bistable phenomena. Here we show that systematic relations readily emerge when the mean dominance durations are examined instead as a function of "percept strength," as measured by the fraction of dominance time, and provide theoretical rationale for this observation. For three different bistable phenomena, plotting the mean dominance durations of the two percepts against the fraction of dominance time resulted in complementary curves with near-perfect symmetry around equi-dominance (the point where each percept dominates half the time). As a consequence, the alternation rate reaches a maximum at equi-dominance. We next show that the observed behavior arises naturally in simple double-well energy models and in neural competition models with cross-inhibition and input normalization. Finally, we discuss the possibility that bistable perceptual switches reflect a perceptual "exploratory" strategy, akin to foraging behavior, which leads naturally to maximal alternation rate at equi-dominance if perceptual switches come with a cost.

[1]  R. Herrnstein On the law of effect. , 1970, Journal of the experimental analysis of behavior.

[2]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[3]  Hermann Haken A Brain Model For Vision in Terms of Synergetics , 1994 .

[4]  Charles Wheatstone F.R.S. XXXVI. Contributions to the physiology of vision.—Part the First. On the some remarkable, and hitherto unobserved, phænomena of binocular vision , 1852 .

[5]  Richard H. A. H. Jacobs,et al.  The time course of binocular rivalry reveals a fundamental role of noise. , 2006, Journal of vision.

[6]  R J HERRNSTEIN,et al.  Relative and absolute strength of response as a function of frequency of reinforcement. , 1961, Journal of the experimental analysis of behavior.

[7]  P. Bressan,et al.  Occlusion and the perception of coherent motion , 1991, Vision Research.

[8]  R. Blake,et al.  A fresh look at the temporal dynamics of binocular rivalry , 1989, Biological Cybernetics.

[9]  N. Parga,et al.  Role of synaptic filtering on the firing response of simple model neurons. , 2004, Physical review letters.

[10]  S. R. Lehky Binocular rivalry is not chaotic , 1995, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[11]  N. Rubin,et al.  Dynamics of perceptual bi-stability : plaids and binocular rivalry compared , 2003 .

[12]  I. Merk,et al.  A stochastic model of multistable visual perception , 2002, Biological Cybernetics.

[13]  T. D. Albright,et al.  Transparency and coherence in human motion perception , 1990, Nature.

[14]  Nava Rubin,et al.  Maximum alternation rate in bi-stable perception occurs at equidominance: experiments and modeling , 2007, BMC Neuroscience.

[15]  W. Levelt On binocular rivalry , 1965 .

[16]  Hugh R Wilson,et al.  Computational evidence for a rivalry hierarchy in vision , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[17]  Carson C. Chow,et al.  A Spiking Neuron Model for Binocular Rivalry , 2004, Journal of Computational Neuroscience.

[18]  I. Ohzawa,et al.  Contrast gain control in the cat's visual system. , 1985, Journal of neurophysiology.

[19]  Hugh R Wilson,et al.  Minimal physiological conditions for binocular rivalry and rivalry memory , 2007, Vision Research.

[20]  Jeroen J. A. van Boxtel,et al.  Dichoptic masking and binocular rivalry share common perceptual dynamics. , 2007, Journal of vision.

[21]  Charles Wheatstone,et al.  Contributions to the Physiology of Vision. , 1837 .

[22]  Pascal Mamassian,et al.  Temporal dynamics in bistable perception. , 2005, Journal of vision.

[23]  Yee-Joon Kim,et al.  Stochastic resonance in binocular rivalry , 2006, Vision Research.

[24]  J. Hell,et al.  Motion-induced blindness in normal observers , 2022 .

[25]  I. Ohzawa,et al.  Contrast gain control in the cat visual cortex , 1982, Nature.

[26]  R. Blake © 2001 Kluwer Academic Publishers. Printed in the Netherlands. 5 A Primer on Binocular Rivalry, Including Current Controversies , 2000 .

[27]  Riani,et al.  Stochastic resonance in the perceptual interpretation of ambiguous figures: A neural network model. , 1994, Physical review letters.

[28]  A. Borsellino,et al.  Reversal time distribution in the perception of visual ambiguous stimuli , 1972, Kybernetik.

[29]  H R Wilson,et al.  A model for motion coherence and transparency , 1994, Visual Neuroscience.

[30]  Nava Rubin,et al.  The dynamics of bi-stable alternation in ambiguous motion displays: a fresh look at plaids , 2003, Vision Research.

[31]  P. Walker Stochastic properties of binocular rivalry alternations , 1975 .

[32]  Charles Wheatstone On some remarkable and hitherto unobserved phenomena of binocular vision. , 1962 .

[33]  Nava Rubin,et al.  Balance between noise and adaptation in competition models of perceptual bistability , 2009, Journal of Computational Neuroscience.

[34]  Alan W Freeman,et al.  Multistage model for binocular rivalry. , 2005, Journal of neurophysiology.

[35]  J. Rinzel,et al.  Noise-induced alternations in an attractor network model of perceptual bistability. , 2007, Journal of neurophysiology.

[36]  H. Wallach On the visually perceived direction of motion ' ' by Hans Wallach : 60 years later , 1997 .

[37]  S. R. Lehky An Astable Multivibrator Model of Binocular Rivalry , 1988, Perception.

[38]  W J Levelt,et al.  Note on the distribution of dominance times in binocular rivalry. , 1967, British journal of psychology.

[39]  Nava Rubin,et al.  Dynamical characteristics common to neuronal competition models. , 2007, Journal of neurophysiology.

[40]  C. D. Weert,et al.  A test of Levelt's second proposition for binocular rivalry , 1993, Vision Research.

[41]  Min-Suk Kang Size matters: a study of binocular rivalry dynamics. , 2009, Journal of vision.

[42]  M. Carandini,et al.  Summation and division by neurons in primate visual cortex. , 1994, Science.

[43]  A. Brownstein,et al.  Some effects of relative reinforcement rate and changeover delay in response-independent concurrent schedules of reinforcement. , 1968, Journal of the experimental analysis of behavior.

[44]  P Killeen,et al.  The matching law. , 1972, Journal of the experimental analysis of behavior.

[45]  R. Blake A Neural Theory of Binocular Rivalry , 1989 .

[46]  Gustavo Deco,et al.  A model of binocular rivalry based on competition in IT , 2002, Neurocomputing.

[47]  Nava Rubin,et al.  Bi-stable depth ordering of superimposed moving gratings. , 2008, Journal of vision.

[48]  P. Christiaan Klink,et al.  General Validity of Levelt's Propositions Reveals Common Computational Mechanisms for Visual Rivalry , 2008, PloS one.

[49]  N. Logothetis,et al.  Visual competition , 2002, Nature Reviews Neuroscience.

[50]  N. Logothetis,et al.  Activity changes in early visual cortex reflect monkeys' percepts during binocular rivalry , 1996, Nature.