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Balance between noise and adaptation in competition models of perceptual bistability

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Abstract

Perceptual bistability occurs when a physical stimulus gives rise to two distinct interpretations that alternate irregularly. Noise and adaptation processes are two possible mechanisms for switching in neuronal competition models that describe the alternating behaviors. Either of these processes, if strong enough, could alone cause the alternations in dominance. We examined their relative role in producing alternations by studying models where by smoothly varying the parameters, one can change the rhythmogenesis mechanism from being adaptation-driven to noise-driven. In consideration of the experimental constraints on the statistics of the alternations (mean and shape of the dominance duration distribution and correlations between successive durations) we ask whether we can rule out one of the mechanisms. We conclude that in order to comply with the observed mean of the dominance durations and their coefficient of variation, the models must operate within a balance between the noise and adaptation strength—both mechanisms are involved in producing alternations, in such a way that the system operates near the boundary between being adaptation-driven and noise-driven.

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Author notes

  1. Asya Shpiro

    Present address: Department of Mathematics, Medgar Evers College, City University of New York, Brooklyn, New York, NY, 11225, USA

  2. Ruben Moreno-Bote

    Present address: Department of Brain and Cognitive Sciences, University of Rochester, Rochester, NY, 14627, USA

Authors and Affiliations

  1. Center for Neural Science, New York University, 4 Washington Place, New York, NY, 10003, USA

    Asya Shpiro, Ruben Moreno-Bote, Nava Rubin & John Rinzel

  2. Courant Institute of Mathematical Sciences, 251 Mercer St., New York, NY, 10012, USA

    John Rinzel

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  1. Asya Shpiro
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  4. John Rinzel
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Correspondence to Asya Shpiro.

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Shpiro, A., Moreno-Bote, R., Rubin, N. et al. Balance between noise and adaptation in competition models of perceptual bistability. J Comput Neurosci 27, 37–54 (2009). https://doi.org/10.1007/s10827-008-0125-3

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  • DOI: https://doi.org/10.1007/s10827-008-0125-3

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