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Ring models of binocular rivalry and fusion

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Abstract

When similar visual stimuli are presented binocularly to both eyes, one perceives a fused single image. However, when the two stimuli are distinct, one does not perceive a single image; instead, one perceives binocular rivalry. That is, one perceives one of the stimulated patterns for a few seconds, then the other for few seconds, and so on – with random transitions between the two percepts. Most theoretical studies focus on rivalry, with few considering the coexistence of fusion and rivalry. Here we develop three distinct computational neuronal network models which capture binocular rivalry with realistic stochastic properties, fusion, and the hysteretic transition between. Each is a conductance-based point neuron model, which is multi-layer with two ocular dominance columns (L & R) and with an idealized “ring” architecture where the orientation preference of each neuron labels its location on a ring. In each model, the primary mechanism initiating binocular rivalry is cross-column inhibition, with firing rate adaptation governing the temporal properties of the transitions between percepts. Under stimulation by similar visual patterns, each of three models uses its own mechanism to overcome cross-column inhibition, and thus to prevent rivalry and allow the fusion of similar images: The first model uses cross-column feedforward inhibition from the opposite eye to “shut off” the cross-column feedback inhibition; the second model “turns on” a second layer of monocular neurons as a parallel pathway to the binocular neurons, rivaling out of phase with the first layer, and together these two pathways represent fusion; and the third model uses cross-column excitation to overcome the cross-column inhibition and enable fusion. Thus, each of the idealized ring models depends upon a different mechanism for fusion that might emerge as an underlying mechanism present in real visual cortex.

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Acknowledgements

We thank David Heeger and John Rinzel for very helpful and informative discussions.

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Authors and Affiliations

  1. Integrated Program in Neuroscience, McGill University, 3801 Rue Université, Montréal, QC, H3A 2B4, Canada

    Ziqi Wang

  2. New York University – Courant Institute of Mathematical Science, 251 Mercer Street, New York, NY, 10012, USA

    Wei Dai & David W. McLaughlin

  3. New York University – Tandon School of Engineering, 6 Metro Tech Center, Brooklyn, NY, 11201, USA

    David W. McLaughlin

  4. New York University Shanghai, 1555 Century Ave, Pudong, Shanghai, 200122, China

    David W. McLaughlin

  5. Neuroscience Institute at NYU Langone Medical Center, Science Building, 435 East 30th Street, New York, NY, 10016, USA

    David W. McLaughlin

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  1. Ziqi Wang
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  2. Wei Dai
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Correspondence to David W. McLaughlin.

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Wang, Z., Dai, W. & McLaughlin, D.W. Ring models of binocular rivalry and fusion. J Comput Neurosci 48, 193–211 (2020). https://doi.org/10.1007/s10827-020-00744-7

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  • DOI: https://doi.org/10.1007/s10827-020-00744-7

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