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Neural field model of binocular rivalry waves

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Abstract

We present a neural field model of binocular rivalry waves in visual cortex. For each eye we consider a one-dimensional network of neurons that respond maximally to a particular feature of the corresponding image such as the orientation of a grating stimulus. Recurrent connections within each one-dimensional network are assumed to be excitatory, whereas connections between the two networks are inhibitory (cross-inhibition). Slow adaptation is incorporated into the model by taking the network connections to exhibit synaptic depression. We derive an analytical expression for the speed of a binocular rivalry wave as a function of various neurophysiological parameters, and show how properties of the wave are consistent with the wave-like propagation of perceptual dominance observed in recent psychophysical experiments. In addition to providing an analytical framework for studying binocular rivalry waves, we show how neural field methods provide insights into the mechanisms underlying the generation of the waves. In particular, we highlight the important role of slow adaptation in providing a “symmetry breaking mechanism” that allows waves to propagate.

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Notes

  1. From a mathematical perspective, it would also be possible to generate waves when the cross-inhibition is longer range than the excitatory connections, see Fig. 4. Which form is more realistic from the biological perspective depends on which classes of neurons are being taken into account by the neural field model. For example, in visual cortex it is known that excitatory pyramidal cells make both local synaptic contacts as well as longer-range horizontal connections. However, the latter innervate both excitatory and local inhibitory neurons so they could have a net inhibitory effect, thus providing a possible source of long-range inhibition; whether long-range connections generate net excitation or net inhibition also depends on stimulus conditions (Lund et al. 2003).

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Authors and Affiliations

  1. Mathematical Institute, University of Oxford, 24-29 St. Giles’, Oxford, OX1 3LB, UK

    Paul C. Bressloff & Matthew A. Webber

  2. Department of Mathematics, University of Utah, Salt Lake City, UT 84112-0090, USA

    Paul C. Bressloff

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  1. Paul C. Bressloff
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  2. Matthew A. Webber
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Correspondence to Paul C. Bressloff.

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Action Editor: Carson C. Chow

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Bressloff, P.C., Webber, M.A. Neural field model of binocular rivalry waves. J Comput Neurosci 32, 233–252 (2012). https://doi.org/10.1007/s10827-011-0351-y

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  • DOI: https://doi.org/10.1007/s10827-011-0351-y

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