Neural field model of binocular rivalry waves in primary visual cortex
Paul Bressloff, Department of Mathematics, University of Utah
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Neural fields model the large-scale dynamics of spatially structured cortical networks in terms of continuum integro-differential equations, whose associated integral kernels represent the spatial distribution of neuronal synaptic connections. The advantage of a continuum rather than a discrete representation of spatially structured networks is that various techniques from the analysis of PDEs can be adapted to study the nonlinear dynamics of cortical patterns, oscillations and waves. In this talk we consider a neural field model of binocular rivalry waves in primary visual cortex (V1), which are thought to be the neural correlate of the wave-like propagation of perceptual dominance during binocular rivalry. Binocular rivalry is the phenomenon where perception switches back and forth between different images presented to the two eyes. The resulting fluctuations in perceptual dominance and suppression provide a basis for non-invasive studies of the human visual system and the identification of possible neural mechanisms underlying conscious visual awareness. 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. We end by discussing recent extensions of the work that incorporate the effects of noise, and the detailed functional architecture of V1.