Underlying neural computations for some visual phenomena

In this paper we examine how a large array of neurons, and their associated neural circuitry, may determine known receptive field profile types and some well-known visual phenomena including Mach bands, edge enhancement, and visual masking of one signal by another. The neural model has a spatio-temporal structure and is described by a nonlinear integropartial differential difference equation with an isotropic Gabor kernel — a Gaussian apertured cosine modulation. Several simulations are presented.

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