Dynamic model of dual layer neural network for vertebrate retina

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Abstract
A neural network model was formulated to describe the spatiotemporal properties of the photoreceptor and horizontal cell responses to light in the vertebrate retina. The model consists of two layers, one of which represents the photoreceptor syncytium and the other the horizontal cell syncytium. Each syncytium is an array of elemental neurons, each of which is expressed by the coupling resistance between neighboring cells and membrane impedance. Corresponding elements of each syncytium interact reciprocally with synaptic weighting functions. The analytical solutions of the voltage responses to extrinsically applied current, which corresponds to the light-induced current, were obtained in the frequency domain. The model provides a computational framework of the early visual processing in the vertebrate retina.<>