A Neural Network Model for the Spatial and Temporal Response of Retinal Ganglion Cells
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This article introduces a quantitative model of early visual system function. The model is formulated to unify analyses of spatial and temporal information processing by the nervous system. Functional constraints of the model suggest mechanisms analogous to photoreceptors, bipolar cells, and retinal ganglion cells, which can be formally represented with first order differential equations. Preliminary numerical simulations and analytical results show that the same formal mechanisms can explain the behavior of both X (linear) and Y (nonlinear) retinal ganglion cell classes by simple changes in the relative width of the receptive field (RF) center and surround mechanisms. Specifically, an increase in the width of the RF center results in a change from X-like to Y-like response, in agreement with anatomical data on the relationship between α- and 𝛽-cell RF profiles. Simulations of model response to various spatio-temporal input patterns replicate many of the classical properties of X and Y cells, including transient (Y) versus sustained (X) responses, null-phase responses to alternating gratings in X cells, on-off or frequency doubling responses in Y cells, and phase-independent on-off responses in Y cells at high spatial frequencies. The model's formal mechanisms may be used in other portions of the visual system and more generally in nervous system structures involved with spatio-temporal information processing.
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