Static nonlinearity in the retinal neuron network

The authors have uncovered several neuronal functions in the retinal neuron network that can be approximated by a cascade structure. Here, they present four examples: (1) Generation of primordial nonlinearity in C amacrine cells modelled by a Wiener structure. (2) Transformation of the primordial nonlinearity into a nonlinearity found in the N amacrine cells modelled by a Korenberg structure. (3) Generation of spike discharges modelled by a Wiener structure. (4) Control of contrast gain modelled by a Wiener structure. Neuronal processes that can be approximated by a static nonlinearity play important functions in the processing of signals in the retinal neuron network.