Abstract
In order to investigate under which assumptions one can expect to determine the probabilistic response of a neural unit to an incoming stochastic excitation, we propose a model that endows the neuron with a variable threshold. It is shown that a fairly complete statistical description of the input-output relationships can be obtained when the input is Poisson, non-homogeneous Poisson and, finally, any stationary continuous stochastic process.
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Ricciardi, L.M., Ventriglia, F. Probabilistic models for determining the input-output relationship in formalized neurons. Kybernetik 7, 175–183 (1970). https://doi.org/10.1007/BF00289404
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DOI: https://doi.org/10.1007/BF00289404