On the stochastic properties of the neural encoding mechanism of sound intensity
Keywords:Computer simulation, Functions, Mathematical models, Parameter estimation, Poisson distribution, Probability density function, Random processes, Signal encoding, Statistical methods, Neural encoding, Poisson process, Pulse-number distribution (PND), Stochastic properties
AbstractThe stochastic properties of the neural encoding mechanism of sound intensity were described. The homogeneous Poisson process was modified and extended to give a more realistic stochastic model that expressed the properties of auditory neurons quantitatively. A command program was written to control the different parameter values to study the effects of the different components on the mean-variance ratio. It was found that the ratio was a monotonic increasing function of dead time under a fixed firing rate, while it increased with increasing values of firing rate.
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