Noise enhancement of signal transduction by parallel arrays of nonlinear neurons with threshold and saturation

A classic model neuron with threshold and saturation is used to form parallel uncoupled neuronal arrays in charge of the transduction of a periodic or aperiodic noisy input signal. The impact on the transduction efficacy of added noises is investigated. In isolated neurons, improvement by noise is possible only in the subthreshold and in the strongly saturating regimes of the neuronal response. In arrays, improvement by noise is always reinforced, and it becomes possible in all regimes of operation, i.e. in the threshold, in the saturation, and also in the intermediate curvilinear part of the neuronal response. All the configurations of improvement by noise apply equally to periodic and to aperiodic signals. These results extend the possible forms of stochastic resonance or improvement by noise accessible in neuronal systems for the processing of information.

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