Noise-assisted traffic of spikes through neuronal junctions

The presence of noise, i.e., random fluctuations, in the nervous system rai ses at least two different questions. First, is there a constructive role n oise can play for signal transmission in a neuron channel? Second, what is the advantage of the power spectra observed for the neuron activity to be s haped like 1/f(k)? To address these questions a simple stochastic model for a junction in neural spike traffic channels is presented. Side channel tra ffic enters main channel traffic depending on the spike rate of the latter one. The main channel traffic itself is triggered by various noise processe s such as Poissonian noise or the zero crossings of Gaussian 1/f(k) noise w hereas the variation of the exponent k gives rise to a maximum of the overa ll traffic efficiency. It is shown that the colored noise is superior to th e Poissonian and, in certain cases, to deterministic, periodically ordered traffic. Further, if this periodicity itself is modulated by Gaussian noise with different spectral exponents k, then such modulation can lead to nois e-assisted traffic as well. The model presented can also be used to conside r car traffic at a junction between a main and a side road and to show how randomness can enhance the traffic efficiency in a network. (C) 2001 Americ an Institute of Physics.