Stochastic resonance driven by time-modulated neurotransmitter random point trains

Information transmitting by temporally modulated random point trains, such as neurotransmitter quanta and spikes, which are neither additive signal and noise nor diffusion approximated additive signal and noise, is studied. We demonstrate that tuning the input train's average rate can optimize the response of an integrate-and-fire model neuron to a signal modulated point train. The characteristics of this phenomenon and its biological significance are discussed.