NOISE-ENHANCED TRANSMISSION OF TIME-MODULATED NEUROTRANSMITTER RANDOM POINT TRAINS IN A NOISY NEURON

Abstract

We numerically investigate the transmission of time-modulated random point trains in a conductance-based neuron model by including shot noise described as additive noise trains. The results show that additive noise trains can induce neuron responses exhibiting correlation with the temporally modulated random point trains. In addition, the additive noise power density can be increased up to an optimal value where the output signal-noise ratio (SNR) reaches a maximum value. This property of noise-enhanced transmission of random point trains can be related to the stochastic resonance (SR) phenomenon. More interestingly, we find that the SNR gain can exceed unity and can also be optimized by tuning the average rate of the input random point trains. The present study illustrates the potential to utilize the additive noise and temporally modulated random point trains for optimizing the response of the neuron to inputs, as well as a guidance in the design of information processing devices to random neuron spiking.