Effect of inhibitory firing patterns on the stochastic resonance in feed-forward-loop neuronal network motifs

Abstract

Neurons express diverse firing patterns in terms of their morphological, biochemical and electrophysiological properties. Different firing patterns can switch the information transmission in neuron network. However, it is not clear how the firing patterns of the neurons affect information transmission. Here we investigate the effect of different firing patterns of inhibitory neuron on network information transmission of triple-neuron feed-forward-loop motif. Results show that the stochastic response behavior can be optimized by certain noise intensity, which indicates stochastic resonance (SR) occurs in the neuronal network motifs. Changing the inhibitory neuron from burst spiking neurons to fast spiking neurons does not affect the optimal noise intensity. In the case of the same noise intensity and coupling coefficient, the bursting neurons produce higher transmission efficiency than the fast firing neurons. Different firing patterns of neuron in the output of the network motif achieved a greater impact on the transmission efficiency of the motif than the neuron located in the middle position. This simulation directly quantifies the influence of firing patterns on information transmission, which has great significance for improving signal transmission efficiency and detecting signals at different operating points.