Role of Noise in Complex Networks of FitzHugh-Nagumo Neurons

This paper deals with the open question related to the role of noise in complex networks of interconnected FitzHugh-Nagumo neurons. In this paper this problem is faced with extensive simulations of different network topologies. The results show that several topologies behave in an optimal way with respect to the range of noise level leading to an improvement in the stimulus-response coherence, while other with respect to the maximum values of the performance index. The best results in terms of both the suitable noise level and high stimulus response coherence have been obtained when a diversity in neuron characteristic parameters has been introduced and the neurons have been connected in a small-world topology