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Coherence Resonance and Noise-Induced Synchronization in Hindmarsh–Rose Neural Network with Different Topologies

In this paper, we investigate coherence resonance (CR) and noise-induced synchronization in Hindmarsh–Rose (HR) neural network with three different types of topologies: regular, random, and small-world. It is found that the additive noise can induce CR in HR neural network with different topologies and its coherence is optimized by a proper noise level. It is also found that as coupling strength increases the plateau in the measure of coherence curve becomes broadened and the effects of network topology is more pronounced simultaneously. Moreover, we find that increasing the probability p of the network topology leads to an enhancement of noise-induced synchronization in HR neurons network.