Abstract
Based on a modified Hindmarsh–Rose model with electromagnetic induction being considered, rhythmicity and firing modes in modular neural network consisting of nonidentical neurons have been explored in detail. The global rhythmicity of the system shows a resonancelike behavior with the increase in the ratio of inactive neurons for strong coupling among neurons inside the subnetwork. We found that interaction between different subnetworks and electromagnetic induction parameter show the tendency to weaken dynamical robustness, whereas self-induction parameter could efficiently improve dynamical robustness of modular network. The dynamics of the active neuron on the road to aging transition is detected. The ratio of inactive neurons switches response-firing modes of the active neuron among spiking, periodic bursting and chaotic bursting. Our model system and results can provide new mechanism explanation for electrical activity in biological systems that are prone to suffer damage or deterioration.
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