Excitement and synchronization of electrically coupled small-world neuronal network with synaptic plasticity

Excitement and synchronization of electrically coupled small-world neuronal network with synaptic plasticity are studied in this paper. The variation properties of synaptic weights are examined first, and then the effects of the synaptic learning coefficient, the coupling strength and the adding probability on the properties of degree of excitement and synchronization of the neuronal network are studied respectively. It is shown that synaptic learning suppresses over-excitement and helps synchronization for the neuronal network. Plus, both introduction of shortcuts and increase of the coupling strength do not affect the degree of excitement and are helpful in improving synchronization for the neuronal network.