Modeling of Synchronous Behaviors of Excitatory and Inhibitory Neurons in Complex Neuronal Networks

In the model of complex networks of excitatory (E) and inhibitory neurons (I), synchronous rhythmic firing patterns is investigated by using Hodgkin-Huxley (HH) type model. Various factors such as synaptic coupling strength, network topology and external input are considered as the main effects on synchronization behavior of the neuronal networks. It is found that when the network is small-world, the degree of synchronization will be improved with the adding edge probability increasing. As for the synaptic inhibition, without inhibitory interactions, neurons would not achieve synchronization. Then once the inhibitory neurons are added, the network would arrive synchrony. Furthermore, different external currents will induce different degree of the synchronization states. The crucial quantity is the expected frequencies of inputs per neuron. So choosing the input current at the appropriate frequency is the key point in enhancing the synchronization of the complex neuronal networks.