Abstract

The coexistence of electrical and chemical synaptic communication among excitatory cells has been evidenced by neuroscientists. Nevertheless, theoretical understanding of hybrid synaptic connections in diverse dynamical states of neural networks for self-organization and robustness, still has not been fully studied. Here, we present a model of neural network that includes chemical excitatory coupling in a way of small-world topology and electrical synaptic coupling among adjacent excitatory cells for excitatory population. Firstly, we use this model to investigate the effect of electrical synaptic coupling among excitatory cells on global network behavior with the goal of theoretically understanding mechanisms of generating rich firing patterns. Secondly, we further study the emergence of various firing ripple events by considering the variation of chemical synaptic inhibition and other factors, such as network densities. We found that the excitatory population has a tendency to synchronization as the weights of electrical synaptic coupling among excitatory cells are increased. Moreover, the existence of these electrical synaptic connections can cause various firing patterns of interest by slightly changing the chemical synaptic weights. Our results pave a way in the study of the dynamical mechanisms and computational significance of the contribution of mixed synapse in the neural functions.