Chaos shapes transient synchrony activities and switchings in the excitatory-inhibitory networks

Chaotic dynamics have been evidenced in experimental data and numerical simulations ranging from the most straightforward individual neurons to the more complex neural groups. Nevertheless, whether chaotic behavior significantly contributes to the emergence of phase shift and spontaneous switchings between transient synchrony activities is subtle and remains elusive. We investigated the emergence of spontaneous transient synchrony activities and self-induced switchings in an excitatory-inhibitory network. We demonstrate that the dynamic nature of isolated neurons plays an essential role in the emergence of chaotic behavior, thereby affecting spontaneous transient synchrony and types of phase shift. We also show that the neural network of the cells with chaotic characteristics after synaptic interactions exhibits a broader range of excitatory transient synchronous dynamics. Our results offer several possibilities for explaining sensory perception and brain disease observed in experiments.