Synchronization transition in gap-junction-coupled leech neurons

The dependence of synchronization transition processes of coupled neurons with coexisting spiking and bursting on the control parameter, initial value, and attraction domain

“…A few recent works have focused on synchronization of coupled systems composed of single units that exhibit multi-stable or coexisting behaviors when isolated [29][30][31][32][33][34][35][36][37]; for example, the coupled system composed of two Rössler-like electronic circuits with coexisting chaotic attractors [29][30][31], two coupled Hénon maps with coexisting periodic behaviors [32], two optical bi-stable systems (with coexistence of fixed point and chaos, of fixed point and periodic attractor, and of two periodic attractors) transition from nonsynchronization to complete synchronization (CS) via various complex synchronous states as the coupling strength increases [33]. In addition to these unidirectionally coupled systems, there are investigations on the bidirectionally coupled systems with coexisting behaviors [34][35][36][37].…”

“…In addition to these unidirectionally coupled systems, there are investigations on the bidirectionally coupled systems with coexisting behaviors [34][35][36][37]. In a previous study [34], the synchronization transition process of two coupled neurons with coexistence of spiking and bursting, which lies between monostable spiking and monostable bursting as the control parameter is changed, was investigated. Three different cases of configurations of the two coupled neurons were considered (one neuron spiking and the other bursting, both bursting, and both spiking, which are here labeled as cases 1, 2, and 3 in the present paper, respectively).…”

Dynamic Behavior Analysis of a Class of Neurons Network Model

“…Biological nervous system is the extremely complex multi-level information network system interconnected by a huge number of neuron cells, therefore discharge activities of neurons and information encoding process exist complex nonlinear dynamical behavior [2][3][4][5][6][7] Neuron dynamics is the combination of neurophysiology and nonlinear dynamics, which becomes the hot spot in the current world cutting-edge research. Biology research shows that different discharge modes have different biological meanings and studies on the discharge of neurons have important meaning on dynamics and biology.…”

Synchronization in Quotient Network Based on Symmetry

“…Intensive research effort is made towards uncovering the effect of network structure on the network's synchronization behavior, such as the effects of average distance [11,12], heterogeneity [13], clustering [14], and weight distribution. In addition, the relationship of network failure with synchronization [15], generalized synchronization [16], and synchronization performance [16], were also extensively studied.…”