title: Stability switches and multistability coexistence in a delay-coupled neural oscillators system.
abstract: In this paper, we present a neural network system composed of two delay-coupled neural oscillators, where each of these can be regarded as the dynamical system describing the average activity of neural population. Analyzing the corresponding characteristic equation, the local stability of rest state is studied. The system exhibits the switch phenomenon between the rest state and periodic activity. Furthermore, the Hopf bifurcation is analyzed and the bifurcation curve is given in the parameters plane. The stability of the bifurcating periodic solutions and direction of the Hopf bifurcation are exhibited. Regarding time delay and coupled weight as the bifurcation parameters, the Fold-Hopf bifurcation is investigated in detail in terms of the central manifold reduction and normal form method. The neural system demonstrates the coexistence of the rest states and periodic activities in the different parameter regions. Employing the normal form of the original system, the coexistence regions are illustrated approximately near the Fold-Hopf singularity point. Finally, numerical simulations are performed to display more complex dynamics. The results illustrate that system may exhibit the rich coexistence of the different neuro-computational properties, such as the rest states, periodic activities, and quasi-periodic behavior. In particular, some periodic activities can evolve into the bursting-type behaviors with the varying time delay. It implies that the coexistence of the quasi-periodic activity and bursting-type behavior can be obtained if the suitable value of system parameter is chosen.
authors.affiliation: School of Aerospace Engineering and Applied Mechanics, Tongji University, Shanghai 200092, China. zigensong@163.com
authors.forename: Zigen
authors.initials: Z
authors.lastname: Song
authors.forename: Jian
authors.initials: J
authors.lastname: Xu
mesh_terms: D000200:Action Potentials / Q000502:physiology; D001683:Biological Clocks; D008959:Models, Neurological; D009415:Nerve Net / Q000502:physiology*; D009716:Numerical Analysis, Computer-Assisted; D013997:Time Factors