Phase-disorder-induced firing activity in excitable neuronal networks with attractive and repulsive coupling

Regulating dynamics through intermittent interactions

In this article we experimentally demonstrate an efficient scheme to regulate the behavior of coupled nonlinear oscillators through dynamic control of their interaction. It is observed that introducing intermittency in the interaction term as a function of time or the system state predictably alters the dynamics of the constituent oscillators. Choosing the nature of the interaction, attractive or repulsive, allows for either suppression of oscillations or stimulation of activity. Two parameters Δ and τ, that reign the extent of interaction among subsystems, are introduced. They serve as a harness to access the entire range of possible behaviors from fixed points to chaos. For fixed values of system parameters and coupling strength, changing Δ and τ offers fine control over the dynamics of coupled subsystems. We show this experimentally using coupled Chua's circuits and elucidate their behavior for a range of coupling parameters through detailed numerical simulations.

Gating-signal propagation by a feed-forward neural motif

We study the signal propagation in a feed-forward motif consisting of three bistable neurons: Two input neurons receive input signals and the third output neuron generates the output. We find that a weak input signal can be propagated from the input neurons to the output neuron without amplitude attenuation. We further reveal that the initial states of the input neurons and the coupling strength act as signal gates and determine whether the propagation is enhanced or not. We also investigate the effect of the input signal frequency on enhanced signal propagation.