Noise-induced cooperative dynamics and its control

The possibility to manipulate the purely noise-induced behaviour in the large ensemble of globally coupled excitable systems is central to my research work. We employ globally coupled noise-driven FitzHugh–Nagumo units as a prototype of excitable system, which serve as a rough model of a neural network. Such a network is capable of demonstrating various kinds of behaviour with non-synchronized or synchronized units, with the mean field demonstrating periodic or chaotic small oscillations, or periodic or aperiodic spiking. Delayed feedback control applied through the mean field is shown capable of manipulating the basic features of the network behaviour, namely, to induce or suppress collective synchrony, to regularize the system behaviour in both synchronous and non-syncrhonous states, to shift the basic time scales of oscillations. These results are relevant to the control of unwanted behaviour in neural networks. [Continues.]