Abstract The FitzHugh–Nagumo equation, originally conceived in neuroscience during the
1960s, became a key model providing a simplified view of excitable neuron cell behavior. Its …

The paper is devoted to the review of the coherence resonance phenomenon in excitable
neural networks. In particular, we explain how coherence can be measured and how noise …

Natural systems are undeniably subject to random fluctuations, arising from either
environmental variability or thermal effects. The consideration of those fluctuations supposes …

In this contribution, we investigate coherence resonance in map-based neural models in the
presence of Lévy noise. The impact of different parameters of Lévy noise on the oscillatory …

The nonlinear dynamics of a FitzHugh–Nagumo (FHN) neuron driven by an oscillating
current and perturbed by a Gaussian noise signal with different intensities D is investigated …

Neuronal brain network is a distributed computing system, whose architecture is dynamically
adjusted to provide optimal performance of sensory processing. A small amount of visual …

We study deterministic systems, composed of excitable units of FitzHugh–Nagumo type, that
are capable of self-generating and self-terminating strong deviations from their regular …

We consider a neuronal network model where an external stimulus excites some neurons,
which in turn activate other neurons in the network via synapse. We find that the regularity in …

The time elapsed model describes the firing activity of a homogenous assembly of neurons
thanks to the distribution of times elapsed since the last discharge. It gives a mathematical …

For some models of relevance in the social sciences we review some examples in which
system size plays an important role in the final outcome of the dynamics. We discuss the …