Neuronal adaptation as well as interdischarge interval correlations have been shown to be
functionally important properties of physiological neurons. We explore the dynamics of a …

We examine analytically the existence and stability of phase-locked states in a weakly
heterogeneous neuronal network. We consider a model of N neurons with all-to-all synaptic …

How does a neuron vary its mean output firing rate if the input changes from random to
oscillatory coherent but noisy activity? What are the critical parameters of the neuronal …

Networks of stochastic spiking neurons are interesting models in the area of theoretical
neuroscience, presenting both continuous and discontinuous phase transitions. Here, we …

Нейронауки в современной биологии по количеству работающих физиков и
математиков занимают одно из ведущих мест, соперничая с молекулярной генетикой и …

Computational neuroscience is dominated by a few paradigmatic models, but it remains an
open question whether the existing modelling frameworks are sufficient to explain observed …

As a new brain‐inspired computational model of artificial neural networks, spiking neural
networks transmit and process information via precisely timed spike trains. Constructing …

Understanding the mechanisms that lead to oscillatory activity in the brain is an ongoing
challenge in computational neuroscience. Here, we address this issue by considering a …

Oscillatory neural dynamics are an inseparable part of mammalian sleep. Characteristic
rhythms are associated with different sleep stages and variable levels of sleep pressure, but …

Event-driven simulation strategies were proposed recently to simulate integrate-and-fire (IF)
type neuronal models. These strategies can lead to computationally efficient algorithms for …