We derive the mean-field equations arising as the limit of a network of interacting spiking
neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of …

In this paper we establish limit theorems for a class of stochastic hybrid systems (continuous
deterministic dynamics coupled with jump Markov processes) in the fluid limit (small jumps …

The brain's activity is characterized by the interaction of a very large number of neurons that
are strongly affected by noise. However, signals often arise at macroscopic scales …

Hodgkin and Huxley's seminal neuron model describes the propagation of voltage spikes in
axons, but it cannot explain certain full-neuron features crucial for understanding the neural …

Neutron-deficient isotopes with Z= 21 to 26 have been produced as projectile-like fragments
of an intense 58 Ni GANIL beam of 69 MeV/nucleon. The nuclei selected by the upgraded …

We discuss the statistics of spikes trains for different types of integrate-and-fire neurons and
different types of synaptic noise models. In contrast with the usual approaches in …

We present simple solutions of first-passage and first-exit time problems for general moving
boundaries and general Itô processes in one dimension, including diffusion processes with …

We investigate the stochastic processes obtained as the fractional Riemann-Liouville
integral of order α∈(0, 1) of Gauss-Markov processes. The general expressions of the …

We find a representation of the integral of the stationary Ornstein–Uhlenbeck (ISOU) process
in terms of Brownian motion B t; moreover, we show that, under certain conditions on the …

We derive the mean-field equations arising as the limit of a network of interacting spiking
neurons, as the number of neurons goes to infinity. The neurons belong to a fixed number of …