Mathematical models are an important tool for neuroscientists. During the last 30 years
many papers have appeared on single neuron description and specifically on stochastic …

Variability in single neuron models is typically implemented either by a stochastic Leaky-
Integrate-and-Fire model or by a model of the Generalized Linear Model (GLM) family. We …

Recently, a class of two-dimensional integrate and fire models has been used to faithfully
model spiking neurons. This class includes the Izhikevich model, the adaptive exponential …

In this paper, we study the influence of the coupling strength on the synchronization
behavior of a population of leaky integrate-and-fire neurons that is self-excitatory with a …

Five parameters of one of the most common neuronal models, the diffusion leaky integrate-
and-fire model, also known as the Ornstein-Uhlenbeck neuronal model, were estimated on …

The integrate-and-fire neuron model is one of the most widely used models for analyzing the
behavior of neural systems. It describes the membrane potential of a neuron in terms of the …

Stochastic biomathematical models are becoming increasingly important as new light is
shed on the role of noise in living systems. In certain biological systems, stochastic effects …

Most biological neurons communicate by short electrical pulses, called action potentials or
spikes. In contrast to the standard neuron model used in artificial neural networks, integrate …

Providing an analytical treatment to the stochastic feature of neurons' dynamics is one of the
current biggest challenges in mathematical biology. The noisy leaky integrate-and-fire …

Artificial Neural Networks, or more simply neural networks, are the main objects of a new
science, named neural computing (or neurocomputing), which aims to define a paradigm of …