English

Long-time behavior of stochastically perturbed neuronal networks

Probability 2018-12-21 v1 Functional Analysis

Abstract

Our investigation is specially motivated by the stochastic version of a common model of potential spread in a dendritic tree. We do not assume the noise in the junction points to be Markovian. In fact, we allow for long-range dependence in time of the stochastic perturbation. This leads to an abstract formulation in terms of a stochastic diffusion with dynamic boundary conditions, featuring fractional Brownian motion. We prove results on existence, uniqueness and asymptotics of weak and strong solutions to such a stochastic differential equation.

Keywords

Cite

@article{arxiv.0807.4057,
  title  = {Long-time behavior of stochastically perturbed neuronal networks},
  author = {Stefano Bonaccorsi and Delio Mugnolo},
  journal= {arXiv preprint arXiv:0807.4057},
  year   = {2018}
}