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arXiv · 0807.4057

Long-time behavior of stochastically perturbed neuronal networks

Stefano Bonaccorsi·Delio Mugnolo
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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.

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Stefano Bonaccorsi, Delio Mugnolo. 2008-07-25. Long-time behavior of stochastically perturbed neuronal networks. https://doi.org/10.1142/s0219493710003030

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