On the return process with refractoriness for a non-homogeneous Ornstein-Uhlenbeck neuronal model

  • Received: 01 October 2012 Accepted: 29 June 2018 Published: 01 October 2013
  • MSC : Primary: 60J60, 92C20; Secondary: 60J75.

  • An Ornstein-Uhlenbeck diffusion process is considered as a model for the membrane potential activity of a single neuron. We assume that the neuron is subject to a sequence of inhibitory and excitatory post-synaptic potentials that occur with time-dependent rates. The resulting process is characterized by time-dependent drift. For this model, we construct the return process describing the membrane potential.It is a non homogeneous Ornstein-Uhlenbeck process with jumps on which the effect of random refractoriness is introduced. An asymptotic analysis of the process modeling the number of firings and the distribution of interspike intervals is performed under the assumption of exponential distribution for the firing time.Some numerical evaluations are performed to provide quantitative information on the role of the parameters.

    Citation: Virginia Giorno, Serena Spina. On the return process with refractoriness for a non-homogeneous Ornstein-Uhlenbeck neuronal model[J]. Mathematical Biosciences and Engineering, 2014, 11(2): 285-302. doi: 10.3934/mbe.2014.11.285

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  • An Ornstein-Uhlenbeck diffusion process is considered as a model for the membrane potential activity of a single neuron. We assume that the neuron is subject to a sequence of inhibitory and excitatory post-synaptic potentials that occur with time-dependent rates. The resulting process is characterized by time-dependent drift. For this model, we construct the return process describing the membrane potential.It is a non homogeneous Ornstein-Uhlenbeck process with jumps on which the effect of random refractoriness is introduced. An asymptotic analysis of the process modeling the number of firings and the distribution of interspike intervals is performed under the assumption of exponential distribution for the firing time.Some numerical evaluations are performed to provide quantitative information on the role of the parameters.


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