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An Hodgkin-Huxley neuron receiving a random periodic signal : ergodicity and estimation

By Michèle Thieullen

Appears in collection : LEM2I international conference / Colloque international du LEM2I

In this talk I will present a stochastic model for the excitability of a neuron in a network. The neuron described by an Hodgkin-Huxley type model receives from the network a random input which is a perturbation of a periodic deterministic signal. For such a model we study ergodicity properties. Then, we prove limit theorems in order to be able to estimate characteristics of the sequence of spiking times. This talk is based on a joint work with R. Hoepfner (Univ. Mainz) and E. Loecherbach (Univ. Cergy-Pontoise).

Hodgkin-Huxley model - ergodicity - limit theorems - estimation

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Citation data

  • DOI 10.24350/CIRM.V.18653803
  • Cite this video Thieullen, Michèle (11/12/2014). An Hodgkin-Huxley neuron receiving a random periodic signal : ergodicity and estimation. CIRM. Audiovisual resource. DOI: 10.24350/CIRM.V.18653803
  • URL https://dx.doi.org/10.24350/CIRM.V.18653803

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Bibliography

  • Höpfner, R. Löcherbach, E., & Thieullen, M. (2013). Transition densities for strongly degenerate time inhomogeneous random models. <arXiv:1310.7373v1> - http://arxiv.org/abs/1310.7373
  • Höpfner, R. Löcherbach, E. and Thieullen, M. (2013). Ergodicity for a stochastic Hodgkin-Huxley model driven by Ornstein-Uhlenbeck type input. <arXiv:1311.3458v3> - http://arxiv.org/abs/1311.3458
  • Höpfner, R. Löcherbach, E. and Thieullen, M. (2012). Transition densities for stochastic Hodgkin-Huxley models. <arXiv:1207.0195v1> - http://arxiv.org/abs/1207.0195

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