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Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons: a review. (Revue des méthodes d’estimation paramétrique pour des modèles neuronaux sous forme d’équations différentielles stochastiques à partir de données neuronales intra-cellulaires.) (English. French summary) Zbl 1357.92010

Summary: Dynamics of the membrane potential in a single neuron can be studied by estimating biophysical parameters from intracellular recordings. Diffusion processes, given as continuous solutions to stochastic differential equations, are widely applied as models for the neuronal membrane potential evolution. One-dimensional models are the stochastic integrate-and-fire neuronal diffusion models. Biophysical neuronal models take into account the dynamics of ion channels or synaptic activity, leading to multidimensional diffusion models. Since only the membrane potential can be measured, this complicates the statistical inference and parameter estimation from these partially observed detailed models. This paper reviews parameter estimation techniques from intracellular recordings in these diffusion models.

MSC:

92C20 Neural biology
60J70 Applications of Brownian motions and diffusion theory (population genetics, absorption problems, etc.)
92B15 General biostatistics
62P10 Applications of statistics to biology and medical sciences; meta analysis