Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons Ditlevsen, Susanne; Samson, Adeline

نویسندگان

  • Susanne Ditlevsen
  • Adeline Samson
چکیده

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. Résumé : On peut étudier la dynamique du potentiel de la membrane d’un neurone en estimant des paramètres biophysiques à partir d’enregistrement intracellulaire. Les processus de diffusion, définis comme solution à temps continu d’équations différentielles stochastiques ont été très utilisés pour modéliser l’évolution du potentiel membranaire. Parmi les processus de dimension un, les plus connus sont les modèles de diffusion intègre-et-tire. D’autres modèles neuronaux sont plus biophysiques et prennent en compte la dynamique des canaux ioniques ou de l’activité synaptique. Ce sont des processus de diffusion multidimensionnels. L’estimation des paramètres de ces modèles est difficile car seulement le potentiel membranaire peut être mesuré. Ce papier résume les techniques d’estimation qui ont été proposées pour ces modèles de diffusion de données intracellulaires. Mots-clés : modèles de diffusion intègre-et-tire, modèles de conductances, modèles à espace d’Ã́©tats, estimation synaptique, maximum de vraisemblance, filtre particulaire, fonctions estimantes, MCMC, observations partielles

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Estimation in the partially observed stochastic Morris-Lecar neuronal model with particle filter and stochastic approximation methods

Parameter estimation in multidimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult problem. In neuroscience, the membrane potential evolution in single neurons can be measured at high frequency, but biophysical realistic models have to include the unobserved dynamics of ion channels. One such model is the...

متن کامل

Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons: a Review

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. Biophys...

متن کامل

Parameter estimation in neuronal stochastic differential equation models from intracellular recordings of membrane potentials in single neurons: a Review Titre: Revue des méthodes d’estimation paramétrique pour des modèles neuronaux sous forme d’équations différentielles stochastiques à partir de données neuronales intra-cellulaires

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. Biophys...

متن کامل

Parameter estimation in the stochastic Morris-Lecar neuronal model with particle filter methods

Parameter estimation in two-dimensional diffusion models with only one coordinate observed is highly relevant in many biological applications, but a statistically difficult problem. In neuroscience, the membrane potential evolution in single neurons can be measured at high frequency, but biophysical realistic models have to include the unobserved dynamics of ion channels. One such model is the ...

متن کامل

Hypoelliptic diffusions: discretization, filtering and inference from complete and partial observations

The statistical problem of parameter estimation in partially observed hypoelliptic diffusion processes is naturally occurring in many applications. However, due to the noise structure, where the noise components of the different coordinates of the multidimensional process operate on different time scales, standard inference tools are ill conditioned. In this paper, we propose to use a higher or...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017