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Erschienen in: Journal of Computational Neuroscience 1/2019

13.08.2019

Electrodiffusion models of synaptic potentials in dendritic spines

verfasst von: Thibault Lagache, Krishna Jayant, Rafael Yuste

Erschienen in: Journal of Computational Neuroscience | Ausgabe 1/2019

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Abstract

The biophysical properties of dendritic spines play a critical role in neuronal integration but are still poorly understood, due to experimental difficulties in accessing them. Spine biophysics has been traditionally explored using theoretical models based on cable theory. However, cable theory generally assumes that concentration changes associated with ionic currents are negligible and, therefore, ignores electrodiffusion, i.e. the interaction between electric fields and ionic diffusion. This assumption, while true for large neuronal compartments, could be incorrect when applied to femto-liter size structures such as dendritic spines. To extend cable theory and explore electrodiffusion effects, we use here the Poisson (P) and Nernst-Planck (NP) equations, which relate electric field to charge and Fick’s law of diffusion, to model ion concentration dynamics in spines receiving excitatory synaptic potentials (EPSPs). We use experimentally measured voltage transients from spines with nanoelectrodes to explore these dynamics with realistic parameters. We find that (i) passive diffusion and electrodiffusion jointly affect the dynamics of spine EPSPs; (ii) spine geometry plays a key role in shaping EPSPs; and, (iii) the spine-neck resistance dynamically decreases during EPSPs, leading to short-term synaptic facilitation. Our formulation, which complements and extends cable theory, can be easily adapted to model ionic biophysics in other nanoscale bio-compartments.

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Metadaten
Titel
Electrodiffusion models of synaptic potentials in dendritic spines
verfasst von
Thibault Lagache
Krishna Jayant
Rafael Yuste
Publikationsdatum
13.08.2019
Verlag
Springer US
Erschienen in
Journal of Computational Neuroscience / Ausgabe 1/2019
Print ISSN: 0929-5313
Elektronische ISSN: 1573-6873
DOI
https://doi.org/10.1007/s10827-019-00725-5

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