4.1 Article

Electrodiffusion models of synaptic potentials in dendritic spines

Journal

JOURNAL OF COMPUTATIONAL NEUROSCIENCE
Volume 47, Issue 1, Pages 77-89

Publisher

SPRINGER
DOI: 10.1007/s10827-019-00725-5

Keywords

Synaptic transmission; Dendritic spines; Electrodiffusion; Asymptotic analysis; Coarse-grained model; Electrophysiology; Simulations

Funding

  1. NIMH [R01MH101218, R01MH100561]
  2. NINDS [R01NS110422]
  3. U.S. Army Research Laboratory [W911NF-12-1-0594]
  4. U.S. Army Research Office [W911NF-12-1-0594]
  5. Fondation pour la Recherche Medicale
  6. Philippe foundation
  7. Kavli Institute of Brain Science at Columbia

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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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