Analytical approach to an integrate-and-fire model with spike-triggered adaptation

Tilo Schwalger and Benjamin Lindner
Phys. Rev. E 92, 062703 – Published 7 December 2015

Abstract

The calculation of the steady-state probability density for multidimensional stochastic systems that do not obey detailed balance is a difficult problem. Here we present the analytical derivation of the stationary joint and various marginal probability densities for a stochastic neuron model with adaptation current. Our approach assumes weak noise but is valid for arbitrary adaptation strength and time scale. The theory predicts several effects of adaptation on the statistics of the membrane potential of a tonically firing neuron: (i) a membrane potential distribution with a convex shape, (ii) a strongly increased probability of hyperpolarized membrane potentials induced by strong and fast adaptation, and (iii) a maximized variability associated with the adaptation current at a finite adaptation time scale.

  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
  • Figure
4 More
  • Received 31 May 2015

DOI:https://doi.org/10.1103/PhysRevE.92.062703

©2015 American Physical Society

Authors & Affiliations

Tilo Schwalger1,2,* and Benjamin Lindner2,3

  • 1Brain Mind Institute, École Polytechnique Féderale de Lausanne (EPFL) Station 15, CH-1015 Lausanne, Switzerland
  • 2Bernstein Center for Computational Neuroscience, Haus 2, Philippstraße 13, 10115 Berlin, Germany
  • 3Department of Physics, Humboldt Universität zu Berlin, Newtonstraße 15, 12489 Berlin, Germany

  • *tilo.schwalger@epfl.ch

Article Text (Subscription Required)

Click to Expand

References (Subscription Required)

Click to Expand
Issue

Vol. 92, Iss. 6 — December 2015

Reuse & Permissions
Access Options
Author publication services for translation and copyediting assistance advertisement

Authorization Required


×
×

Images

×

Sign up to receive regular email alerts from Physical Review E

Log In

Cancel
×

Search


Article Lookup

Paste a citation or DOI

Enter a citation
×