Neural Comp. Sign up for ETOCS
HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
 QUICK SEARCH:   [advanced]


     


This Article
Right arrow Full Text
Right arrow Full Text (PDF)
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Similar articles in this journal
Right arrow Similar articles in PubMed
Right arrow Alert me to new issues of the journal
Right arrow Download to citation manager
Right arrow reprints & permissions
Citing Articles
Right arrow Citing Articles via HighWire
Right arrow Citing Articles via Google Scholar
Google Scholar
Right arrow Articles by Rudolph, M.
Right arrow Articles by Destexhe, A.
Right arrow Search for Related Content
PubMed
Right arrow PubMed Citation
Right arrow Articles by Rudolph, M.
Right arrow Articles by Destexhe, A.
(Neural Computation. 2005;17:2301-2315.)
© 2005 The MIT Press


Note

An Extended Analytic Expression for the Membrane Potential Distribution of Conductance-Based Synaptic Noise

M. Rudolph

Michael.Rudolph{at}iaf.cnrs-gif.fr, Unité de Neuroscience Intégratives et Computationnelles, CNRS, 91198 Gif-sur-Yvette, France

A. Destexhe

Alain.Destexhe{at}iaf.cnrs-gif.fr, Unité de Neuroscience Intégratives et Computationnelles, CNRS, 91198 Gif-sur-Yvette, France

Synaptically generated subthreshold membrane potential (Vm) fluctuations can be characterized within the framework of stochastic calculus. It is possible to obtain analytic expressions for the steady-state Vm distribution, even in the case of conductance-based synaptic currents. However, as we show here, the analytic expressions obtained may substantially deviate from numerical solutions if the stochastic membrane equations are solved exclusively based on expectation values of differentials of the stochastic variables, hence neglecting the spectral properties of the underlying stochastic processes. We suggest a simple solution that corrects these deviations, leading to extended analytic expressions of the Vm distribution valid for a parameter regime that covers several orders of magnitude around physiologically realistic values. These extended expressions should enable finer characterization of the stochasticity of synaptic currents by analyzing experimentally recorded Vm distributions and may be applicable to other classes of stochastic processes as well.




This article has been cited by other articles:


Home page
Neural Comput.Home page
E. Muller, L. Buesing, J. Schemmel, and K. Meier
Spike-Frequency Adapting Neural Ensembles: Beyond Mean Adaptation and Renewal Theories
Neural Comput., November 1, 2007; 19(11): 2958 - 3010.
[Abstract] [Full Text] [PDF]


Home page
J. Neurosci.Home page
M. Rudolph, M. Pospischil, I. Timofeev, and A. Destexhe
Inhibition Determines Membrane Potential Dynamics and Controls Action Potential Generation in Awake and Sleeping Cat Cortex
J. Neurosci., May 16, 2007; 27(20): 5280 - 5290.
[Abstract] [Full Text] [PDF]


Home page
Neural Comput.Home page
M. Rudolph and A. Destexhe
On the use of analytical expressions for the voltage distribution to analyze intracellular recordings.
Neural Comput., December 1, 2006; 18(12): 2917 - 2922.
[Abstract] [Full Text] [PDF]


Home page
Neural Comput.Home page
B. Lindner and A. Longtin
Comment on "Characterization of Subthreshold Voltage Fluctuations in Neuronal Membranes," by M. Rudolph and A. Destexhe
Neural Comput., August 1, 2006; 18(8): 1896 - 1931.
[Abstract] [Full Text] [PDF]




HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS
J COGNITIVE NEUROSCIENCE NEURAL COMPUTATION MIT PRESS JOURNALS
Copyright © 2005 by The MIT Press.