Literature DB >> 10905807

The approach of a neuron population firing rate to a new equilibrium: an exact theoretical result.

B W Knight1, A Omurtag, L Sirovich.   

Abstract

The response of a noninteracting population of identical neurons to a step change in steady synaptic input can be analytically calculated exactly from the dynamical equation that describes the population's evolution in time. Here, for model integrate-and-fire neurons that undergo a fixed finite upward shift in voltage in response to each synaptic event, we compare the theoretical prediction with the result of a direct simulation of 90,000 model neurons. The degree of agreement supports the applicability of the population dynamics equation. The theoretical prediction is in the form of a series. Convergence is rapid, so that the full result is well approximated by a few terms.

Mesh:

Year:  2000        PMID: 10905807     DOI: 10.1162/089976600300015493

Source DB:  PubMed          Journal:  Neural Comput        ISSN: 0899-7667            Impact factor:   2.026


  17 in total

1.  How spike generation mechanisms determine the neuronal response to fluctuating inputs.

Authors:  Nicolas Fourcaud-Trocmé; David Hansel; Carl van Vreeswijk; Nicolas Brunel
Journal:  J Neurosci       Date:  2003-12-17       Impact factor: 6.167

2.  Population density models of integrate-and-fire neurons with jumps: well-posedness.

Authors:  Grégory Dumont; Jacques Henry
Journal:  J Math Biol       Date:  2012-06-20       Impact factor: 2.259

Review 3.  Emerging concepts for the dynamical organization of resting-state activity in the brain.

Authors:  Gustavo Deco; Viktor K Jirsa; Anthony R McIntosh
Journal:  Nat Rev Neurosci       Date:  2011-01       Impact factor: 34.870

4.  Action potential onset dynamics and the response speed of neuronal populations.

Authors:  B Naundorf; T Geisel; F Wolf
Journal:  J Comput Neurosci       Date:  2005-06       Impact factor: 1.621

5.  Stochastic models of neuronal dynamics.

Authors:  L M Harrison; O David; K J Friston
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2005-05-29       Impact factor: 6.237

6.  Factors affecting phase synchronization in integrate-and-fire oscillators.

Authors:  Todd W Troyer
Journal:  J Comput Neurosci       Date:  2006-04-22       Impact factor: 1.621

7.  Integral equation methods for computing likelihoods and their derivatives in the stochastic integrate-and-fire model.

Authors:  Liam Paninski; Adrian Haith; Gabor Szirtes
Journal:  J Comput Neurosci       Date:  2007-05-10       Impact factor: 1.621

8.  Dimensionally-reduced visual cortical network model predicts network response and connects system- and cellular-level descriptions.

Authors:  Louis Tao; Andrew T Sornborger
Journal:  J Comput Neurosci       Date:  2009-10-06       Impact factor: 1.621

9.  Improved dimensionally-reduced visual cortical network using stochastic noise modeling.

Authors:  Louis Tao; Jeremy Praissman; Andrew T Sornborger
Journal:  J Comput Neurosci       Date:  2011-08-27       Impact factor: 1.621

10.  Mechanisms explaining transitions between tonic and phasic firing in neuronal populations as predicted by a low dimensional firing rate model.

Authors:  Anca R Radulescu
Journal:  PLoS One       Date:  2010-09-22       Impact factor: 3.240

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