Literature DB >> 14995506

Interspike interval statistics of neurons driven by colored noise.

Benjamin Lindner1.   

Abstract

A perfect integrate-and-fire model driven by colored noise is studied by means of the interspike interval (ISI) density and the serial correlation coefficient. Exact and approximate expressions for these functions are derived for weak dichotomous or Gaussian noise, respectively. It is shown that correlations in the input result in positive correlations in the ISI sequence and in a reduction of ISI variability. The results also indicate that for weak noise, the noise distribution only shapes the ISI density but not the ISI correlations which are determined by the noise's correlation function.

Mesh:

Year:  2004        PMID: 14995506     DOI: 10.1103/PhysRevE.69.022901

Source DB:  PubMed          Journal:  Phys Rev E Stat Nonlin Soft Matter Phys        ISSN: 1539-3755


  24 in total

1.  Integrate-and-fire neurons with threshold noise: a tractable model of how interspike interval correlations affect neuronal signal transmission.

Authors:  Benjamin Lindner; Maurice J Chacron; André Longtin
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2005-08-26

2.  Spike-frequency adaptation and intrinsic properties of an identified, looming-sensitive neuron.

Authors:  Fabrizio Gabbiani; Holger G Krapp
Journal:  J Neurophysiol       Date:  2006-03-29       Impact factor: 2.714

3.  Spontaneous dynamics and response properties of a Hodgkin-Huxley-type neuron model driven by harmonic synaptic noise.

Authors:  Hoai Nguyen; Alexander B Neiman
Journal:  Eur Phys J Spec Top       Date:  2010-09       Impact factor: 2.707

4.  Coherent stochastic oscillations enhance signal detection in spiking neurons.

Authors:  Tatiana A Engel; Brian Helbig; David F Russell; Lutz Schimansky-Geier; Alexander B Neiman
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2009-08-18

5.  Interspike interval correlation in a stochastic exponential integrate-and-fire model with subthreshold and spike-triggered adaptation.

Authors:  LieJune Shiau; Tilo Schwalger; Benjamin Lindner
Journal:  J Comput Neurosci       Date:  2015-04-19       Impact factor: 1.621

6.  Statistical structure of neural spiking under non-Poissonian or other non-white stimulation.

Authors:  Tilo Schwalger; Felix Droste; Benjamin Lindner
Journal:  J Comput Neurosci       Date:  2015-05-05       Impact factor: 1.621

7.  Channel noise from both slow adaptation currents and fast currents is required to explain spike-response variability in a sensory neuron.

Authors:  Karin Fisch; Tilo Schwalger; Benjamin Lindner; Andreas V M Herz; Jan Benda
Journal:  J Neurosci       Date:  2012-11-28       Impact factor: 6.167

8.  An integrate-and-fire model to generate spike trains with long-range dependence.

Authors:  Alexandre Richard; Patricio Orio; Etienne Tanré
Journal:  J Comput Neurosci       Date:  2018-03-24       Impact factor: 1.621

Review 9.  Reliability, synchrony and noise.

Authors:  G Bard Ermentrout; Roberto F Galán; Nathaniel N Urban
Journal:  Trends Neurosci       Date:  2008-07-05       Impact factor: 13.837

10.  Spike correlations - what can they tell about synchrony?

Authors:  Tatjana Tchumatchenko; Theo Geisel; Maxim Volgushev; Fred Wolf
Journal:  Front Neurosci       Date:  2011-05-11       Impact factor: 4.677

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