Literature DB >> 14685771

Dynamics of one-dimensional spiking neuron models.

Romain Brette1.   

Abstract

In this paper we make a rigorous mathematical analysis of one-dimensional spiking neuron models in a unified framework. We find that, under conditions satisfied in particular by the periodically and aperiodically driven leaky integrator as well as some of its variants, the spike map is increasing on its range, which leaves no room for chaotic behavior. A rigorous expression of the Lyapunov exponent is derived. Finally, we analyse the periodically driven perfect integrator and show that the restriction of the phase map to its range is always conjugated to a rotation, and we provide an explicit expression of the invariant measure.

Mesh:

Year:  2003        PMID: 14685771     DOI: 10.1007/s00285-003-0223-9

Source DB:  PubMed          Journal:  J Math Biol        ISSN: 0303-6812            Impact factor:   2.259


  16 in total

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Authors:  P E Latham; B J Richmond; P G Nelson; S Nirenberg
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2.  Precision and reliability of periodically and quasiperiodically driven integrate-and-fire neurons.

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5.  The effect of dynamic synapses on spatiotemporal receptive fields in visual cortex.

Authors:  O B Artun; H Z Shouval; L N Cooper
Journal:  Proc Natl Acad Sci U S A       Date:  1998-09-29       Impact factor: 11.205

6.  Physiological gain leads to high ISI variability in a simple model of a cortical regular spiking cell.

Authors:  T W Troyer; K D Miller
Journal:  Neural Comput       Date:  1997-07-01       Impact factor: 2.026

7.  Phase-locked responses in the Limulus lateral eye. Theoretical and experimental investigation.

Authors:  C Ascoli; M Barbi; S Chillemi; D Petracchi
Journal:  Biophys J       Date:  1977-09       Impact factor: 4.033

8.  A neuronal model for the discharge patterns produced by cyclic inputs.

Authors:  A Rescigno; R B Stein; R L Purple; R E Poppele
Journal:  Bull Math Biophys       Date:  1970-09

9.  Phase locking to high frequencies in the auditory nerve and cochlear nucleus magnocellularis of the barn owl, Tyto alba.

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Journal:  J Neurosci       Date:  1997-05-01       Impact factor: 6.167

10.  Dynamics of encoding in a population of neurons.

Authors:  B W Knight
Journal:  J Gen Physiol       Date:  1972-06       Impact factor: 4.086

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  8 in total

1.  The Cauchy problem for one-dimensional spiking neuron models.

Authors:  Romain Brette
Journal:  Cogn Neurodyn       Date:  2007-11-15       Impact factor: 5.082

2.  Mode-locked spike trains in responses of ventral cochlear nucleus chopper and onset neurons to periodic stimuli.

Authors:  Jonathan Laudanski; Stephen Coombes; Alan R Palmer; Christian J Sumner
Journal:  J Neurophysiol       Date:  2009-12-30       Impact factor: 2.714

3.  Spectrum of Lyapunov exponents of non-smooth dynamical systems of integrate-and-fire type.

Authors:  Douglas Zhou; Yi Sun; Aaditya V Rangan; David Cai
Journal:  J Comput Neurosci       Date:  2009-12-09       Impact factor: 1.621

4.  Automatic fitting of spiking neuron models to electrophysiological recordings.

Authors:  Cyrille Rossant; Dan F M Goodman; Jonathan Platkiewicz; Romain Brette
Journal:  Front Neuroinform       Date:  2010-03-05       Impact factor: 4.081

5.  Fitting neuron models to spike trains.

Authors:  Cyrille Rossant; Dan F M Goodman; Bertrand Fontaine; Jonathan Platkiewicz; Anna K Magnusson; Romain Brette
Journal:  Front Neurosci       Date:  2011-02-23       Impact factor: 4.677

6.  Computing with neural synchrony.

Authors:  Romain Brette
Journal:  PLoS Comput Biol       Date:  2012-06-14       Impact factor: 4.475

7.  Spiking models for level-invariant encoding.

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Journal:  Front Comput Neurosci       Date:  2012-01-10       Impact factor: 2.380

8.  The Dynamics of Balanced Spiking Neuronal Networks Under Poisson Drive Is Not Chaotic.

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Journal:  Front Comput Neurosci       Date:  2018-06-28       Impact factor: 2.380

  8 in total

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