Literature DB >> 17970651

Event-driven simulations of nonlinear integrate-and-fire neurons.

Arnaud Tonnelier1, Hana Belmabrouk, Dominique Martinez.   

Abstract

Event-driven strategies have been used to simulate spiking neural networks exactly. Previous work is limited to linear integrate-and-fire neurons. In this note, we extend event-driven schemes to a class of nonlinear integrate-and-fire models. Results are presented for the quadratic integrate-and-fire model with instantaneous or exponential synaptic currents. Extensions to conductance-based currents and exponential integrate-and-fire neurons are discussed.

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Year:  2007        PMID: 17970651     DOI: 10.1162/neco.2007.19.12.3226

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


  7 in total

1.  Voltage-stepping schemes for the simulation of spiking neural networks.

Authors:  G Zheng; A Tonnelier; D Martinez
Journal:  J Comput Neurosci       Date:  2008-11-26       Impact factor: 1.621

2.  A generalized linear integrate-and-fire neural model produces diverse spiking behaviors.

Authors:  Stefan Mihalaş; Ernst Niebur
Journal:  Neural Comput       Date:  2009-03       Impact factor: 2.026

3.  A Markovian event-based framework for stochastic spiking neural networks.

Authors:  Jonathan D Touboul; Olivier D Faugeras
Journal:  J Comput Neurosci       Date:  2011-04-16       Impact factor: 1.621

4.  Estimating parameters of generalized integrate-and-fire neurons from the maximum likelihood of spike trains.

Authors:  Yi Dong; Stefan Mihalas; Alexander Russell; Ralph Etienne-Cummings; Ernst Niebur
Journal:  Neural Comput       Date:  2011-08-18       Impact factor: 2.026

5.  FNS allows efficient event-driven spiking neural network simulations based on a neuron model supporting spike latency.

Authors:  Gianluca Susi; Pilar Garcés; Emanuele Paracone; Alessandro Cristini; Mario Salerno; Fernando Maestú; Ernesto Pereda
Journal:  Sci Rep       Date:  2021-06-09       Impact factor: 4.379

6.  Analytical insights on theta-gamma coupled neural oscillators.

Authors:  Lorenzo Fontolan; Maciej Krupa; Alexandre Hyafil; Boris Gutkin
Journal:  J Math Neurosci       Date:  2013-08-14       Impact factor: 1.300

7.  NEVESIM: event-driven neural simulation framework with a Python interface.

Authors:  Dejan Pecevski; David Kappel; Zeno Jonke
Journal:  Front Neuroinform       Date:  2014-08-14       Impact factor: 4.081

  7 in total

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