Citation Relationships



Brette R (2006) Exact simulation of integrate-and-fire models with synaptic conductances. Neural Comput 18:2004-27[PubMed]

References and models cited by this paper

References and models that cite this paper

Abbott LF, Nelson SB (2000) Synaptic plasticity: taming the beast. Nat Neurosci 3 Suppl:1178-83 [PubMed]

Brette R, Guigon E (2003) Reliability of spike timing is a general property of spiking model neurons. Neural Comput 15:279-308 [Journal] [PubMed]

   Reliability of spike timing is a general property of spiking model neurons (Brette & Guigon 2003) [Model]

Brown R (1988) Calendar queues: A fast 0(1) priority queue implementation for the simulation event set problem J Commun ACM 31:1220-1227

Brunel N (2000) Dynamics of sparsely connected networks of excitatory and inhibitory spiking neurons. J Comput Neurosci 8:183-208 [Journal] [PubMed]

   Sparsely connected networks of spiking neurons (Brunel 2000) [Model]

Cateau H, Fukai T (2003) A stochastic method to predict the consequence of arbitrary forms of spike-timing-dependent plasticity. Neural Comput 15:597-620 [PubMed]

Claverol E, Brown A, Chad J (2002) Discrete simulation of large aggregates of neurons Neurocomputing 47:277-297

Connolly C, Marian I, Reilly R (2003) Approaches to efficient simulation with spiking neural networks Paper presented at the Eighth Neural Computation and Psychology Workshop

Delorme A, Thorpe SJ (2003) SpikeNET: an event-driven simulation package for modelling large networks of spiking neurons. Network 14:613-27

Destexhe A, Mainen Z, Sejnowski TJ (1994) An efficient method for computing synaptic conductances based on a kinetic model of receptor binding Neural Comput 6:14-18 [Journal]

   Efficient Method for Computing Synaptic Conductance (Destexhe et al 1994) [Model]
   Kinetic synaptic models applicable to building networks (Destexhe et al 1998) [Model]
   Application of a common kinetic formalism for synaptic models (Destexhe et al 1994) [Model]

Destexhe A, Rudolph M, Fellous JM, Sejnowski TJ (2001) Fluctuating synaptic conductances recreate in vivo-like activity in neocortical neurons. Neuroscience 107:13-24 [PubMed]

   Fluctuating synaptic conductances recreate in-vivo-like activity (Destexhe et al 2001) [Model]

Ermentrout GB, Kopell N (1986) Parabolic bursting in an excitable system coupled with a slow oscillation. Siam J Appl Math 46:233-253

Fourcaud-Trocme N, Hansel D, van Vreeswijk C, Brunel N (2003) How spike generation mechanisms determine the neuronal response to fluctuating inputs. J Neurosci 23:11628-40 [PubMed]

Gerstner W, Kistler WM (2002) Spiking neuron models

Grassmann C, Anlauf J (1998) Distributed, event driven simulation of spiking neural networks Proceedings of the International ICSC-IFAC Symposium on Neural Computation :100-105

Hansel D, Mato G, Meunier C, Neltner L (1998) On numerical simulations of integrate-and-fire neural networks. Neural Comput 10:467-83 [PubMed]

Kempter R, Gerstner W, van Hemmen JL (2001) Intrinsic stabilization of output rates by spike-based Hebbian learning. Neural Comput 13:2709-41 [PubMed]

Knight BW (1972) Dynamics of encoding in a population of neurons. J Gen Physiol 59:734-66 [PubMed]

Lapicque L (1907) Recherches quantitatives sur lexcitation electrique des nerfs traitee comme une polarisation J Physiol Pathol Gen 9:620-635 [Journal]

Lee G, Farhat NH (2006) The double queue method: a numerical method for integrate-and-fire neuron networks. Neural Netw 14:921-32 [PubMed]

Liu YH, Wang XJ (2001) Spike-Frequency Adaptation of a Generalized Leaky Integrate-and-Fire Model Neuron J Comput Neurosci 10:25-45 [Journal]

Lytton WW (1996) Optimizing synaptic conductance calculation for network simulations. Neural Comput 8:501-9 [PubMed]

Lytton WW, Hines ML (2005) Independent variable time-step integration of individual neurons for network simulations. Neural Comput 17:903-21 [Journal] [PubMed]

   Local variable time step method (Lytton, Hines 2005) [Model]

Mainen ZF, Sejnowski TJ (1995) Reliability of spike timing in neocortical neurons. Science 268:1503-6 [PubMed]

Makino T (2003) A discrete-event neural network simulator for general neuron models Neural Comput App 11:210-223

Marian I, Reilly R, Mackey D (2002) Efficient event-driven simulation of spiking neural networks Proceedings of the 3rd WSEAS International Conference on Neural Networks and Applications

Mattia M, Del Giudice P (2000) Efficient event-driven simulation of large networks of spiking neurons and dynamical synapses. Neural Comput 12:2305-29 [PubMed]

Morrison A, Mehring C, Geisel T, Aertsen AD, Diesmann M (2005) Advancing the boundaries of high-connectivity network simulation with distributed computing. Neural Comput 17:1776-801 [PubMed]

Olshausen BA, Field DJ (2005) How close are we to understanding v1? Neural Comput 17:1665-99

Press WH, Teukolsky SA, Vellerling WT, Flannery BP (1992) Numerical Recipes In C: The Art Of Scientific Computing

Richardson MJ, Brunel N, Hakim V (2003) From subthreshold to firing-rate resonance. J Neurophysiol 89:2538-54 [Journal] [PubMed]

Rochel O, Martinez D (2003) An event-driven framework for the simulation of networks of spiking neurons Proc. 11th European Symposium on Artificial Neural Networks :295-300

Shelley MJ, Tao L (2001) Efficient and accurate time-stepping schemes for integrate-and-fire neuronal networks. J Comput Neurosci 11:111-9 [Journal] [PubMed]

Song S, Abbott LF (2001) Cortical development and remapping through spike timing-dependent plasticity. Neuron 32:339-50 [PubMed]

Song S, Miller KD, Abbott LF (2000) Competitive Hebbian learning through spike-timing-dependent synaptic plasticity. Nat Neurosci 3:919-26 [PubMed]

Stopfer M, Bhagavan S, Smith BH, Laurent G (1997) Impaired odour discrimination on desynchronization of odour-encoding neural assemblies. Nature 390:70-4 [PubMed]

Ziegler B, Praehofer H, Kim T (2000) Theory of modeling and simulation Integrating discrete event and continuous complex dynamic systems (2nd ed)

Alturki A, Feng F, Nair A, Guntu V, Nair SS (2016) Distinct current modules shape cellular dynamics in model neurons. Neuroscience 334:309-331 [Journal] [PubMed]

   Distinct current modules shape cellular dynamics in model neurons (Alturki et al 2016) [Model]

Gutig R, Sompolinsky H (2009) Time-warp-invariant neuronal processing. PLoS Biol 7:e1000141 [Journal] [PubMed]

   Time-warp-invariant neuronal processing (Gutig & Sompolinsky 2009) [Model]

Morrison A, Straube S, Plesser HE, Diesmann M (2007) Exact subthreshold integration with continuous spike times in discrete-time neural network simulations. Neural Comput 19:47-79 [PubMed]

Rangan AV, Cai D (2007) Fast numerical methods for simulating large-scale integrate-and-fire neuronal networks. J Comput Neurosci 22:81-100 [Journal] [PubMed]

Sterratt D, Graham B, Gillies A, Willshaw D (2011) Principles of Computational Modelling in Neuroscience, Cambridge University Press :1-401 [Journal]

   Principles of Computational Modelling in Neuroscience (Book) (Sterratt et al. 2011) [Model]

Stewart RD, Bair W (2009) Spiking neural network simulation: numerical integration with the Parker-Sochacki method. J Comput Neurosci [Journal] [PubMed]

   Numerical Integration of Izhikevich and HH model neurons (Stewart and Bair 2009) [Model]

Tonnelier A, Belmabrouk H, Martinez D (2007) Event-driven simulations of nonlinear integrate-and-fire neurons. Neural Comput 19:3226-38 [PubMed]

van Elburg RA, van Ooyen A (2009) Generalization of the Event-Based Carnevale-Hines Integration Scheme for Integrate-and-Fire Models. Neural Comput 21:1913-1930 [Journal] [PubMed]

   Generalized Carnevale-Hines algorithm (van Elburg and van Ooyen 2009) [Model]

(44 refs)