142 related articles for article (PubMed ID: 22364504)
1. Analytical integrate-and-fire neuron models with conductance-based dynamics and realistic postsynaptic potential time course for event-driven simulation strategies.
Rudolph-Lilith M; Dubois M; Destexhe A
Neural Comput; 2012 Jun; 24(6):1426-61. PubMed ID: 22364504
[TBL] [Abstract][Full Text] [Related]
2. Analytical integrate-and-fire neuron models with conductance-based dynamics for event-driven simulation strategies.
Rudolph M; Destexhe A
Neural Comput; 2006 Sep; 18(9):2146-210. PubMed ID: 16846390
[TBL] [Abstract][Full Text] [Related]
3. Exact simulation of integrate-and-fire models with synaptic conductances.
Brette R
Neural Comput; 2006 Aug; 18(8):2004-27. PubMed ID: 16771661
[TBL] [Abstract][Full Text] [Related]
4. Predicting spike times of a detailed conductance-based neuron model driven by stochastic spike arrival.
Jolivet R; Gerstner W
J Physiol Paris; 2004; 98(4-6):442-51. PubMed ID: 16274972
[TBL] [Abstract][Full Text] [Related]
5. A review of the integrate-and-fire neuron model: I. Homogeneous synaptic input.
Burkitt AN
Biol Cybern; 2006 Jul; 95(1):1-19. PubMed ID: 16622699
[TBL] [Abstract][Full Text] [Related]
6. Including long-range dependence in integrate-and-fire models of the high interspike-interval variability of cortical neurons.
Jackson BS
Neural Comput; 2004 Oct; 16(10):2125-95. PubMed ID: 15333210
[TBL] [Abstract][Full Text] [Related]
7. Event-driven simulations of nonlinear integrate-and-fire neurons.
Tonnelier A; Belmabrouk H; Martinez D
Neural Comput; 2007 Dec; 19(12):3226-38. PubMed ID: 17970651
[TBL] [Abstract][Full Text] [Related]
8. Accelerating event-driven simulation of spiking neurons with multiple synaptic time constants.
D'Haene M; Schrauwen B; Van Campenhout J; Stroobandt D
Neural Comput; 2009 Apr; 21(4):1068-99. PubMed ID: 18928367
[TBL] [Abstract][Full Text] [Related]
9. Calculating event-triggered average synaptic conductances from the membrane potential.
Pospischil M; Piwkowska Z; Rudolph M; Bal T; Destexhe A
J Neurophysiol; 2007 Mar; 97(3):2544-52. PubMed ID: 17151222
[TBL] [Abstract][Full Text] [Related]
10. Response of integrate-and-fire neurons to noisy inputs filtered by synapses with arbitrary timescales: firing rate and correlations.
Moreno-Bote R; Parga N
Neural Comput; 2010 Jun; 22(6):1528-72. PubMed ID: 20100073
[TBL] [Abstract][Full Text] [Related]
11. A review of the integrate-and-fire neuron model: II. Inhomogeneous synaptic input and network properties.
Burkitt AN
Biol Cybern; 2006 Aug; 95(2):97-112. PubMed ID: 16821035
[TBL] [Abstract][Full Text] [Related]
12. Critical analysis of dimension reduction by a moment closure method in a population density approach to neural network modeling.
Ly C; Tranchina D
Neural Comput; 2007 Aug; 19(8):2032-92. PubMed ID: 17571938
[TBL] [Abstract][Full Text] [Related]
13. On the performance of voltage stepping for the simulation of adaptive, nonlinear integrate-and-fire neuronal networks.
Kaabi MG; Tonnelier A; Martinez D
Neural Comput; 2011 May; 23(5):1187-204. PubMed ID: 21299420
[TBL] [Abstract][Full Text] [Related]
14. Firing frequency of leaky intergrate-and-fire neurons with synaptic current dynamics.
Brunel N; Sergi S
J Theor Biol; 1998 Nov; 195(1):87-95. PubMed ID: 9802952
[TBL] [Abstract][Full Text] [Related]
15. Theory of input spike auto- and cross-correlations and their effect on the response of spiking neurons.
Moreno-Bote R; Renart A; Parga N
Neural Comput; 2008 Jul; 20(7):1651-705. PubMed ID: 18254697
[TBL] [Abstract][Full Text] [Related]
16. Dynamics of deterministic and stochastic paired excitatory-inhibitory delayed feedback.
Laing CR; Longtin A
Neural Comput; 2003 Dec; 15(12):2779-822. PubMed ID: 14629868
[TBL] [Abstract][Full Text] [Related]
17. Exact simulation of integrate-and-fire models with exponential currents.
Brette R
Neural Comput; 2007 Oct; 19(10):2604-9. PubMed ID: 17716004
[TBL] [Abstract][Full Text] [Related]
18. Spike train statistics and dynamics with synaptic input from any renewal process: a population density approach.
Ly C; Tranchina D
Neural Comput; 2009 Feb; 21(2):360-96. PubMed ID: 19431264
[TBL] [Abstract][Full Text] [Related]
19. Generalization of the event-based Carnevale-Hines integration scheme for integrate-and-fire models.
van Elburg RA; van Ooyen A
Neural Comput; 2009 Jul; 21(7):1913-30. PubMed ID: 19292645
[TBL] [Abstract][Full Text] [Related]
20. Firing rate of the noisy quadratic integrate-and-fire neuron.
Brunel N; Latham PE
Neural Comput; 2003 Oct; 15(10):2281-306. PubMed ID: 14511522
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]