509 related articles for article (PubMed ID: 18386986)
1. Encoding and decoding spikes for dynamic stimuli.
Natarajan R; Huys QJ; Dayan P; Zemel RS
Neural Comput; 2008 Sep; 20(9):2325-60. PubMed ID: 18386986
[TBL] [Abstract][Full Text] [Related]
2. Fast population coding.
Huys QJ; Zemel RS; Natarajan R; Dayan P
Neural Comput; 2007 Feb; 19(2):404-41. PubMed ID: 17206870
[TBL] [Abstract][Full Text] [Related]
3. Decoding a temporal population code.
Knüsel P; Wyss R; König P; Verschure PF
Neural Comput; 2004 Oct; 16(10):2079-100. PubMed ID: 15333208
[TBL] [Abstract][Full Text] [Related]
4. Bayesian spiking neurons II: learning.
Deneve S
Neural Comput; 2008 Jan; 20(1):118-45. PubMed ID: 18045003
[TBL] [Abstract][Full Text] [Related]
5. Overview of facts and issues about neural coding by spikes.
Cessac B; Paugam-Moisy H; Viéville T
J Physiol Paris; 2010; 104(1-2):5-18. PubMed ID: 19925865
[TBL] [Abstract][Full Text] [Related]
6. Dual information representation with stable firing rates and chaotic spatiotemporal spike patterns in a neural network model.
Araki O; Aihara K
Neural Comput; 2001 Dec; 13(12):2799-822. PubMed ID: 11705411
[TBL] [Abstract][Full Text] [Related]
7. Spiking neural networks for cortical neuronal spike train decoding.
Fang H; Wang Y; He J
Neural Comput; 2010 Apr; 22(4):1060-85. PubMed ID: 19922291
[TBL] [Abstract][Full Text] [Related]
8. Event-driven simulation scheme for spiking neural networks using lookup tables to characterize neuronal dynamics.
Ros E; Carrillo R; Ortigosa EM; Barbour B; Agís R
Neural Comput; 2006 Dec; 18(12):2959-93. PubMed ID: 17052155
[TBL] [Abstract][Full Text] [Related]
9. Deterministic neural dynamics transmitted through neural networks.
Asai Y; Guha A; Villa AE
Neural Netw; 2008 Aug; 21(6):799-809. PubMed ID: 18675536
[TBL] [Abstract][Full Text] [Related]
10. Spatial and temporal pattern analysis via spiking neurons.
Natschläger T; Ruf B
Network; 1998 Aug; 9(3):319-32. PubMed ID: 9861993
[TBL] [Abstract][Full Text] [Related]
11. Computing with continuous attractors: stability and online aspects.
Wu S; Amari S
Neural Comput; 2005 Oct; 17(10):2215-39. PubMed ID: 16105223
[TBL] [Abstract][Full Text] [Related]
12. Computational properties of networks of synchronous groups of spiking neurons.
Dayhoff JE
Neural Comput; 2007 Sep; 19(9):2433-67. PubMed ID: 17650065
[TBL] [Abstract][Full Text] [Related]
13. An extended model for a spiking neuron class.
Guerreiro AM; Paz de Araujo CA
Biol Cybern; 2007 Sep; 97(3):211-9. PubMed ID: 17647011
[TBL] [Abstract][Full Text] [Related]
14. Learning real-world stimuli in a neural network with spike-driven synaptic dynamics.
Brader JM; Senn W; Fusi S
Neural Comput; 2007 Nov; 19(11):2881-912. PubMed ID: 17883345
[TBL] [Abstract][Full Text] [Related]
15. On the maximization of information flow between spiking neurons.
Parra LC; Beck JM; Bell AJ
Neural Comput; 2009 Nov; 21(11):2991-3009. PubMed ID: 19635018
[TBL] [Abstract][Full Text] [Related]
16. Efficient computation based on stochastic spikes.
Ernst U; Rotermund D; Pawelzik K
Neural Comput; 2007 May; 19(5):1313-43. PubMed ID: 17381268
[TBL] [Abstract][Full Text] [Related]
17. Selective population rate coding: a possible computational role of gamma oscillations in selective attention.
Masuda N
Neural Comput; 2009 Dec; 21(12):3335-62. PubMed ID: 19686062
[TBL] [Abstract][Full Text] [Related]
18. Computation with spikes in a winner-take-all network.
Oster M; Douglas R; Liu SC
Neural Comput; 2009 Sep; 21(9):2437-65. PubMed ID: 19548795
[TBL] [Abstract][Full Text] [Related]
19. A learning rule for the emergence of stable dynamics and timing in recurrent networks.
Buonomano DV
J Neurophysiol; 2005 Oct; 94(4):2275-83. PubMed ID: 16160088
[TBL] [Abstract][Full Text] [Related]
20. Oscillations and spiking pairs: behavior of a neuronal model with STDP learning.
Shen X; Lin X; De Wilde P
Neural Comput; 2008 Aug; 20(8):2037-69. PubMed ID: 18336082
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
