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Items: 1 to 20 of 274

1.

Self-organizing dual coding based on spike-time-dependent plasticity.

Masuda N, Aihara K.

Neural Comput. 2004 Mar;16(3):627-63.

PMID:
15006094
2.
3.

Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner.

Liu JK, Buonomano DV.

J Neurosci. 2009 Oct 21;29(42):13172-81. doi: 10.1523/JNEUROSCI.2358-09.2009.

4.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. II. Input selectivity--symmetry breaking.

Gilson M, Burkitt AN, Grayden DB, Thomas DA, van Hemmen JL.

Biol Cybern. 2009 Aug;101(2):103-14. doi: 10.1007/s00422-009-0320-y. Epub 2009 Jun 18.

PMID:
19536559
5.
6.

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.

7.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks. I. Input selectivity--strengthening correlated input pathways.

Gilson M, Burkitt AN, Grayden DB, Thomas DA, van Hemmen JL.

Biol Cybern. 2009 Aug;101(2):81-102. doi: 10.1007/s00422-009-0319-4. Epub 2009 Jun 18.

PMID:
19536560
8.

Self-tuning of neural circuits through short-term synaptic plasticity.

Sussillo D, Toyoizumi T, Maass W.

J Neurophysiol. 2007 Jun;97(6):4079-95. Epub 2007 Apr 4.

9.

Inhibitory synaptic plasticity regulates pyramidal neuron spiking in the rodent hippocampus.

Saraga F, Balena T, Wolansky T, Dickson CT, Woodin MA.

Neuroscience. 2008 Jul 31;155(1):64-75. doi: 10.1016/j.neuroscience.2008.05.009. Epub 2008 May 21.

PMID:
18562122
10.

Broadband coding with dynamic synapses.

Lindner B, Gangloff D, Longtin A, Lewis JE.

J Neurosci. 2009 Feb 18;29(7):2076-88. doi: 10.1523/JNEUROSCI.3702-08.2009.

11.

STDP provides the substrate for igniting synfire chains by spatiotemporal input patterns.

Hosaka R, Araki O, Ikeguchi T.

Neural Comput. 2008 Feb;20(2):415-35.

PMID:
18045011
12.

Learning input correlations through nonlinear temporally asymmetric Hebbian plasticity.

Gütig R, Aharonov R, Rotter S, Sompolinsky H.

J Neurosci. 2003 May 1;23(9):3697-714.

13.

Emergence of network structure due to spike-timing-dependent plasticity in recurrent neuronal networks IV: structuring synaptic pathways among recurrent connections.

Gilson M, Burkitt AN, Grayden DB, Thomas DA, van Hemmen JL.

Biol Cybern. 2009 Dec;101(5-6):427-44. doi: 10.1007/s00422-009-0346-1. Epub 2009 Nov 24.

PMID:
19937070
14.

What can a neuron learn with spike-timing-dependent plasticity?

Legenstein R, Naeger C, Maass W.

Neural Comput. 2005 Nov;17(11):2337-82.

PMID:
16156932
15.
16.

Optimality model of unsupervised spike-timing-dependent plasticity: synaptic memory and weight distribution.

Toyoizumi T, Pfister JP, Aihara K, Gerstner W.

Neural Comput. 2007 Mar;19(3):639-71.

PMID:
17298228
17.

Analog-digital simulations of full conductance-based networks of spiking neurons with spike timing dependent plasticity.

Zou Q, Bornat Y, Saïghi S, Tomas J, Renaud S, Destexhe A.

Network. 2006 Sep;17(3):211-33.

PMID:
17162612
18.

Adaptive synchronization of activities in a recurrent network.

Voegtlin T.

Neural Comput. 2009 Jun;21(6):1749-75. doi: 10.1162/neco.2009.02-08-708.

PMID:
19191597
19.

Neurons tune to the earliest spikes through STDP.

Guyonneau R, VanRullen R, Thorpe SJ.

Neural Comput. 2005 Apr;17(4):859-79.

PMID:
15829092
20.

Reinforcement learning, spike-time-dependent plasticity, and the BCM rule.

Baras D, Meir R.

Neural Comput. 2007 Aug;19(8):2245-79.

PMID:
17571943

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