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Items: 1 to 20 of 76

1.

[Neurodarvinism: models of selection of neuronal groups].

[No authors listed]

Zh Vyssh Nerv Deiat Im I P Pavlova. 2005 Jul-Aug;55(4):459-71. Review. Russian.

PMID:
16217959
2.

Selection versus instruction: use of computer models to compare brain theories.

Reeke GN Jr.

Int Rev Neurobiol. 1994;37:211-42; discussion 285-8. Review. No abstract available.

PMID:
7883479
3.

An extended model for a spiking neuron class.

Guerreiro AM, Paz de Araujo CA.

Biol Cybern. 2007 Sep;97(3):211-9. Epub 2007 Jul 24.

PMID:
17647011
4.

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. doi: 10.1162/neco.2008.08-06-317.

PMID:
18336082
5.

Natural selection in relation to complexity.

Salthe SN.

Artif Life. 2008 Summer;14(3):363-74. doi: 10.1162/artl.2008.14.3.14309.

PMID:
18631102
6.

Programmable logic construction kits for hyper-real-time neuronal modeling.

Guerrero-Rivera R, Morrison A, Diesmann M, Pearce TC.

Neural Comput. 2006 Nov;18(11):2651-79.

PMID:
16999574
7.

Self organized mapping of data clusters to neuron groups.

Müller D.

Neural Netw. 2009 May;22(4):415-24. doi: 10.1016/j.neunet.2008.09.017. Epub 2008 Nov 20.

PMID:
19103474
8.

Clustering irregular shapes using high-order neurons.

Lipson H, Siegelmann HT.

Neural Comput. 2000 Oct;12(10):2331-53.

PMID:
11032037
9.

Nonlinear electronic circuit with neuron like bursting and spiking dynamics.

Savino GV, Formigli CM.

Biosystems. 2009 Jul;97(1):9-14. doi: 10.1016/j.biosystems.2009.03.005. Epub 2009 Apr 1.

PMID:
19505632
10.
11.

Distinguishing causal interactions in neural populations.

Seth AK, Edelman GM.

Neural Comput. 2007 Apr;19(4):910-33.

PMID:
17348767
12.

Population thinking and neuronal selection: metaphors or concepts?

Mayr E.

Int Rev Neurobiol. 1994;37:27-34; discussion 47-50. No abstract available.

PMID:
7883481
13.

Using complicated, wide dynamic range driving to develop models of single neurons in single recording sessions.

Hobbs KH, Hooper SL.

J Neurophysiol. 2008 Apr;99(4):1871-83. doi: 10.1152/jn.00032.2008. Epub 2008 Feb 6.

14.

Computational properties of networks of synchronous groups of spiking neurons.

Dayhoff JE.

Neural Comput. 2007 Sep;19(9):2433-67.

PMID:
17650065
15.

Group report: emergent properties of natural and artificial systems.

Reimann S, Fuster JM, Gierer A, Mayer-Kress G, Neumann T, Roelfsema P, Rotter S, Schöner G, Stephan A, Vaadia E, Walter H.

Z Naturforsch C. 1998 Jul-Aug;53(7-8):770-4. No abstract available.

PMID:
9755525
16.

Neural-electronic inhibition simulated with a neuron model implemented in SPICE.

Szlavik RB, Bhuiyan AK, Carver A, Jenkins F.

IEEE Trans Neural Syst Rehabil Eng. 2006 Mar;14(1):109-15.

PMID:
16562638
17.

Towards cortex sized artificial neural systems.

Johansson C, Lansner A.

Neural Netw. 2007 Jan;20(1):48-61. Epub 2006 Jul 24.

PMID:
16860539
18.

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
19.

Learning to attend: modeling the shaping of selectivity in infero-temporal cortex in a categorization task.

Szabo M, Deco G, Fusi S, Del Giudice P, Mattia M, Stetter M.

Biol Cybern. 2006 May;94(5):351-65. Epub 2006 Mar 23.

PMID:
16555071
20.

Functional consequences of model complexity in rhythmic systems: I. Systematic reduction of a bursting neuron model.

Sorensen ME, DeWeerth SP.

J Neural Eng. 2007 Sep;4(3):179-88. Epub 2007 Apr 20.

PMID:
17873419

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