These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


BIOMARKERS

Molecular Biopsy of Human Tumors

- a resource for Precision Medicine *

226 related articles for article (PubMed ID: 20830512)

  • 1. A network of spiking neurons that can represent interval timing: mean field analysis.
    Gavornik JP; Shouval HZ
    J Comput Neurosci; 2011 Apr; 30(2):501-13. PubMed ID: 20830512
    [TBL] [Abstract][Full Text] [Related]  

  • 2. Learning reward timing in cortex through reward dependent expression of synaptic plasticity.
    Gavornik JP; Shuler MG; Loewenstein Y; Bear MF; Shouval HZ
    Proc Natl Acad Sci U S A; 2009 Apr; 106(16):6826-31. PubMed ID: 19346478
    [TBL] [Abstract][Full Text] [Related]  

  • 3. An STDP training algorithm for a spiking neural network with dynamic threshold neurons.
    Strain TJ; McDaid LJ; McGinnity TM; Maguire LP; Sayers HM
    Int J Neural Syst; 2010 Dec; 20(6):463-80. PubMed ID: 21117270
    [TBL] [Abstract][Full Text] [Related]  

  • 4. Learning in neural networks by reinforcement of irregular spiking.
    Xie X; Seung HS
    Phys Rev E Stat Nonlin Soft Matter Phys; 2004 Apr; 69(4 Pt 1):041909. PubMed ID: 15169045
    [TBL] [Abstract][Full Text] [Related]  

  • 5. Mirrored STDP Implements Autoencoder Learning in a Network of Spiking Neurons.
    Burbank KS
    PLoS Comput Biol; 2015 Dec; 11(12):e1004566. PubMed ID: 26633645
    [TBL] [Abstract][Full Text] [Related]  

  • 6. A single spiking neuron that can represent interval timing: analysis, plasticity and multi-stability.
    Shouval HZ; Gavornik JP
    J Comput Neurosci; 2011 Apr; 30(2):489-99. PubMed ID: 20827572
    [TBL] [Abstract][Full Text] [Related]  

  • 7. Embedding multiple trajectories in simulated recurrent neural networks in a self-organizing manner.
    Liu JK; Buonomano DV
    J Neurosci; 2009 Oct; 29(42):13172-81. PubMed ID: 19846705
    [TBL] [Abstract][Full Text] [Related]  

  • 8. Identification of functional synaptic plasticity from spiking activities using nonlinear dynamical modeling.
    Song D; Chan RH; Robinson BS; Marmarelis VZ; Opris I; Hampson RE; Deadwyler SA; Berger TW
    J Neurosci Methods; 2015 Apr; 244():123-35. PubMed ID: 25280984
    [TBL] [Abstract][Full Text] [Related]  

  • 9. Bayesian spiking neurons II: learning.
    Deneve S
    Neural Comput; 2008 Jan; 20(1):118-45. PubMed ID: 18045003
    [TBL] [Abstract][Full Text] [Related]  

  • 10. Introduction to spiking neural networks: Information processing, learning and applications.
    Ponulak F; Kasinski A
    Acta Neurobiol Exp (Wars); 2011; 71(4):409-33. PubMed ID: 22237491
    [TBL] [Abstract][Full Text] [Related]  

  • 11. Distributed synchrony in a cell assembly of spiking neurons.
    Levy N; Horn D; Meilijson I; Ruppin E
    Neural Netw; 2001; 14(6-7):815-24. PubMed ID: 11665773
    [TBL] [Abstract][Full Text] [Related]  

  • 12. A Scalable Weight-Free Learning Algorithm for Regulatory Control of Cell Activity in Spiking Neuronal Networks.
    Zhang X; Foderaro G; Henriquez C; Ferrari S
    Int J Neural Syst; 2018 Mar; 28(2):1750015. PubMed ID: 28270025
    [TBL] [Abstract][Full Text] [Related]  

  • 13. Self-sustained asynchronous irregular states and Up-Down states in thalamic, cortical and thalamocortical networks of nonlinear integrate-and-fire neurons.
    Destexhe A
    J Comput Neurosci; 2009 Dec; 27(3):493-506. PubMed ID: 19499317
    [TBL] [Abstract][Full Text] [Related]  

  • 14. On the sample complexity of learning for networks of spiking neurons with nonlinear synaptic interactions.
    Schmitt M
    IEEE Trans Neural Netw; 2004 Sep; 15(5):995-1001. PubMed ID: 15484876
    [TBL] [Abstract][Full Text] [Related]  

  • 15. Training and Spontaneous Reinforcement of Neuronal Assemblies by Spike Timing Plasticity.
    Ocker GK; Doiron B
    Cereb Cortex; 2019 Mar; 29(3):937-951. PubMed ID: 29415191
    [TBL] [Abstract][Full Text] [Related]  

  • 16. A Simple Network Architecture Accounts for Diverse Reward Time Responses in Primary Visual Cortex.
    Huertas MA; Hussain Shuler MG; Shouval HZ
    J Neurosci; 2015 Sep; 35(37):12659-72. PubMed ID: 26377457
    [TBL] [Abstract][Full Text] [Related]  

  • 17. A solution to the learning dilemma for recurrent networks of spiking neurons.
    Bellec G; Scherr F; Subramoney A; Hajek E; Salaj D; Legenstein R; Maass W
    Nat Commun; 2020 Jul; 11(1):3625. PubMed ID: 32681001
    [TBL] [Abstract][Full Text] [Related]  

  • 18. Neuron as a reward-modulated combinatorial switch and a model of learning behavior.
    Rvachev MM
    Neural Netw; 2013 Oct; 46():62-74. PubMed ID: 23708671
    [TBL] [Abstract][Full Text] [Related]  

  • 19. Supervised Learning in Spiking Neural Networks for Precise Temporal Encoding.
    Gardner B; Grüning A
    PLoS One; 2016; 11(8):e0161335. PubMed ID: 27532262
    [TBL] [Abstract][Full Text] [Related]  

  • 20. Learning in realistic networks of spiking neurons and spike-driven plastic synapses.
    Mongillo G; Curti E; Romani S; Amit DJ
    Eur J Neurosci; 2005 Jun; 21(11):3143-60. PubMed ID: 15978023
    [TBL] [Abstract][Full Text] [Related]  

    [Next]    [New Search]
    of 12.