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Journal Abstract Search

213 related items for PubMed ID: 16105224

  • 1. Optimal signal estimation in neuronal models.
    Lánský P, Greenwood PE.
    Neural Comput; 2005 Oct; 17(10):2240-57. PubMed ID: 16105224
    [Abstract] [Full Text] [Related]

  • 2. Optimal signal in sensory neurons under an extended rate coding concept.
    Lansky P, Greenwood PE.
    Biosystems; 2007 Oct; 89(1-3):10-5. PubMed ID: 17284342
    [Abstract] [Full Text] [Related]

  • 3. 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
    [Abstract] [Full Text] [Related]

  • 4. Optimum signal in a diffusion leaky integrate-and-fire neuronal model.
    Lansky P, Sacerdote L, Zucca C.
    Math Biosci; 2007 Jun; 207(2):261-74. PubMed ID: 17070558
    [Abstract] [Full Text] [Related]

  • 5. Classification of stationary neuronal activity according to its information rate.
    Kostal L, Lánský P.
    Network; 2006 Jun; 17(2):193-210. PubMed ID: 16818397
    [Abstract] [Full Text] [Related]

  • 6. Neuronal coding and spiking randomness.
    Kostal L, Lansky P, Rospars JP.
    Eur J Neurosci; 2007 Nov; 26(10):2693-701. PubMed ID: 18001270
    [Abstract] [Full Text] [Related]

  • 7. Optimum signal in a simple neuronal model with signal-dependent noise.
    Greenwood PE, Lánský P.
    Biol Cybern; 2005 Mar; 92(3):199-205. PubMed ID: 15750866
    [Abstract] [Full Text] [Related]

  • 8. Synaptic input statistics tune the variability and reproducibility of neuronal responses.
    Dorval AD, White JA.
    Chaos; 2006 Jun; 16(2):026105. PubMed ID: 16822037
    [Abstract] [Full Text] [Related]

  • 9. Estimating the temporal interval entropy of neuronal discharge.
    Reeke GN, Coop AD.
    Neural Comput; 2004 May; 16(5):941-70. PubMed ID: 15070505
    [Abstract] [Full Text] [Related]

  • 10. Estimating spiking irregularities under changing environments.
    Miura K, Okada M, Amari S.
    Neural Comput; 2006 Oct; 18(10):2359-86. PubMed ID: 16907630
    [Abstract] [Full Text] [Related]

  • 11. Parameters of the diffusion leaky integrate-and-fire neuronal model for a slowly fluctuating signal.
    Picchini U, Ditlevsen S, De Gaetano A, Lansky P.
    Neural Comput; 2008 Nov; 20(11):2696-714. PubMed ID: 18533814
    [Abstract] [Full Text] [Related]

  • 12. Similarity of interspike interval distributions and information gain in a stationary neuronal firing.
    Kostal L, Lansky P.
    Biol Cybern; 2006 Feb; 94(2):157-67. PubMed ID: 16315047
    [Abstract] [Full Text] [Related]

  • 13. Computation of spiking activity for a stochastic spatial neuron model: effects of spatial distribution of input on bimodality and CV of the ISI distribution.
    Tuckwell HC.
    Math Biosci; 2007 Jun; 207(2):246-60. PubMed ID: 17337282
    [Abstract] [Full Text] [Related]

  • 14. Oscillating neurons in the cochlear nucleus: II. Simulation results.
    Bahmer A, Langner G.
    Biol Cybern; 2006 Oct; 95(4):381-92. PubMed ID: 16847667
    [Abstract] [Full Text] [Related]

  • 15. Synaptic transmission in a diffusion model for neural activity.
    Lánská V, Lánský P, Smith CE.
    J Theor Biol; 1994 Feb 21; 166(4):393-406. PubMed ID: 8176948
    [Abstract] [Full Text] [Related]

  • 16. A first-order nonhomogeneous Markov model for the response of spiking neurons stimulated by small phase-continuous signals.
    Tapson J, Jin C, van Schaik A, Etienne-Cummings R.
    Neural Comput; 2009 Jun 21; 21(6):1554-88. PubMed ID: 19191600
    [Abstract] [Full Text] [Related]

  • 17. Increase of neuronal response variability at higher processing levels as revealed by simultaneous recordings.
    Vogel A, Hennig RM, Ronacher B.
    J Neurophysiol; 2005 Jun 21; 93(6):3548-59. PubMed ID: 15716366
    [Abstract] [Full Text] [Related]

  • 18. 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 21; 101(2):103-14. PubMed ID: 19536559
    [Abstract] [Full Text] [Related]

  • 19. Reducing the variability of neural responses: a computational theory of spike-timing-dependent plasticity.
    Bohte SM, Mozer MC.
    Neural Comput; 2007 Feb 21; 19(2):371-403. PubMed ID: 17206869
    [Abstract] [Full Text] [Related]

  • 20. Randomness and variability of the neuronal activity described by the Ornstein-Uhlenbeck model.
    Kostal L, Lansky P, Zucca C.
    Network; 2007 Mar 21; 18(1):63-75. PubMed ID: 17454682
    [Abstract] [Full Text] [Related]

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