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Journal Abstract Search


192 related items for PubMed ID: 30294750

  • 1. Linear-nonlinear-time-warp-poisson models of neural activity.
    Lawlor PN, Perich MG, Miller LE, Kording KP.
    J Comput Neurosci; 2018 Dec; 45(3):173-191. PubMed ID: 30294750
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  • 2. 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
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  • 3. The spike trains of inhibited pacemaker neurons seen through the magnifying glass of nonlinear analyses.
    Segundo JP, Sugihara G, Dixon P, Stiber M, Bersier LF.
    Neuroscience; 1998 Dec; 87(4):741-66. PubMed ID: 9759964
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  • 4. Modeling stimulus-dependent variability improves decoding of population neural responses.
    Ghanbari A, Lee CM, Read HL, Stevenson IH.
    J Neural Eng; 2019 Oct 25; 16(6):066018. PubMed ID: 31404915
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  • 5. An Empirical Model for Reliable Spiking Activity.
    Wang W, Tripathy SJ, Padmanabhan K, Urban NN, Kass RE.
    Neural Comput; 2015 Aug 25; 27(8):1609-23. PubMed ID: 26079749
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  • 7. Statistical properties of superimposed stationary spike trains.
    Deger M, Helias M, Boucsein C, Rotter S.
    J Comput Neurosci; 2012 Jun 25; 32(3):443-63. PubMed ID: 21964584
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  • 8. A rate and history-preserving resampling algorithm for neural spike trains.
    Harrison MT, Geman S.
    Neural Comput; 2009 May 25; 21(5):1244-58. PubMed ID: 19018703
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  • 14. What can a neuron learn with spike-timing-dependent plasticity?
    Legenstein R, Naeger C, Maass W.
    Neural Comput; 2005 Nov 25; 17(11):2337-82. PubMed ID: 16156932
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  • 17. Serial correlation in neural spike trains: experimental evidence, stochastic modeling, and single neuron variability.
    Farkhooi F, Strube-Bloss MF, Nawrot MP.
    Phys Rev E Stat Nonlin Soft Matter Phys; 2009 Feb 25; 79(2 Pt 1):021905. PubMed ID: 19391776
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