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Journal Abstract Search

213 related items for PubMed ID: 27008191

  • 21.
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  • 22. Analyzing short-term noise dependencies of spike-counts in macaque prefrontal cortex using copulas and the flashlight transformation.
    Onken A, Grünewälder S, Munk MH, Obermayer K.
    PLoS Comput Biol; 2009 Nov; 5(11):e1000577. PubMed ID: 19956759
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  • 23. Coding with noisy neurons: stability of tuning curve estimation strongly depends on the analysis method.
    Etzold A, Schwegler H, Eurich CW.
    J Neurosci Methods; 2004 Apr 30; 134(2):109-19. PubMed ID: 15003377
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  • 26. Increase of neuronal response variability at higher processing levels as revealed by simultaneous recordings.
    Vogel A, Hennig RM, Ronacher B.
    J Neurophysiol; 2005 Jun 30; 93(6):3548-59. PubMed ID: 15716366
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  • 30. Quantifying variability in neural responses and its application for the validation of model predictions.
    Hsu A, Borst A, Theunissen FE.
    Network; 2004 May 30; 15(2):91-109. PubMed ID: 15214701
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  • 31. The firing statistics of Poisson neuron models driven by slow stimuli.
    Urdapilleta E, Samengo I.
    Biol Cybern; 2009 Oct 30; 101(4):265-77. PubMed ID: 19784667
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  • 32. Bayesian active learning of neural firing rate maps with transformed gaussian process priors.
    Park M, Weller JP, Horwitz GD, Pillow JW.
    Neural Comput; 2014 Aug 30; 26(8):1519-41. PubMed ID: 24877730
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  • 33. Dimensionality reduction in neural models: an information-theoretic generalization of spike-triggered average and covariance analysis.
    Pillow JW, Simoncelli EP.
    J Vis; 2006 Apr 28; 6(4):414-28. PubMed ID: 16889478
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  • 34. Probabilistic population codes for Bayesian decision making.
    Beck JM, Ma WJ, Kiani R, Hanks T, Churchland AK, Roitman J, Shadlen MN, Latham PE, Pouget A.
    Neuron; 2008 Dec 26; 60(6):1142-52. PubMed ID: 19109917
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  • 35. Nonconvergence in logistic and poisson models for neural spiking.
    Zhao M, Iyengar S.
    Neural Comput; 2010 May 26; 22(5):1231-44. PubMed ID: 20100077
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  • 36. Poisson or not Poisson: differences in spike train statistics between parietal cortical areas.
    Averbeck BB.
    Neuron; 2009 May 14; 62(3):310-1. PubMed ID: 19447087
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  • 37. Maximally informative stimuli and tuning curves for sigmoidal rate-coding neurons and populations.
    McDonnell MD, Stocks NG.
    Phys Rev Lett; 2008 Aug 01; 101(5):058103. PubMed ID: 18764432
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  • 38. Neuron's eye view: Inferring features of complex stimuli from neural responses.
    Chen X, Beck JM, Pearson JM.
    PLoS Comput Biol; 2017 Aug 01; 13(8):e1005645. PubMed ID: 28827790
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  • 39. Spike-train variability of auditory neurons in vivo: dynamic responses follow predictions from constant stimuli.
    Schaette R, Gollisch T, Herz AV.
    J Neurophysiol; 2005 Jun 01; 93(6):3270-81. PubMed ID: 15689392
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  • 40. A flexible approach to modelling over-, under- and equidispersed count data in IRT: The Two-Parameter Conway-Maxwell-Poisson Model.
    Beisemann M.
    Br J Math Stat Psychol; 2022 Nov 01; 75(3):411-443. PubMed ID: 35678959
    [Abstract] [Full Text] [Related]

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