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Journal Abstract Search

311 related items for PubMed ID: 21919785

  • 1. Improved similarity measures for small sets of spike trains.
    Naud R, Gerhard F, Mensi S, Gerstner W.
    Neural Comput; 2011 Dec; 23(12):3016-69. PubMed ID: 21919785
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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. Wavelet-based processing of neuronal spike trains prior to discriminant analysis.
    Laubach M.
    J Neurosci Methods; 2004 Apr 30; 134(2):159-68. PubMed ID: 15003382
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  • 4. A reproducing kernel Hilbert space framework for spike train signal processing.
    Paiva AR, Park I, Príncipe JC.
    Neural Comput; 2009 Feb 30; 21(2):424-49. PubMed ID: 19431265
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  • 5. Measurement of variability dynamics in cortical spike trains.
    Nawrot MP, Boucsein C, Rodriguez Molina V, Riehle A, Aertsen A, Rotter S.
    J Neurosci Methods; 2008 Apr 30; 169(2):374-90. PubMed ID: 18155774
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  • 6. Attractor reliability reveals deterministic structure in neuronal spike trains.
    Tiesinga PH, Fellous JM, Sejnowski TJ.
    Neural Comput; 2002 Jul 30; 14(7):1629-50. PubMed ID: 12079549
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  • 12. Measuring spike pattern reliability with the Lempel-Ziv-distance.
    Christen M, Kohn A, Ott T, Stoop R.
    J Neurosci Methods; 2006 Sep 30; 156(1-2):342-50. PubMed ID: 16584787
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  • 17. Spatiotemporal spike encoding of a continuous external signal.
    Masuda N, Aihara K.
    Neural Comput; 2002 Jul 30; 14(7):1599-628. PubMed ID: 12079548
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  • 18. Parameter identification for a local field potential driven model of the Parkinsonian subthalamic nucleus spike activity.
    Michmizos KP, Sakas D, Nikita KS.
    Neural Netw; 2012 Dec 30; 36():146-56. PubMed ID: 23131592
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  • 19. 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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