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 *

185 related articles for article (PubMed ID: 24245675)

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

  • 22. Optimal decision making on the basis of evidence represented in spike trains.
    Zhang J; Bogacz R
    Neural Comput; 2010 May; 22(5):1113-48. PubMed ID: 20028228
    [TBL] [Abstract][Full Text] [Related]  

  • 23. The effect of interspike interval statistics on the information gain under the rate coding hypothesis.
    Koyama S; Kostal L
    Math Biosci Eng; 2014 Feb; 11(1):63-80. PubMed ID: 24245680
    [TBL] [Abstract][Full Text] [Related]  

  • 24. Information geometry of interspike intervals in spiking neurons.
    Ikeda K
    Neural Comput; 2005 Dec; 17(12):2719-35. PubMed ID: 16212769
    [TBL] [Abstract][Full Text] [Related]  

  • 25. Comparing neuronal spike trains with inhomogeneous Poisson distribution: evaluation procedure and experimental application in cases of cyclic activity.
    Fiore L; Lorenzetti W; Ratti G
    J Neurosci Methods; 2005 Nov; 149(1):7-14. PubMed ID: 15967509
    [TBL] [Abstract][Full Text] [Related]  

  • 26. Modeling and analyzing higher-order correlations in non-Poissonian spike trains.
    Reimer IC; Staude B; Ehm W; Rotter S
    J Neurosci Methods; 2012 Jun; 208(1):18-33. PubMed ID: 22561088
    [TBL] [Abstract][Full Text] [Related]  

  • 27. Spike train statistics and dynamics with synaptic input from any renewal process: a population density approach.
    Ly C; Tranchina D
    Neural Comput; 2009 Feb; 21(2):360-96. PubMed ID: 19431264
    [TBL] [Abstract][Full Text] [Related]  

  • 28. Distribution of interspike intervals estimated from multiple spike trains observed in a short time window.
    Pawlas Z; Lansky P
    Phys Rev E Stat Nonlin Soft Matter Phys; 2011 Jan; 83(1 Pt 1):011910. PubMed ID: 21405716
    [TBL] [Abstract][Full Text] [Related]  

  • 29. Analysis and modelling of variability and covariability of population spike trains across multiple time scales.
    Lyamzin DR; Garcia-Lazaro JA; Lesica NA
    Network; 2012; 23(1-2):76-103. PubMed ID: 22578115
    [TBL] [Abstract][Full Text] [Related]  

  • 30. Interspike interval statistics of a leaky integrate-and-fire neuron driven by Gaussian noise with large correlation times.
    Schwalger T; Schimansky-Geier L
    Phys Rev E Stat Nonlin Soft Matter Phys; 2008 Mar; 77(3 Pt 1):031914. PubMed ID: 18517429
    [TBL] [Abstract][Full Text] [Related]  

  • 31. Cross nearest-spike interval based method to measure synchrony dynamics.
    Montoro AM; Cao R; Faes C; Molenberghs G; Espinosa N; Cudeiro J; Marino J
    Math Biosci Eng; 2014 Feb; 11(1):27-48. PubMed ID: 24245679
    [TBL] [Abstract][Full Text] [Related]  

  • 32. Dethroning the Fano Factor: A Flexible, Model-Based Approach to Partitioning Neural Variability.
    Charles AS; Park M; Weller JP; Horwitz GD; Pillow JW
    Neural Comput; 2018 Apr; 30(4):1012-1045. PubMed ID: 29381442
    [TBL] [Abstract][Full Text] [Related]  

  • 33. Local shuffling of spike trains boosts the accuracy of spike train spectral analysis.
    Rivlin-Etzion M; Ritov Y; Heimer G; Bergman H; Bar-Gad I
    J Neurophysiol; 2006 May; 95(5):3245-56. PubMed ID: 16407432
    [TBL] [Abstract][Full Text] [Related]  

  • 34. A nonparametric approach for detection of bursts in spike trains.
    Gourévitch B; Eggermont JJ
    J Neurosci Methods; 2007 Mar; 160(2):349-58. PubMed ID: 17070926
    [TBL] [Abstract][Full Text] [Related]  

  • 35. On the Spike Train Variability Characterized by Variance-to-Mean Power Relationship.
    Koyama S
    Neural Comput; 2015 Jul; 27(7):1530-48. PubMed ID: 25973546
    [TBL] [Abstract][Full Text] [Related]  

  • 36. Spike train probability models for stimulus-driven leaky integrate-and-fire neurons.
    Koyama S; Kass RE
    Neural Comput; 2008 Jul; 20(7):1776-95. PubMed ID: 18336078
    [TBL] [Abstract][Full Text] [Related]  

  • 37. Gaussian process approach to spiking neurons for inhomogeneous Poisson inputs.
    Amemori KI; Ishii S
    Neural Comput; 2001 Dec; 13(12):2763-97. PubMed ID: 11705410
    [TBL] [Abstract][Full Text] [Related]  

  • 38. Multiscale analysis of neural spike trains.
    Ramezan R; Marriott P; Chenouri S
    Stat Med; 2014 Jan; 33(2):238-56. PubMed ID: 23996238
    [TBL] [Abstract][Full Text] [Related]  

  • 39. 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
    [TBL] [Abstract][Full Text] [Related]  

  • 40. Weber's law implies neural discharge more regular than a Poisson process.
    Kang J; Wu J; Smerieri A; Feng J
    Eur J Neurosci; 2010 Mar; 31(6):1006-18. PubMed ID: 20377615
    [TBL] [Abstract][Full Text] [Related]  

    [Previous]   [Next]    [New Search]
    of 10.