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  • Poster presentation
  • Open Access

Histogram binwidth and kernel bandwidth selection for the spike-rate estimation

BMC Neuroscience200910 (Suppl 1) :P116

  • Published:


  • Animal Model
  • Rate Increase
  • Rate Process
  • Free Parameter
  • Experimental Trial

Histogram and kernel methods have been used as standard tools for capturing the instantaneous rate of neuronal spike discharges in the neurophysiology community. These methods are left with one free parameter that determines the smoothness of the estimated rate, namely a binwidth or bandwidth. In most of the neurophysiology literature, however, the binwidth or bandwidth that critically determines the goodness of the fit of the estimated rate to the underlying rate has been selected by individual researchers in an unsystematic manner. Recently, we established a method for selecting the histogram binwidth [1] as well as the kernel bandwidth [2], with which the estimated rate best approximates the unknown underlying rate. The resolution of the optimized estimated rate increases, or the optimal bin/band-width decreases, with the number of spike sequences sampled. It is notable that the optimal bin/band-width diverges if only a small number of experimental trials are available from a moderately fluctuating rate process [3]. In this case, any attempt for characterizing the underlying spike rate will lead to spurious results. To assist those who are confronted with such paucity of data, we developed a method that can suggest how many more trials are needed until the set of data can be analyzed with the required resolution.

Authors’ Affiliations

Theoretical Neuroscience Group, RIKEN Brain Science Institute, Wako-shi, Saitama, Japan
Department of Physics, Kyoto University, Kyoto, Japan


  1. Shimazaki H, Shinomoto S: A method for selecting the bin size of a time histogram. Neural Comput. 2007, 19: 1503-1527. 10.1162/neco.2007.19.6.1503.PubMedView ArticleGoogle Scholar
  2. Shimazaki H, Shinomoto S: Kernel width optimization in the spike-rate estimation. Neural Coding. 2007, Montevideo Uruguay, 120-123.Google Scholar
  3. Koyama S, Shinomoto S: Histogram bin width selection for time-dependent Poisson processes. J Phys A: Math Gen. 2004, 37: 7255-7265. 10.1088/0305-4470/37/29/006.View ArticleGoogle Scholar


© Shimazaki and Shinomoto; licensee BioMed Central Ltd. 2009

This article is published under license to BioMed Central Ltd.