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BMC Neuroscience

Open Access

Measures of statistical dispersion based on Entropy and Fisher information

  • Lubomir Kostal1,
  • Petr Lansky1 and
  • Ondrej Pokora1
BMC Neuroscience201112(Suppl 1):P255

Published: 18 July 2011


Standard DeviationExperimental DataAnimal ModelFisher InformationStatistical Dispersion

We propose and discuss two information-based measures of statistical dispersion suitable to description of interspike interval data. The measures are compared with the standard deviation. Although the standard deviation is used routinely, we show that it is not well suited to quantify some aspects of dispersion which are often expected intuitively, such as the degree of randomness. The proposed dispersion measures are not mutually independent, however, each describes the firing regularity from a different point of view. We discuss relationships between the measures and describe their extreme values. We also apply the method to real experimental data from spontaneously active olfactory neurons of rats. Our results and conclusions are applicable to a wide range of situations where the distribution of a continuous positive random variable is of interest.



This work was supported by AV0Z50110509 and Centre for Neuroscience LC554.

Authors’ Affiliations

Department of Computational Neuroscience, Institute of Physiology, Praha, Czech Republic


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© Kostal et al; licensee BioMed Central Ltd. 2011

This article is published under license to BioMed Central Ltd. This is an open access article distributed under the terms of the Creative Commons Attribution License (, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.