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正随机变量的可变性度量。

Variability measures of positive random variables.

机构信息

Department of Computational Neuroscience, Institute of Physiology, Academy of Sciences of the Czech Republic, Prague, Czech Republic.

出版信息

PLoS One. 2011;6(7):e21998. doi: 10.1371/journal.pone.0021998. Epub 2011 Jul 22.

Abstract

During the stationary part of neuronal spiking response, the stimulus can be encoded in the firing rate, but also in the statistical structure of the interspike intervals. We propose and discuss two information-based measures of statistical dispersion of the interspike interval distribution, the entropy-based dispersion and Fisher information-based dispersion. The measures are compared with the frequently used concept of standard deviation. It is shown, that standard deviation is not well suited to quantify some aspects of dispersion that are often expected intuitively, such as the degree of randomness. The proposed dispersion measures are not entirely independent, although each describes the interspike intervals from a different point of view. The new methods are applied to common models of neuronal firing and to both simulated and experimental data.

摘要

在神经元发放反应的静止部分,刺激可以通过发放率进行编码,也可以通过发放间隔的统计结构进行编码。我们提出并讨论了两种基于信息的发放间隔分布统计离散度的度量方法,基于熵的离散度和基于 Fisher 信息的离散度。这两种度量方法与常用的标准差概念进行了比较。结果表明,标准差并不适合量化一些直观上期望的离散度方面,例如随机性的程度。所提出的离散度度量方法并不完全独立,尽管它们各自从不同的角度描述了发放间隔。新方法应用于常见的神经元发放模型,以及模拟和实验数据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dfd5/3142115/81287767dfd3/pone.0021998.g001.jpg

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