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Fano Factor: A Potentially Useful Information

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F20%3A00535578" target="_blank" >RIV/67985823:_____/20:00535578 - isvavai.cz</a>

  • Result on the web

    <a href="https://www.frontiersin.org/articles/10.3389/fncom.2020.569049/full" target="_blank" >https://www.frontiersin.org/articles/10.3389/fncom.2020.569049/full</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.3389/fncom.2020.569049" target="_blank" >10.3389/fncom.2020.569049</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Fano Factor: A Potentially Useful Information

  • Original language description

    The Fano factor, defined as the variance-to-mean ratio of spike counts in a time window, is often used to measure the variability of neuronal spike trains. However, despite its transparent definition, careless use of the Fano factor can easily lead to distorted or even wrong results. One of the problems is the unclear dependence of the Fano factor on the spiking rate, which is often neglected or handled insufficiently. In this paper we aim to explore this problem in more detail and to study the possible solution, which is to evaluate the Fano factor in the operational time. We use equilibrium renewal and Markov renewal processes as spike train models to describe the method in detail, and we provide an illustration on experimental data.

  • Czech name

  • Czech description

Classification

  • Type

    J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database

  • CEP classification

  • OECD FORD branch

    10103 - Statistics and probability

Result continuities

  • Project

    <a href="/en/project/GA20-10251S" target="_blank" >GA20-10251S: Optimality of neuronal communication: an information-theoretic perspective</a><br>

  • Continuities

    I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Name of the periodical

    Frontiers in Computational Neuroscience

  • ISSN

    1662-5188

  • e-ISSN

  • Volume of the periodical

    14

  • Issue of the periodical within the volume

    Nov 20

  • Country of publishing house

    CH - SWITZERLAND

  • Number of pages

    14

  • Pages from-to

    569049

  • UT code for WoS article

    000596050300001

  • EID of the result in the Scopus database

    2-s2.0-85097215057