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On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985823%3A_____%2F18%3A00489921" target="_blank" >RIV/67985823:_____/18:00489921 - isvavai.cz</a>

  • Result on the web

    <a href="http://dx.doi.org/10.1063/1.5009574" target="_blank" >http://dx.doi.org/10.1063/1.5009574</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1063/1.5009574" target="_blank" >10.1063/1.5009574</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    On two diffusion neuronal models with multiplicative noise: The mean first-passage time properties

  • Original language description

    Two diffusion processes with multiplicative noise, able to model the changes in the neuronal membrane depolarization between two consecutive spikes of a single neuron, are considered and compared. The processes have the same deterministic part but different stochastic components. The differences in the state-dependent variabilities, their asymptotic distributions, and the properties of the first-passage time across a constant threshold are investigated. Closed form expressions for the mean of the first-passage time of both processes are derived and applied to determine the role played by the parameters involved in the model. It is shown that for some values of the input parameters, the higher variability, given by the second moment, does not imply shorter mean first-passage time. The reason for that can be found in the complete shape of the stationary distribution of the two processes. Applications outside neuroscience are also mentioned.

  • 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

    10102 - Applied mathematics

Result continuities

  • Project

    <a href="/en/project/GA17-06943S" target="_blank" >GA17-06943S: Neural coding precision and its adaptation to the stimulus statistics</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2018

  • Confidentiality

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

Data specific for result type

  • Name of the periodical

    Chaos

  • ISSN

    1054-1500

  • e-ISSN

  • Volume of the periodical

    28

  • Issue of the periodical within the volume

    4

  • Country of publishing house

    US - UNITED STATES

  • Number of pages

    9

  • Pages from-to

  • UT code for WoS article

    000431142000007

  • EID of the result in the Scopus database

    2-s2.0-85044920219