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

Kód výsledku v 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>

Výsledek na webu

<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>

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

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

Popis výsledku anglicky

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.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10102 - Applied mathematics

Projekt

<a href="/cs/project/GA17-06943S" target="_blank" >GA17-06943S: Přesnost neuronálního kódování a její adaptace na statistiku stimulu</a><br>

Návaznosti

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

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název periodika

Chaos

ISSN

1054-1500

e-ISSN

—

Svazek periodika

28

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

9

Strana od-do

—

Kód UT WoS článku

000431142000007

EID výsledku v databázi Scopus

2-s2.0-85044920219