Ergodicity and parameter estimates in auditory neural circuits

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F18%3A00100732" target="_blank" >RIV/00216224:14310/18:00100732 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/68407700:21230/18:00315062 RIV/00216208:11110/18:10376709

Výsledek na webu

<a href="http://dx.doi.org/10.1007/s00422-017-0739-5" target="_blank" >http://dx.doi.org/10.1007/s00422-017-0739-5</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/s00422-017-0739-5" target="_blank" >10.1007/s00422-017-0739-5</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Ergodicity and parameter estimates in auditory neural circuits

Popis výsledku v původním jazyce

This paper discusses ergodic properties and circular statistical characteristics in neuronal spike trains. Ergodicity means that the average taken over a long time period and over smaller population should equal to the average in less time and larger population. Objectives are to show simple examples of design and validation of a neuronal model, where the ergodicity assumption helps finding correspondence between variables and parameters. Methods used are analytical and numerical computations, numerical models of phenomenological spiking neurons and neuronal circuits. Results obtained using these methods are the following. They are: formula to calculate vector strength of neural spike timing in dependence of the spike train parameters, description of parameters of spike train variability and model of output spiking density based on assumption of the computation realized by sound localization neural circuit. Theoretical results are illustrated by references to experimental data. Examples of neurons, where spike trains have and have not the ergodic property are then discussed.

Název v anglickém jazyce

Ergodicity and parameter estimates in auditory neural circuits

Popis výsledku anglicky

This paper discusses ergodic properties and circular statistical characteristics in neuronal spike trains. Ergodicity means that the average taken over a long time period and over smaller population should equal to the average in less time and larger population. Objectives are to show simple examples of design and validation of a neuronal model, where the ergodicity assumption helps finding correspondence between variables and parameters. Methods used are analytical and numerical computations, numerical models of phenomenological spiking neurons and neuronal circuits. Results obtained using these methods are the following. They are: formula to calculate vector strength of neural spike timing in dependence of the spike train parameters, description of parameters of spike train variability and model of output spiking density based on assumption of the computation realized by sound localization neural circuit. Theoretical results are illustrated by references to experimental data. Examples of neurons, where spike trains have and have not the ergodic property are then discussed.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

10103 - Statistics and probability

Projekt

<a href="/cs/project/GA15-06991S" target="_blank" >GA15-06991S: Analýza funkcionálních dat a související témata</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

Biological Cybernetics

ISSN

0340-1200

e-ISSN

1432-0770

Svazek periodika

112

Číslo periodika v rámci svazku

1-2

Stát vydavatele periodika

US - Spojené státy americké

Počet stran výsledku

15

Strana od-do

41-55

Kód UT WoS článku

000430460400005

EID výsledku v databázi Scopus

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