Klasifikace stimulů podle křivek stimulus-odpověď a jejich variabilitě

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14310%2F08%3A00024208" target="_blank" >RIV/00216224:14310/08:00024208 - isvavai.cz</a>

Nalezeny alternativní kódy

RIV/67985823:_____/08:00311439

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Classification of stimuli based on stimulus-response curves and their variability

Popis výsledku v původním jazyce

Neuronal responses evoked in sensory neurons by static stimuli of various intensities are usually characterized by their input-output transfer function, i.e. by plotting the firing frequency (or any other measurable neuron response) versus the corresponding stimulus intensity. The aim of the present article is to determine the stimulus intensities which can be considered as "the most important" from two different points of view: transferring as much information as possible and coding the intensity as precisely as possible. These two problems are very different because, for example, an informative signal may be difficult to identify. We show that the role of noise is crucial in both problems. To obtain the range of stimuli which are the best identified,we propose to use measures based on Fisher information as known from the theory of statistical inference. To classify the most important stimuli from the point of view of information transfer, we suggest methods based on information theo

Název v anglickém jazyce

Classification of stimuli based on stimulus-response curves and their variability

Popis výsledku anglicky

Neuronal responses evoked in sensory neurons by static stimuli of various intensities are usually characterized by their input-output transfer function, i.e. by plotting the firing frequency (or any other measurable neuron response) versus the corresponding stimulus intensity. The aim of the present article is to determine the stimulus intensities which can be considered as "the most important" from two different points of view: transferring as much information as possible and coding the intensity as precisely as possible. These two problems are very different because, for example, an informative signal may be difficult to identify. We show that the role of noise is crucial in both problems. To obtain the range of stimuli which are the best identified,we propose to use measures based on Fisher information as known from the theory of statistical inference. To classify the most important stimuli from the point of view of information transfer, we suggest methods based on information theo

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

BD - Teorie informace

OECD FORD obor

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Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

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

Rok uplatnění

2008

Kód důvěrnosti údajů

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

Název periodika

Brain Research

ISSN

0006-8993

e-ISSN

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Svazek periodika

Volume 122

Číslo periodika v rámci svazku

srpen 2008

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

10

Strana od-do

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Kód UT WoS článku

000258954600007

EID výsledku v databázi Scopus

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