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

Result code in 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>

Alternative codes found

RIV/67985823:_____/08:00311439

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

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

Original language description

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

Czech name

Klasifikace stimulů podle křivek stimulus-odpověď a jejich variabilitě

Czech description

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

Type

J_x - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)

CEP classification

BD - Information theory

OECD FORD branch

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Project

Result was created during the realization of more than one project. More information in the Projects tab.

Continuities

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

Publication year

2008

Confidentiality

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

Name of the periodical

Brain Research

ISSN

0006-8993

e-ISSN

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Volume of the periodical

Volume 122

Issue of the periodical within the volume

srpen 2008

Country of publishing house

NL - THE KINGDOM OF THE NETHERLANDS

Number of pages

10

Pages from-to

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UT code for WoS article

000258954600007

EID of the result in the Scopus database

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