Analysis of fMRI time-series by entropy measure

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00023752%3A_____%2F12%3A43913751" target="_blank" >RIV/00023752:_____/12:43913751 - isvavai.cz</a>

Result on the web

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DOI - Digital Object Identifier

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Result language

angličtina

Original language name

Analysis of fMRI time-series by entropy measure

Original language description

Entropy is a measure of information content or complexity. Information-theoretic modeling has been successfully used in various biological data analyses including functional magnetic resonance (fMRI). Several studies have tested and evaluated entropy measures on simulated datasets and real fMRI data. The efficiency of entropy algorithms has been compared to classical methods based on the linear model. Here we explain and summarize entropy algorithms that have been used in fMRI analysis, their advantagesover classical methods and their potential use in event-related and block design fMRI.

Czech name

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Czech description

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Type

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

CEP classification

FH - Neurology, neuro-surgery, nuero-sciences

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

2012

Confidentiality

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

Name of the periodical

Neuroendocrinology Letters

ISSN

0172-780X

e-ISSN

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Volume of the periodical

33

Issue of the periodical within the volume

5

Country of publishing house

SE - SWEDEN

Number of pages

6

Pages from-to

471-476

UT code for WoS article

000311470400001

EID of the result in the Scopus database

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