Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F10%3APU87210" target="_blank" >RIV/00216305:26220/10:PU87210 - isvavai.cz</a>
Alternative codes found
RIV/00216224:14110/10:00046675
Result on the web
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DOI - Digital Object Identifier
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Alternative languages
Result language
angličtina
Original language name
Dynamic Granger causality based on Kalman filter for evaluation of functional network connectivity in fMRI data
Original language description
Time-varying estimation of multivariate autoregresive model based on Kalman filtering for more accurate evaluation of Granger causality in fMRI data.
Czech name
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Czech description
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Classification
Type
J<sub>x</sub> - Unclassified - Peer-reviewed scientific article (Jimp, Jsc and Jost)
CEP classification
FH - Neurology, neuro-surgery, nuero-sciences
OECD FORD branch
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Result continuities
Project
<a href="/en/project/1M0572" target="_blank" >1M0572: Data, algorithms, decision making</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>Z - Vyzkumny zamer (s odkazem do CEZ)<br>S - Specificky vyzkum na vysokych skolach
Others
Publication year
2010
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
NeuroImage
ISSN
1053-8119
e-ISSN
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Volume of the periodical
53
Issue of the periodical within the volume
1
Country of publishing house
US - UNITED STATES
Number of pages
13
Pages from-to
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UT code for WoS article
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EID of the result in the Scopus database
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