Multivariate Autoregressive Modelling of Causal Connections in EEG
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F68407700%3A21230%2F10%3A00172262" target="_blank" >RIV/68407700:21230/10:00172262 - isvavai.cz</a>
Result on the web
—
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
Multivariate Autoregressive Modelling of Causal Connections in EEG
Original language description
Conditional Granger causality and related methods have been used in neurophysiology in recent years for revealing causal relations in brain. Multivariate autoregressive models can model dynamic relations in electroencephalography and derived estimators can measure not only the strength of connections but also their directions which are important for understanding brain function during specific tasks. This paper propose an extension of the conditional Granger causality in order to improve a differentiation between strong and weak causal connections.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
FH - Neurology, neuro-surgery, nuero-sciences
OECD FORD branch
—
Result continuities
Project
<a href="/en/project/GD102%2F08%2FH008" target="_blank" >GD102/08/H008: Analysis and modelling biomedical and speech signals</a><br>
Continuities
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
Article name in the collection
Analýza a zpracování řečových a biologických signálů - sborník prací 2010
ISBN
978-80-01-04680-7
ISSN
—
e-ISSN
—
Number of pages
5
Pages from-to
—
Publisher name
České vysoké učení technické v Praze
Place of publication
Praha
Event location
Praha
Event date
Dec 10, 2010
Type of event by nationality
CST - Celostátní akce
UT code for WoS article
—