Extended time-frequency granger causality for evaluation of functional network connectivity in event-related FMRI data

Author

Havlicek, M. ; Jan, J. ; Calhoun, V.D. ; Brazdil, M.

Author_Institution

Dept. of Biomed. Eng., Univ. of Technol. Brno, Brno, Czech Republic

fYear

2009

fDate

3-6 Sept. 2009

Firstpage

4440

Lastpage

4443

Abstract

In this article, we show that adaptive multivariate autoregressive (AMVAR) modeling accompanied by proper estimation of the delay and the width of hemodynamic response function is an effective technique for evaluation of spectral Granger causality among different functional brain networks identified by independent component analysis from event-related fMRI data. The entire concept is demonstrated on 28 subjects auditory oddball fMRI data.

Keywords

autoregressive processes; biomedical MRI; brain; causality; haemodynamics; independent component analysis; medical signal processing; adaptive multivariate autoregressive modeling; auditory oddball fMRI data; delay estimation; event-related FMRI data; extended time-frequency Granger causality; functional brain networks; functional network connectivity; hemodynamic response function; independent component analysis; spectral Granger causality; Algorithms; Brain; Hemodynamics; Humans; Magnetic Resonance Imaging; Multivariate Analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2009. EMBC 2009. Annual International Conference of the IEEE

Conference_Location

Minneapolis, MN

ISSN

1557-170X

Print_ISBN

978-1-4244-3296-7

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2009.5332759

Filename

5332759