Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality

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

doi:10.1007/978-3-642-03882-2_191

Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality

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

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Scopus citations

Abstract

In this article we show that Adaptive Multivariate Autoregressive (AMVAR) modeling accompanied by proper preprocessing is an effective technique for evaluation of spectral Granger causality among functional brain networks identified by independent component analysis from event-related fMRI data.

Original language	English (US)
Title of host publication	World Congress on Medical Physics and Biomedical Engineering
Subtitle of host publication	Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Publisher	Springer Verlag
Pages	716-719
Number of pages	4
Edition	4
ISBN (Print)	9783642038815
DOIs	https://doi.org/10.1007/978-3-642-03882-2_191
State	Published - 2009
Externally published	Yes
Event	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics - Munich, Germany Duration: Sep 7 2009 → Sep 12 2009

Publication series

Name	IFMBE Proceedings
Number	4
Volume	25
ISSN (Print)	1680-0737

Other

Other	World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics
Country/Territory	Germany
City	Munich
Period	9/7/09 → 9/12/09

Keywords

Adaptive
Granger
ICA
Spectral
fMRI

ASJC Scopus subject areas

Bioengineering
Biomedical Engineering

Access to Document

10.1007/978-3-642-03882-2_191

Cite this

Havlicek, M., Jan, J., Calhoun, V. D., Brazdil, M., & Mikl, M. (2009). Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality. In World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics (4 ed., pp. 716-719). (IFMBE Proceedings; Vol. 25, No. 4). Springer Verlag. https://doi.org/10.1007/978-3-642-03882-2_191

Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality. / Havlicek, M.; Jan, J.; Calhoun, V. D. et al.
World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4. ed. Springer Verlag, 2009. p. 716-719 (IFMBE Proceedings; Vol. 25, No. 4).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Havlicek, M, Jan, J, Calhoun, VD, Brazdil, M & Mikl, M 2009, Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality. in World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 edn, IFMBE Proceedings, no. 4, vol. 25, Springer Verlag, pp. 716-719, World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics, Munich, Germany, 9/7/09. https://doi.org/10.1007/978-3-642-03882-2_191

Havlicek M, Jan J, Calhoun VD, Brazdil M, Mikl M. Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality. In World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4 ed. Springer Verlag. 2009. p. 716-719. (IFMBE Proceedings; 4). doi: 10.1007/978-3-642-03882-2_191

Havlicek, M. ; Jan, J. ; Calhoun, V. D. et al. / Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality. World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics. 4. ed. Springer Verlag, 2009. pp. 716-719 (IFMBE Proceedings; 4).

@inproceedings{f2972b4aa42642159ffc79f091594cce,

title = "Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality",

abstract = "In this article we show that Adaptive Multivariate Autoregressive (AMVAR) modeling accompanied by proper preprocessing is an effective technique for evaluation of spectral Granger causality among functional brain networks identified by independent component analysis from event-related fMRI data.",

keywords = "Adaptive, Granger, ICA, Spectral, fMRI",

author = "M. Havlicek and J. Jan and Calhoun, {V. D.} and M. Brazdil and M. Mikl",

year = "2009",

doi = "10.1007/978-3-642-03882-2_191",

language = "English (US)",

isbn = "9783642038815",

series = "IFMBE Proceedings",

publisher = "Springer Verlag",

number = "4",

pages = "716--719",

booktitle = "World Congress on Medical Physics and Biomedical Engineering",

edition = "4",

note = "World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics ; Conference date: 07-09-2009 Through 12-09-2009",

}

TY - GEN

T1 - Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality

AU - Havlicek, M.

AU - Jan, J.

AU - Calhoun, V. D.

AU - Brazdil, M.

AU - Mikl, M.

PY - 2009

Y1 - 2009

N2 - In this article we show that Adaptive Multivariate Autoregressive (AMVAR) modeling accompanied by proper preprocessing is an effective technique for evaluation of spectral Granger causality among functional brain networks identified by independent component analysis from event-related fMRI data.

AB - In this article we show that Adaptive Multivariate Autoregressive (AMVAR) modeling accompanied by proper preprocessing is an effective technique for evaluation of spectral Granger causality among functional brain networks identified by independent component analysis from event-related fMRI data.

KW - Adaptive

KW - Granger

KW - ICA

KW - Spectral

KW - fMRI

UR - http://www.scopus.com/inward/record.url?scp=77950185850&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77950185850&partnerID=8YFLogxK

U2 - 10.1007/978-3-642-03882-2_191

DO - 10.1007/978-3-642-03882-2_191

M3 - Conference contribution

AN - SCOPUS:77950185850

SN - 9783642038815

T3 - IFMBE Proceedings

SP - 716

EP - 719

BT - World Congress on Medical Physics and Biomedical Engineering

PB - Springer Verlag

T2 - World Congress on Medical Physics and Biomedical Engineering: Image Processing, Biosignal Processing, Modelling and Simulation, Biomechanics

Y2 - 7 September 2009 through 12 September 2009

ER -

Evaluation of functional network connectivity in event-related FMRI data based on ICA and time-frequency granger causality

Abstract

Publication series

Other

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this