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

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

Research output: Contribution to journalArticle

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.

Original languageEnglish (US)
Pages (from-to)4440-4443
Number of pages4
JournalConference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference
StatePublished - 2009
Externally publishedYes

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Causality
Magnetic Resonance Imaging
Independent component analysis
Hemodynamics
Brain

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition
  • Signal Processing
  • Biomedical Engineering
  • Health Informatics

Cite this

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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.",
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