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

M. Havlicek, J. Jan, VD. Calhoun, M. Brazdil

Jazyk angličtina Země Spojené státy americké

Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem

Perzistentní odkaz   https://www.medvik.cz/link/bmc12025434

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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$a Havlíček, Martin. $7 xx0276470 $u Department of Biomedical Engineering, University of Technology Brno, Czech Republic, and with the Mind Research Network, Albuquerque, NM, USA. havlicekm@phd.feec.vutbr.cz
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$a Extended time-frequency Granger causality for evaluation of functional network connectivity in event-related FMRI data / $c M. Havlicek, J. Jan, VD. Calhoun, M. Brazdil
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$a 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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