A dual echo approach to removing motion artefacts in fMRI time series

In fMRI, subject motion can severely affect data quality. This is a particular problem when movement is correlated with the experimental paradigm as this potentially causes artefactual activation. A method is presented that uses linear regression, to utilise the time course of an image acquired at v...

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Bibliographic Details
Published inNMR in biomedicine Vol. 22; no. 5; pp. 551 - 560
Main Authors Buur, Pieter F., Poser, Benedikt A., Norris, David G.
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 01.06.2009
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Summary:In fMRI, subject motion can severely affect data quality. This is a particular problem when movement is correlated with the experimental paradigm as this potentially causes artefactual activation. A method is presented that uses linear regression, to utilise the time course of an image acquired at very short echo time (TE) as a voxel‐wise regressor for a second image in the same echo train, that is acquired with high BOLD sensitivity. The value of this approach is demonstrated using task‐locked motion combined with visual stimulation. Results obtained at both 1.5 and 3 T show improvements in functional activation maps for individual subjects. The method is straightforward to implement, does not require extra scan time and can easily be embedded in a multi‐echo acquisition framework. Copyright © 2009 John Wiley & Sons, Ltd. Subject motion can severely affect fMRI data quality. A method is presented that utilises the time course of an image acquired at short echo time as regressor for a second image in the same echo train that has high BOLD sensitivity. Results at 1.5 and 3 T show improvements in activation for individual subjects in a paradigm combining visual stimulation with task‐locked motion. The method is straightforward to implement and does not require extra scan time.
Bibliography:Dutch Technology Foundation (STW) - No. NGT.6154
ark:/67375/WNG-8W7ZFK8G-4
ArticleID:NBM1371
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content type line 23
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ISSN:0952-3480
1099-1492
DOI:10.1002/nbm.1371