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Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection
Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will a...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5589107/ https://www.ncbi.nlm.nih.gov/pubmed/28880888 http://dx.doi.org/10.1371/journal.pone.0182939 |
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author | Power, Jonathan D. Plitt, Mark Kundu, Prantik Bandettini, Peter A. Martin, Alex |
author_facet | Power, Jonathan D. Plitt, Mark Kundu, Prantik Bandettini, Peter A. Martin, Alex |
author_sort | Power, Jonathan D. |
collection | PubMed |
description | Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). |
format | Online Article Text |
id | pubmed-5589107 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-55891072017-09-15 Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection Power, Jonathan D. Plitt, Mark Kundu, Prantik Bandettini, Peter A. Martin, Alex PLoS One Research Article Head motion can be estimated at any point of fMRI image processing. Processing steps involving temporal interpolation (e.g., slice time correction or outlier replacement) often precede motion estimation in the literature. From first principles it can be anticipated that temporal interpolation will alter head motion in a scan. Here we demonstrate this effect and its consequences in five large fMRI datasets. Estimated head motion was reduced by 10–50% or more following temporal interpolation, and reductions were often visible to the naked eye. Such reductions make the data seem to be of improved quality. Such reductions also degrade the sensitivity of analyses aimed at detecting motion-related artifact and can cause a dataset with artifact to falsely appear artifact-free. These reduced motion estimates will be particularly problematic for studies needing estimates of motion in time, such as studies of dynamics. Based on these findings, it is sensible to obtain motion estimates prior to any image processing (regardless of subsequent processing steps and the actual timing of motion correction procedures, which need not be changed). We also find that outlier replacement procedures change signals almost entirely during times of motion and therefore have notable similarities to motion-targeting censoring strategies (which withhold or replace signals entirely during times of motion). Public Library of Science 2017-09-07 /pmc/articles/PMC5589107/ /pubmed/28880888 http://dx.doi.org/10.1371/journal.pone.0182939 Text en https://creativecommons.org/publicdomain/zero/1.0/ This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication. |
spellingShingle | Research Article Power, Jonathan D. Plitt, Mark Kundu, Prantik Bandettini, Peter A. Martin, Alex Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title | Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title_full | Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title_fullStr | Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title_full_unstemmed | Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title_short | Temporal interpolation alters motion in fMRI scans: Magnitudes and consequences for artifact detection |
title_sort | temporal interpolation alters motion in fmri scans: magnitudes and consequences for artifact detection |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5589107/ https://www.ncbi.nlm.nih.gov/pubmed/28880888 http://dx.doi.org/10.1371/journal.pone.0182939 |
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