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Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI
Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that “resting-state” fMRI-based brain connectivity conclusions ma...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2014
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154676/ https://www.ncbi.nlm.nih.gov/pubmed/25188284 http://dx.doi.org/10.1371/journal.pone.0104947 |
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author | Spisák, Tamás Jakab, András Kis, Sándor A. Opposits, Gábor Aranyi, Csaba Berényi, Ervin Emri, Miklós |
author_facet | Spisák, Tamás Jakab, András Kis, Sándor A. Opposits, Gábor Aranyi, Csaba Berényi, Ervin Emri, Miklós |
author_sort | Spisák, Tamás |
collection | PubMed |
description | Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that “resting-state” fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons. |
format | Online Article Text |
id | pubmed-4154676 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2014 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-41546762014-09-08 Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI Spisák, Tamás Jakab, András Kis, Sándor A. Opposits, Gábor Aranyi, Csaba Berényi, Ervin Emri, Miklós PLoS One Research Article Functional Magnetic Resonance Imaging (fMRI) based brain connectivity analysis maps the functional networks of the brain by estimating the degree of synchronous neuronal activity between brain regions. Recent studies have demonstrated that “resting-state” fMRI-based brain connectivity conclusions may be erroneous when motion artifacts have a differential effect on fMRI BOLD signals for between group comparisons. A potential explanation could be that in-scanner displacement, due to rotational components, is not spatially constant in the whole brain. However, this localized nature of motion artifacts is poorly understood and is rarely considered in brain connectivity studies. In this study, we initially demonstrate the local correspondence between head displacement and the changes in the resting-state fMRI BOLD signal. Than, we investigate how connectivity strength is affected by the population-level variation in the spatial pattern of regional displacement. We introduce Regional Displacement Interaction (RDI), a new covariate parameter set for second-level connectivity analysis and demonstrate its effectiveness in reducing motion related confounds in comparisons of groups with different voxel-vise displacement pattern and preprocessed using various nuisance regression methods. The effect of using RDI as second-level covariate is than demonstrated in autism-related group comparisons. The relationship between the proposed method and some of the prevailing subject-level nuisance regression techniques is evaluated. Our results show that, depending on experimental design, treating in-scanner head motion as a global confound may not be appropriate. The degree of displacement is highly variable among various brain regions, both within and between subjects. These regional differences bias correlation-based measures of brain connectivity. The inclusion of the proposed second-level covariate into the analysis successfully reduces artifactual motion-related group differences and preserves real neuronal differences, as demonstrated by the autism-related comparisons. Public Library of Science 2014-09-04 /pmc/articles/PMC4154676/ /pubmed/25188284 http://dx.doi.org/10.1371/journal.pone.0104947 Text en © 2014 Spisák et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Spisák, Tamás Jakab, András Kis, Sándor A. Opposits, Gábor Aranyi, Csaba Berényi, Ervin Emri, Miklós Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title | Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title_full | Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title_fullStr | Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title_full_unstemmed | Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title_short | Voxel-Wise Motion Artifacts in Population-Level Whole-Brain Connectivity Analysis of Resting-State fMRI |
title_sort | voxel-wise motion artifacts in population-level whole-brain connectivity analysis of resting-state fmri |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4154676/ https://www.ncbi.nlm.nih.gov/pubmed/25188284 http://dx.doi.org/10.1371/journal.pone.0104947 |
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