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Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity
Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-le...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MIT Press
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370491/ https://www.ncbi.nlm.nih.gov/pubmed/30793090 http://dx.doi.org/10.1162/netn_a_00071 |
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author | Lydon-Staley, David M. Ciric, Rastko Satterthwaite, Theodore D. Bassett, Danielle S. |
author_facet | Lydon-Staley, David M. Ciric, Rastko Satterthwaite, Theodore D. Bassett, Danielle S. |
author_sort | Lydon-Staley, David M. |
collection | PubMed |
description | Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8–22 years). Each strategy was evaluated according to a number of benchmarks, including (a) the residual association between participant motion and edge dispersion, (b) distance-dependent effects of motion on edge dispersion, (c) the degree to which functional subnetworks could be identified by multilayer modularity maximization, and (d) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies. |
format | Online Article Text |
id | pubmed-6370491 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MIT Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-63704912019-02-21 Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity Lydon-Staley, David M. Ciric, Rastko Satterthwaite, Theodore D. Bassett, Danielle S. Netw Neurosci Research Articles Dynamic functional connectivity reflects the spatiotemporal organization of spontaneous brain activity in health and disease. Dynamic functional connectivity may be susceptible to artifacts induced by participant motion. This report provides a systematic evaluation of 12 commonly used participant-level confound regression strategies designed to mitigate the effects of micromovements in a sample of 393 youths (ages 8–22 years). Each strategy was evaluated according to a number of benchmarks, including (a) the residual association between participant motion and edge dispersion, (b) distance-dependent effects of motion on edge dispersion, (c) the degree to which functional subnetworks could be identified by multilayer modularity maximization, and (d) measures of module reconfiguration, including node flexibility and node promiscuity. Results indicate variability in the effectiveness of the evaluated pipelines across benchmarks. Methods that included global signal regression were the most consistently effective de-noising strategies. MIT Press 2019-02-01 /pmc/articles/PMC6370491/ /pubmed/30793090 http://dx.doi.org/10.1162/netn_a_00071 Text en © 2018 Massachusetts Institute of Technology This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. For a full description of the license, please visit https://creativecommons.org/licenses/by/4.0/legalcode. |
spellingShingle | Research Articles Lydon-Staley, David M. Ciric, Rastko Satterthwaite, Theodore D. Bassett, Danielle S. Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title | Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title_full | Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title_fullStr | Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title_full_unstemmed | Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title_short | Evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
title_sort | evaluation of confound regression strategies for the mitigation of micromovement artifact in studies of dynamic resting-state functional connectivity and multilayer network modularity |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6370491/ https://www.ncbi.nlm.nih.gov/pubmed/30793090 http://dx.doi.org/10.1162/netn_a_00071 |
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