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Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects

With the increasing use of functional brain network properties as markers of brain disorders, efficient visualization and evaluation methods have become essential. Eigenvector centrality mapping (ECM) of functional MRI (fMRI) data enables the representation of per-node graph theoretical measures as...

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Autor principal: Wink, Alle Meije
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609310/
https://www.ncbi.nlm.nih.gov/pubmed/31316335
http://dx.doi.org/10.3389/fnins.2019.00648
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author Wink, Alle Meije
author_facet Wink, Alle Meije
author_sort Wink, Alle Meije
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description With the increasing use of functional brain network properties as markers of brain disorders, efficient visualization and evaluation methods have become essential. Eigenvector centrality mapping (ECM) of functional MRI (fMRI) data enables the representation of per-node graph theoretical measures as brain maps. This paper studies the use of centrality dynamics for measuring group differences in imaging studies. Imaging data were used from a publicly available imaging study, which included resting fMRI data. After warping the images to a standard space and masking cortical regions, ECM were computed in a sliding window. The dual regression method was used to identify dynamic centrality differences inside well-known resting-state networks between gender and age groups. Gender-related differences were found in the medial and lateral visual, motor, default mode, and executive control RSN, where male subjects had more consistent centrality variations within the network. Age-related differences between the youngest and oldest subjects, based on a median split, were found in the medial visual, executive control and left frontoparietal networks, where younger subjects had more consistent centrality variations within the network. Our findings show that centrality dynamics can be used to identify between-group functional brain network centrality differences, and that age and gender distributions studies need to be taken into account in functional imaging studies.
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spelling pubmed-66093102019-07-17 Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects Wink, Alle Meije Front Neurosci Neuroscience With the increasing use of functional brain network properties as markers of brain disorders, efficient visualization and evaluation methods have become essential. Eigenvector centrality mapping (ECM) of functional MRI (fMRI) data enables the representation of per-node graph theoretical measures as brain maps. This paper studies the use of centrality dynamics for measuring group differences in imaging studies. Imaging data were used from a publicly available imaging study, which included resting fMRI data. After warping the images to a standard space and masking cortical regions, ECM were computed in a sliding window. The dual regression method was used to identify dynamic centrality differences inside well-known resting-state networks between gender and age groups. Gender-related differences were found in the medial and lateral visual, motor, default mode, and executive control RSN, where male subjects had more consistent centrality variations within the network. Age-related differences between the youngest and oldest subjects, based on a median split, were found in the medial visual, executive control and left frontoparietal networks, where younger subjects had more consistent centrality variations within the network. Our findings show that centrality dynamics can be used to identify between-group functional brain network centrality differences, and that age and gender distributions studies need to be taken into account in functional imaging studies. Frontiers Media S.A. 2019-06-27 /pmc/articles/PMC6609310/ /pubmed/31316335 http://dx.doi.org/10.3389/fnins.2019.00648 Text en Copyright © 2019 Wink. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Wink, Alle Meije
Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title_full Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title_fullStr Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title_full_unstemmed Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title_short Eigenvector Centrality Dynamics From Resting-State fMRI: Gender and Age Differences in Healthy Subjects
title_sort eigenvector centrality dynamics from resting-state fmri: gender and age differences in healthy subjects
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6609310/
https://www.ncbi.nlm.nih.gov/pubmed/31316335
http://dx.doi.org/10.3389/fnins.2019.00648
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