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Resting-State Brain Organization Revealed by Functional Covariance Networks
BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale netw...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3236756/ https://www.ncbi.nlm.nih.gov/pubmed/22174905 http://dx.doi.org/10.1371/journal.pone.0028817 |
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author | Zhang, Zhiqiang Liao, Wei Zuo, Xi-Nian Wang, Zhengge Yuan, Cuiping Jiao, Qing Chen, Huafu Biswal, Bharat B. Lu, Guangming Liu, Yijun |
author_facet | Zhang, Zhiqiang Liao, Wei Zuo, Xi-Nian Wang, Zhengge Yuan, Cuiping Jiao, Qing Chen, Huafu Biswal, Bharat B. Lu, Guangming Liu, Yijun |
author_sort | Zhang, Zhiqiang |
collection | PubMed |
description | BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale. |
format | Online Article Text |
id | pubmed-3236756 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-32367562011-12-15 Resting-State Brain Organization Revealed by Functional Covariance Networks Zhang, Zhiqiang Liao, Wei Zuo, Xi-Nian Wang, Zhengge Yuan, Cuiping Jiao, Qing Chen, Huafu Biswal, Bharat B. Lu, Guangming Liu, Yijun PLoS One Research Article BACKGROUND: Brain network studies using techniques of intrinsic connectivity network based on fMRI time series (TS-ICN) and structural covariance network (SCN) have mapped out functional and structural organization of human brain at respective time scales. However, there lacks a meso-time-scale network to bridge the ICN and SCN and get insights of brain functional organization. METHODOLOGY AND PRINCIPAL FINDINGS: We proposed a functional covariance network (FCN) method by measuring the covariance of amplitude of low-frequency fluctuations (ALFF) in BOLD signals across subjects, and compared the patterns of ALFF-FCNs with the TS-ICNs and SCNs by mapping the brain networks of default network, task-positive network and sensory networks. We demonstrated large overlap among FCNs, ICNs and SCNs and modular nature in FCNs and ICNs by using conjunctional analysis. Most interestingly, FCN analysis showed a network dichotomy consisting of anti-correlated high-level cognitive system and low-level perceptive system, which is a novel finding different from the ICN dichotomy consisting of the default-mode network and the task-positive network. CONCLUSION: The current study proposed an ALFF-FCN approach to measure the interregional correlation of brain activity responding to short periods of state, and revealed novel organization patterns of resting-state brain activity from an intermediate time scale. Public Library of Science 2011-12-13 /pmc/articles/PMC3236756/ /pubmed/22174905 http://dx.doi.org/10.1371/journal.pone.0028817 Text en Zhang 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 Zhang, Zhiqiang Liao, Wei Zuo, Xi-Nian Wang, Zhengge Yuan, Cuiping Jiao, Qing Chen, Huafu Biswal, Bharat B. Lu, Guangming Liu, Yijun Resting-State Brain Organization Revealed by Functional Covariance Networks |
title | Resting-State Brain Organization Revealed by Functional Covariance Networks |
title_full | Resting-State Brain Organization Revealed by Functional Covariance Networks |
title_fullStr | Resting-State Brain Organization Revealed by Functional Covariance Networks |
title_full_unstemmed | Resting-State Brain Organization Revealed by Functional Covariance Networks |
title_short | Resting-State Brain Organization Revealed by Functional Covariance Networks |
title_sort | resting-state brain organization revealed by functional covariance networks |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3236756/ https://www.ncbi.nlm.nih.gov/pubmed/22174905 http://dx.doi.org/10.1371/journal.pone.0028817 |
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