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Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network
BACKGROUND: The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted...
Autores principales: | , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2009
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2721978/ https://www.ncbi.nlm.nih.gov/pubmed/19684850 http://dx.doi.org/10.1371/journal.pone.0006660 |
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author | Morgan, Victoria L. Mishra, Arabinda Newton, Allen T. Gore, John C. Ding, Zhaohua |
author_facet | Morgan, Victoria L. Mishra, Arabinda Newton, Allen T. Gore, John C. Ding, Zhaohua |
author_sort | Morgan, Victoria L. |
collection | PubMed |
description | BACKGROUND: The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI. METHODOLOGY/PRINCIPAL FINDINGS: Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. CONCLUSIONS/SIGNIFICANCE: These findings suggest that structure-function relations in the human language circuits may involve a number of confounding factors that need to be addressed. Nevertheless, the insights gained from this work offers a useful guidance for continued studies that may provide a non-invasive means to evaluate brain network integrity in vivo for use in diagnosing and determining disease progression and recovery. |
format | Text |
id | pubmed-2721978 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2009 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-27219782009-08-17 Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network Morgan, Victoria L. Mishra, Arabinda Newton, Allen T. Gore, John C. Ding, Zhaohua PLoS One Research Article BACKGROUND: The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in characterizing the relationship between these measures in the distributed neural networks of the brain. In this study, we attempted an integration of structural and functional analyses of the human language circuits, including Wernicke's (WA), Broca's (BA) and supplementary motor area (SMA), using a combination of blood oxygen level dependent (BOLD) and diffusion tensor MRI. METHODOLOGY/PRINCIPAL FINDINGS: Functional connectivity was measured by low frequency inter-regional correlations of BOLD MRI signals acquired in a resting steady-state, and structural connectivity was measured by using adaptive fiber tracking with diffusion tensor MRI data. The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions. Along the path between BA and SMA, the fibers tracked generally formed a single bundle and the mean radius of the bundle was positively correlated with functional connectivity. However, fractional anisotropy was found not to be correlated with functional connectivity along paths connecting either BA and SMA or BA and WA. CONCLUSIONS/SIGNIFICANCE: These findings suggest that structure-function relations in the human language circuits may involve a number of confounding factors that need to be addressed. Nevertheless, the insights gained from this work offers a useful guidance for continued studies that may provide a non-invasive means to evaluate brain network integrity in vivo for use in diagnosing and determining disease progression and recovery. Public Library of Science 2009-08-17 /pmc/articles/PMC2721978/ /pubmed/19684850 http://dx.doi.org/10.1371/journal.pone.0006660 Text en Morgan 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 Morgan, Victoria L. Mishra, Arabinda Newton, Allen T. Gore, John C. Ding, Zhaohua Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title_full | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title_fullStr | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title_full_unstemmed | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title_short | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
title_sort | integrating functional and diffusion magnetic resonance imaging for analysis of structure-function relationship in the human language network |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2721978/ https://www.ncbi.nlm.nih.gov/pubmed/19684850 http://dx.doi.org/10.1371/journal.pone.0006660 |
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