Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network
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 integrat...
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| Published in | PloS one Vol. 4; no. 8; p. e6660 |
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| Main Authors | , , , , |
| Format | Journal Article |
| Language | English |
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United States
Public Library of Science
17.08.2009
Public Library of Science (PLoS) |
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| Abstract | 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.
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.
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. |
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| AbstractList | 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.BACKGROUNDThe 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.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.METHODOLOGY/PRINCIPAL FINDINGSFunctional 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.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.CONCLUSIONS/SIGNIFICANCEThese 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. 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. 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. 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. 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. 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. 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. 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. 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. |
| Audience | Academic |
| Author | Morgan, Victoria L. Mishra, Arabinda Newton, Allen T. Gore, John C. Ding, Zhaohua |
| AuthorAffiliation | 4 Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee, United States of America 1 Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, United States of America 3 Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America University of Regensburg, Germany 2 Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America |
| AuthorAffiliation_xml | – name: 3 Department of Electrical Engineering and Computer Science, Vanderbilt University, Nashville, Tennessee, United States of America – name: 2 Department of Biomedical Engineering, Vanderbilt University, Nashville, Tennessee, United States of America – name: University of Regensburg, Germany – name: 4 Chemical and Physical Biology Program, Vanderbilt University, Nashville, Tennessee, United States of America – name: 1 Vanderbilt University Institute of Imaging Science, Nashville, Tennessee, United States of America |
| Author_xml | – sequence: 1 givenname: Victoria L. surname: Morgan fullname: Morgan, Victoria L. – sequence: 2 givenname: Arabinda surname: Mishra fullname: Mishra, Arabinda – sequence: 3 givenname: Allen T. surname: Newton fullname: Newton, Allen T. – sequence: 4 givenname: John C. surname: Gore fullname: Gore, John C. – sequence: 5 givenname: Zhaohua surname: Ding fullname: Ding, Zhaohua |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/19684850$$D View this record in MEDLINE/PubMed |
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| ContentType | Journal Article |
| Copyright | COPYRIGHT 2009 Public Library of Science 2009 Morgan et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. Morgan et al. 2009 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Conceived and designed the experiments: VLM ZD. Performed the experiments: VLM ZD. Analyzed the data: VLM AM ATN ZD. Contributed reagents/materials/analysis tools: VLM AM ATN ZD. Wrote the paper: VLM ZD. Interpretation and critical revision of manuscript: JCG. |
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| Snippet | The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing interest in... Background The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing... BACKGROUND:The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing... Background The capabilities of magnetic resonance imaging (MRI) to measure structural and functional connectivity in the human brain have motivated growing... |
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| SubjectTerms | Adaptive structures Adult Anisotropy Aphasia Artificial neural networks Biomedical engineering Brain Circuits Computer engineering Correlation analysis Diffusion Diffusion Magnetic Resonance Imaging - methods Female Fibers Functional magnetic resonance imaging Human subjects Humans In vivo methods and tests Language Magnetic resonance Magnetic resonance imaging Male Medical imaging equipment Neural networks Neuroimaging Neuroscience/Cognitive Neuroscience Neuroscience/Sensory Systems Neurosciences NMR Nuclear magnetic resonance Oxygen Radiology and Medical Imaging/Magnetic Resonance Imaging Resonance Science Structure-function relationships Studies Supplementary motor area Tracking Trends |
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| Title | Integrating Functional and Diffusion Magnetic Resonance Imaging for Analysis of Structure-Function Relationship in the Human Language Network |
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