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Integrating functional and diffusion magnetic resonance imaging for analysis of structure-function relationship in the human language network.

Morgan VL, Mishra A, Newton AT, Gore JC, Ding Z - PLoS ONE (2009)

Bottom Line: The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions.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.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University Institute of Imaging Science, Nashville, TN, USA. victoria.morgan@vanderbilt.edu

ABSTRACT

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.

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Related in: MedlinePlus

Group and individual regions of interest.a) Three different regions of interest determined using group activation maps at t>3 cluster size 10 identified in MNI template space with voxel size 4×4×4 mm3; b) The same region of interest masks shown in white with a single subject's regions used for functional connectivity analysis shown within; c) The same subject's regions of interest transformed into individual DTI image space used for DTI tractography with voxel size 2×2×2 mm3. Red = supplementary motor region (SMA), blue = Broca's area (BA), and green = Wernicke's area (WA).
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pone-0006660-g001: Group and individual regions of interest.a) Three different regions of interest determined using group activation maps at t>3 cluster size 10 identified in MNI template space with voxel size 4×4×4 mm3; b) The same region of interest masks shown in white with a single subject's regions used for functional connectivity analysis shown within; c) The same subject's regions of interest transformed into individual DTI image space used for DTI tractography with voxel size 2×2×2 mm3. Red = supplementary motor region (SMA), blue = Broca's area (BA), and green = Wernicke's area (WA).

Mentions: To determine group activation, all of the individual subjects' contrast maps of map1 were entered in a one-sample t-test using SPM5. Activation at the threshold of t>3 with a cluster size of 10 (approximately p<0.001 corrected for multiple comparisons based on AlphaSim software [64]) was arbitrarily chosen to generally determine group activation regions. The regions were then smoothed using a 6 mm FWHM kernel. Regions of interest in Broca's area and supplementary motor area were identified on the group map and these two regions were used as the Broca's region and supplementary motor region group masks. The same method was used with the subjects' map2 to determine a Wernicke's area group mask (see Figure 1a).


Integrating functional and diffusion magnetic resonance imaging for analysis of structure-function relationship in the human language network.

Morgan VL, Mishra A, Newton AT, Gore JC, Ding Z - PLoS ONE (2009)

Group and individual regions of interest.a) Three different regions of interest determined using group activation maps at t>3 cluster size 10 identified in MNI template space with voxel size 4×4×4 mm3; b) The same region of interest masks shown in white with a single subject's regions used for functional connectivity analysis shown within; c) The same subject's regions of interest transformed into individual DTI image space used for DTI tractography with voxel size 2×2×2 mm3. Red = supplementary motor region (SMA), blue = Broca's area (BA), and green = Wernicke's area (WA).
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2721978&req=5

pone-0006660-g001: Group and individual regions of interest.a) Three different regions of interest determined using group activation maps at t>3 cluster size 10 identified in MNI template space with voxel size 4×4×4 mm3; b) The same region of interest masks shown in white with a single subject's regions used for functional connectivity analysis shown within; c) The same subject's regions of interest transformed into individual DTI image space used for DTI tractography with voxel size 2×2×2 mm3. Red = supplementary motor region (SMA), blue = Broca's area (BA), and green = Wernicke's area (WA).
Mentions: To determine group activation, all of the individual subjects' contrast maps of map1 were entered in a one-sample t-test using SPM5. Activation at the threshold of t>3 with a cluster size of 10 (approximately p<0.001 corrected for multiple comparisons based on AlphaSim software [64]) was arbitrarily chosen to generally determine group activation regions. The regions were then smoothed using a 6 mm FWHM kernel. Regions of interest in Broca's area and supplementary motor area were identified on the group map and these two regions were used as the Broca's region and supplementary motor region group masks. The same method was used with the subjects' map2 to determine a Wernicke's area group mask (see Figure 1a).

Bottom Line: The results showed that different language pathways exhibited different structural and functional connectivity, indicating varying levels of inter-dependence in processing across regions.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.

View Article: PubMed Central - PubMed

Affiliation: Vanderbilt University Institute of Imaging Science, Nashville, TN, USA. victoria.morgan@vanderbilt.edu

ABSTRACT

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.

Show MeSH
Related in: MedlinePlus