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Articles, Behavioral/Cognitive

Aging-Resilient Associations between the Arcuate Fasciculus and Vocabulary Knowledge: Microstructure or Morphology?

Susan Teubner-Rhodes, Kenneth I. Vaden Jr., Stephanie L. Cute, Jason D. Yeatman, Robert F. Dougherty and Mark A. Eckert
Journal of Neuroscience 6 July 2016, 36 (27) 7210-7222; https://doi.org/10.1523/JNEUROSCI.4342-15.2016
Susan Teubner-Rhodes
1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina 29425-5500,
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Kenneth I. Vaden Jr.
1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina 29425-5500,
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Stephanie L. Cute
1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina 29425-5500,
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Jason D. Yeatman
2Institute for Learning and Brain Sciences and Department of Speech and Hearing Sciences, University of Washington, Seattle, Washington 98195-7988, and
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Robert F. Dougherty
3Center for Cognitive and Neurobiological Imaging, Stanford University, Stanford, California 94305-2130
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Mark A. Eckert
1Department of Otolaryngology-Head and Neck Surgery, Medical University of South Carolina, Charleston, South Carolina 29425-5500,
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  • Figure 1.
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    Figure 1.

    Correlations of education (top) and age (bottom) with vocabulary (red, left) and processing speed (blue, right). M, Male; F, female. Gray shading represents the 95% CI. Processing speed was measured by performance on the Connections Simple task such that higher values indicate faster processing speed. A, B, Education was significantly positively correlated with Vocabulary Knowledge but not processing speed. C, D, Age in years did not predict Vocabulary Knowledge but was significantly negatively correlated with processing speed.

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    Figure 2.

    Tract renderings of the left arcuate fasciculus from selected participants with (A) low Vocabulary Knowledge (bottom quartile) and low or high tract volume and (B) high Vocabulary Knowledge (top quartile) and normal tract volume. F, Female; M, male. Yellow area in the posterior segment of the tract represents nodes 73–88 where FA was significantly positively correlated with Vocabulary Knowledge (pFWE < 0.05). Some fibers do not appear to pass through the ROIs for individual participants; this is because AFQ's fiber selection algorithm uses a smoothed ROI to correct for small errors in coregistration from MNI space to the participant's native space.

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    Figure 3.

    Correlations with diffusion metrics in the (A, B) left arcuate fasciculus and (C) left frontoparietal SLF by node position, and corresponding fiber renderings from an example participant. FP SLF, Frontoparietal superior longitudinal fasciculus. Color represents the r value of the correlation at each node position. Shaded gray area represents nodes where the permutation-corrected significance level was p < 0.05, which are depicted in color on the rendered fibers. y-axis indicates the mean value of the diffusion metric at each node represented by the x-axis. Error bars indicate SD of the mean diffusion metric. A, FA was significantly positively correlated with Vocabulary Knowledge in nodes 73–88 of the left arcuate fasciculus. B, MD was significantly negatively correlated with processing speed in nodes 9–11 and 40–85 of the left arcuate fasciculus. C, MD was significantly negatively correlated with processing speed in nodes 1–11 and 94–100 of the left frontoparietal SLF. The spread of the fibers at the posterior end of the tract is consistent with prior work (Catani et al., 2005).

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    Figure 4.

    Correlations of diffusion metrics averaged across nodes in the arcuate fasciculus and frontoparietal SLF with vocabulary (red, left) and processing speed (blue, right). M, Male; F, female; FP SLF, frontoparietal superior longitudinal fasciculus. Gray shading represents the 95% CI. Processing speed was measured by performance on the Connections Simple task such that higher values indicate faster processing. A, B, Left arcuate fasciculus FA (nodes 73–88) was significantly positively correlated with Vocabulary Knowledge but not processing speed. C, D, Left arcuate fasciculus MD (nodes 40–85) did not predict Vocabulary Knowledge but was significantly negatively correlated with processing speed. The correlation with processing speed in D was significantly stronger in males than females (Z = −2.04, p < 0.05; males: r = −0.61, p < 0.001; females: r = −0.28, p < 0.05). E, F, Left frontoparietal SLF MD (nodes 1–11) did not predict Vocabulary Knowledge but was significantly negatively correlated with processing speed. The correlation with processing speed in F was significantly stronger in males than females (Z = −2.17, p < 0.05; males: r = −0.57, p < 0.001; females: r = −0.20, p = 0.13).

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    Figure 5.

    Correlations between age, T1w/T2w, and diffusion metrics averaged across nodes in the arcuate fasciculus and frontoparietal SLF. M, Male; F, female; FP SLF, frontoparietal superior longitudinal fasciculus. Gray shading represents 95% CI. A, B, Age was significantly negatively correlated with T1w/T2w in both the left arcuate (nodes 73–88) and left frontoparietal SLF (1–11). C, D, Age was not correlated with FA in the left arcuate (nodes 73–88) but was significantly positively correlated with MD in the left frontoparietal SLF (nodes 1–11). E, F, T1w/T2w was not correlated with FA in the left arcuate (nodes 73–88) but was significantly positively correlated with MD in the left frontoparietal SLF (nodes 1–11).

Tables

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    Table 1.

    Correlations of education and age with vocabulary and processing speed measuresa

    Vocabulary KnowledgePicture VocabularyConnections Simple
    Simple correlations
        Education0.54***0.45***0.05
        Age0.040.16−0.64***
        Age20.100.020.02
    Partial correlations controlling for education
        Education———
        Age0.050.18−0.64***
        Age2−0.03−0.100.00
    • ↵aSimple correlations with Z-transformed scores on the cognitive metrics and partial correlations after controlling for education. Age2, Residuals of age-squared after regressing out actual age in years. Bootstrap (1000) CIs for significant correlations: Education with Vocabulary Knowledge [0.39, 0.67], Picture Vocabulary [0.27, 0.59]; Age with Connections Simple [−0.75, −0.53].

    • ↵***p < 0.001.

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    Table 2.

    Diffusion correlations with language and processing speed measuresa

    Vocabulary KnowledgePicture VocabularyConnections Simple
    L arcuate fasciculus FA (nodes 73–88)0.38***b0.31**0.16
    L arcuate fasciculus MD (nodes 40–85)−0.18−0.14−0.41***b
    R arcuate fasciculus MD (nodes 51–75)−0.10−0.08−0.44***b
    L frontoparietal SLF MD (nodes 1–11)−0.06−0.10−0.28**b
    R frontoparietal SLF MD (nodes 84–100)−0.07−0.04−0.31**b
    • ↵aCorrelations of diffusion metrics averaged across tract segments with Z-transformed scores on the cognitive metrics. L, Left; R, right. Bootstrap (1000) CIs for significant correlations: L arcuate FA (nodes 73–88) with Vocabulary Knowledge [0.17, 0.55] and Picture Vocabulary [0.12, 0.48]; L arcuate MD (nodes 40–85) with Connections Simple [−0.57, −0.23]; and R arcuate MD (nodes 51–75) with Connections Simple [−0.60, −0.25].

    • ↵bThe nodes in the defined region exhibited significant correlations in permutation testing across the entire tract.

    • ↵**p < 0.01;

    • ↵***p < 0.001.

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    Table 3.

    Correlations of age, the T1w/T2w ratio, and diffusion metrics in regions of interesta

    123
    L arcuate fasciculus (nodes 73–88)
        1. Age—
        2. T1w/T2w ratio−0.64***—
        3. FA0.050.02—
    L arcuate fasciculus (nodes 40–85)
        1. Age—
        2. T1w/T2w ratio−0.67***—
        3. MD0.38***−0.45***—
    R arcuate fasciculus (nodes 51–75)
        1. Age—
        2. T1w/T2w ratio−0.60***—
        3. MD0.32**−0.43***—
    L frontoparietal SLF (nodes 1–11)
        1. Age—
        2. T1w/T2w ratio−0.69***—
        3. MD0.30**−0.39***—
    R frontoparietal SLF (nodes 84–100)
        1. Age—
        2. T1w/T2w ratio−0.74***—
        3. MD0.29**−0.33***—
    • ↵aT1w/T2w ratio and diffusion metrics were averaged across the relevant nodes. L, Left; R, right.

    • ↵**p < 0.01;

    • ↵***p < 0.001.

    • View popup
    Table 4.

    Mean (SD) of Vocabulary Knowledge, FA, intracranial volume, and age by left arcuate fasciculus volume classification

    NormalHigh VolumeLow Volume
    Vocabulary Knowledgea64.70 (7.67)58.44 (9.25)*55.43 (8.22)*
    FA0.51 (0.07)0.48 (0.05)0.45 (0.06)*
    Intracranial volume1492.72 (185.58)1538.73 (176.69)1271.57 (112.15)**
    Age55.24 (16.55)51.32 (22.45)45.38 (18.17)
    • ↵aVocabulary Knowledge is reported as raw scores.

    • ↵*p < 0.05;

    • ↵**p < 0.01; difference from normal group.

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The Journal of Neuroscience: 36 (27)
Journal of Neuroscience
Vol. 36, Issue 27
6 Jul 2016
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Aging-Resilient Associations between the Arcuate Fasciculus and Vocabulary Knowledge: Microstructure or Morphology?
Susan Teubner-Rhodes, Kenneth I. Vaden Jr., Stephanie L. Cute, Jason D. Yeatman, Robert F. Dougherty, Mark A. Eckert
Journal of Neuroscience 6 July 2016, 36 (27) 7210-7222; DOI: 10.1523/JNEUROSCI.4342-15.2016

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Aging-Resilient Associations between the Arcuate Fasciculus and Vocabulary Knowledge: Microstructure or Morphology?
Susan Teubner-Rhodes, Kenneth I. Vaden Jr., Stephanie L. Cute, Jason D. Yeatman, Robert F. Dougherty, Mark A. Eckert
Journal of Neuroscience 6 July 2016, 36 (27) 7210-7222; DOI: 10.1523/JNEUROSCI.4342-15.2016
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Keywords

  • aging
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