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Articles, Behavioral/Cognitive

Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities

Tanya M. Evans, John Kochalka, Tricia J. Ngoon, Sarah S. Wu, Shaozheng Qin, Christian Battista and Vinod Menon
Journal of Neuroscience 19 August 2015, 35 (33) 11743-11750; DOI: https://doi.org/10.1523/JNEUROSCI.0216-15.2015
Tanya M. Evans
1Department of Psychiatry and Behavioral Sciences,
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John Kochalka
1Department of Psychiatry and Behavioral Sciences,
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Tricia J. Ngoon
1Department of Psychiatry and Behavioral Sciences,
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Sarah S. Wu
1Department of Psychiatry and Behavioral Sciences,
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Shaozheng Qin
1Department of Psychiatry and Behavioral Sciences,
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Christian Battista
1Department of Psychiatry and Behavioral Sciences,
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Vinod Menon
1Department of Psychiatry and Behavioral Sciences,
2Department of Neurology and Neurological Sciences,
3Stanford Neuroscience Institute,
4Symbolic Systems Program, Stanford University School of Medicine, Stanford, California 94305
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  • Figure 1.
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    Figure 1.

    Growth curves for individual children's (n = 43) standardized score on the WIAT-II Numerical Operations subtest. Lines depict linear regression of Numerical Operations standardized score versus age across longitudinal visits for each child. Children who made gains relative to their peers over time are plotted in green. Those who declined or remained stable are plotted in red. The annualized change (slopes of individual regression lines) is used in subsequent regression and confirmatory cross-validation analyses.

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    Figure 2.

    a–d , Structural integrity in regions within ( a ) VTOC (FG), ( b ) PPC (IPS), ( c ) PFC [DLPFC, VLPFC, and pre/primary motor cortex (PMC)], and ( d ) visual cortex (cuneus) predicts longitudinal gains in numerical abilities. Children with higher volume in these regions at age 8 had steeper growth curves from childhood to adolescence. GMV, Gray matter volume.

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    Figure 3.

    Intrinsic functional connectivity of brain regions identified in the structural MRI analysis predicts gains in numerical abilities. a , b , The FG connectivity map had the most predictive voxels, displayed here in ( a ) an overlay of all functional connectivity maps and ( b ) quantified in a bar graph. c , Individual connectivity maps of regions within the VTOC, PPC, PFC, and visual cortex are displayed with the seed shown in pink. ROIs for functional connectivity analyses were generated by placing 6 mm spheres at the cluster peaks (most-significant voxels) from the VBM-based predictive analysis. PMC, Premotor cortex.

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    Table 1.

    Brain areas where structural integrity predicts longitudinal growth in numerical abilities a

    RegionBrodmann's areaNumber of voxels (mm3)Peak Z-scorePeak MNI coordinates (mm)Math ReasoningWord ReadingReading ComprehensionWorking memory
    xyz
    VTOC
        Left FG37973.62−36−58−12 p = 0.14, r = 0.13 p = 0.99, r = −0.34 p = 0.14, r = 0.12 p = 0.84, r = −0.2
    PPC
        Left IPS391613.78−42−4054 p = 0.78, r = −0.19 p = 0.93, r = −0.24 p = 0.67, r = −0.14 p = 0.98, r = −0.29
    PFC
        Left DLPFC462153.97−524113 p = 0.54, r = −0.09 p = 0.60, r = −0.11 p = 0.84, r = −0.21 p = 0.44, r = −0.04
        Left DLPFC45923.5−40276 p = 0.97, r = −0.27 p = 0.52, r = −0.07 p = 0.92, r = −0.24 p = 0.74, r = −0.18
        Left VLPFC105164.10−2745−8 p = 0.22, r = −0.07 p = 0.50, r = −0.06 p = 0.84, r = −0.21 p = 0.23, r = 0.07
        Right pre/primary motor cortex66984.1434846 p = 0.007, r = 0.34 p = 0.32, r = 0.01 p = 0.05, r = 0.22 p = 0.67, r = −0.14
    Visual cortex
        Right cuneus175514.2718−9613 p = 0.25, r = −0.05 p = 0.45, r = −0.05 p = 0.11, r = 0.16 p = 0.95, r = −0.27
        Right cuneus181163.7922−9425 p = 0.08, r = −0.55 p = 0.85, r = −0.19 p = 0.93, r = −0.24 p = 0.93, r = −0.24
    • ↵ a Clusters in which gray matter volume is predictive of numerical gains. Math and reading measures are subtests from the WIAT-II. The Working Memory Test Battery for Children was used to measure working memory.

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    Table 2.

    Brain regions in which intrinsic functional connectivity with the FG is predictive of gains in numerical skills

    RegionBrodmann's areaNumber of voxels (mm3)Peak Z-scorePeak MNI coordinates (mm)
    xyz
    VTOC
        Right FG197523.7724−72−2
    PPC
        Bilateral precuneus71413.624−5446
    PFC
        Left DLPFC461063.39−382836
        Right DLPFC441675.3140826
    Visual cortex
        Right cuneus183634.0816−8828
    Temporal cortex
        Right anterior temporal cortex214043.64486−20
        Left anterior temporal cortex212083.29−502−24
    Subcortical
        Right basal ganglia (caudate)1163.581086
        Medial
        Mid-cingulate232715.252−836
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The Journal of Neuroscience: 35 (33)
Journal of Neuroscience
Vol. 35, Issue 33
19 Aug 2015
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Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities
Tanya M. Evans, John Kochalka, Tricia J. Ngoon, Sarah S. Wu, Shaozheng Qin, Christian Battista, Vinod Menon
Journal of Neuroscience 19 August 2015, 35 (33) 11743-11750; DOI: 10.1523/JNEUROSCI.0216-15.2015

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Brain Structural Integrity and Intrinsic Functional Connectivity Forecast 6 Year Longitudinal Growth in Children's Numerical Abilities
Tanya M. Evans, John Kochalka, Tricia J. Ngoon, Sarah S. Wu, Shaozheng Qin, Christian Battista, Vinod Menon
Journal of Neuroscience 19 August 2015, 35 (33) 11743-11750; DOI: 10.1523/JNEUROSCI.0216-15.2015
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Keywords

  • cognition
  • connectivity
  • development
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  • pediatric
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