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Articles, Behavioral/Systems/Cognitive

Heritability of Working Memory Brain Activation

Gabriëlla A. M. Blokland, Katie L. McMahon, Paul M. Thompson, Nicholas G. Martin, Greig I. de Zubicaray and Margaret J. Wright
Journal of Neuroscience 27 July 2011, 31 (30) 10882-10890; DOI: https://doi.org/10.1523/JNEUROSCI.5334-10.2011
Gabriëlla A. M. Blokland
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Katie L. McMahon
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Paul M. Thompson
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Nicholas G. Martin
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Greig I. de Zubicaray
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Margaret J. Wright
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  • Figure 1.
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    Figure 1.

    Observed and expected sampling distributions for genetic and environmental parameters. h2 observed = [2*(rMZ − rDZ)] and c2 observed = [(2*rDZ) − rMZ] (Falconer and Mackay, 1996). h2 and c2 expected are normal distributions with a mean of zero and an expected sampling variance estimated as [4*((1 − rMZ2)2 /m + (1 − rDZ2)2 /n)] for h2 expected, and [(4*(1 − rDZ2)2)/n + ((1 − rMZ2)2/m)] for c2 expected, where n and m refer to the numbers of DZ and MZ twin pairs, respectively, and rMZ and rDZ are set to zero under the null hypothesis of no heritability and no common environmental influence (Visscher, 2004).

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    Figure 2.

    Group activation, twin correlations, and test-retest reliability. A–C, Group random-effects analysis for the 2-back >0-back t contrast (p < 0.05, FWE corrected) (A), maximum likelihood MZ and DZ twin correlations (B), and test-retest correlations within the group activation mask (C). Confidence intervals for twin and test-retest correlations are available in the supplemental material (available at www.jneurosci.org as supplemental material). Statistical maps are rendered on the Freesurfer inflated brain (CorTechs Labs) (Fischl et al., 1999) using the SPM SurfRend Toolbox (http://spmsurfrend.sourceforge.net; authored by Itamar Kahn, Universität Freiburg, Freiburg, Germany) and NeuroLens (Neurovascular Imaging Laboratory, L'Unité de Neuroimagerie Fonctionnelle, Montréal, QC, Canada), separately for lateral and medial views in the left and right hemispheres.

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    Figure 3.

    Variance component estimates for n-back task-related brain activation. A, Percentages of variance explained by genetic (a2) and unique environmental factors (e2). B, Probability map for a2, indicating which genetic estimates were significant after height (p < 0.05) and cluster (>147 voxels) thresholding.

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    Figure 4.

    Covariate effect estimates for sex, age, 2-back performance accuracy, and FIQ. A, Standardized regression coefficients (β values) obtained from multiple regression of task-related activation on sex, age, 2-back performance accuracy, and FIQ in Mx (Neale et al., 2002). Positive effects (i.e., greater activation in males, in older participants, and in participants who performed better on the n-back task or with higher FIQ) are represented by hot colors and negative effects (i.e., greater activation in females, in younger participants, and in participants who performed worse on the n-back task or with lower FIQ) are represented by cold colors. B, Height-thresholded (p < 0.05) and cluster-thresholded (>147 voxels) p value maps corresponding to the regression coefficient maps of sex, age, 2-back performance accuracy, and FIQ.

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    Table 1.

    Demographic characteristics of the twin samplea

    (mean ± SD)Females (n = 199 individuals)Males (n = 120 individuals)Total (n = 319 individuals)
    Age (years)23.5 ± 1.823.7 ± 1.923.6 ± 1.8
    FIQb113.4 ± 10.9117.5 ± 12.9**114.9 ± 11.9
    Gestational age (weeks)c37.9 ± 2.838.1 ± 2.738.0 ± 2.7
    Birth weight (g)2575.4 ± 477.42715.9 ± 525.4*2628.5 ± 500.0
    Socioeconomic index52.6 ± 24.254.7 ± 24.653.4 ± 24.3
    • ↵aThe sample included 75 MZ pairs, 66 DZ pairs, and 37 unpaired twins. Although unpaired MZ and DZ twins did not contribute to the estimation of the genetic and environmental parameters, they did contribute to the estimation of mean and variance effects (i.e. they allowed a more accurate estimation of phenotypic correlations and phenotypic effects).

    • ↵bFIQ was measured using five subtests from the Multidimensional Aptitude Battery (Jackson, 1984), as close as possible to the twins' 16th birthday. The observed higher mean is likely due to the fact that the MAB test was created and normalized for Canadian samples, and therefore results on this test may differ when used in a different country. In addition, the presence of an ascertainment bias cannot be excluded, as more intelligent and often more highly educated people tend to volunteer for these studies more frequently. However, the higher FIQ mean does not affect the representativeness of this sample because FIQ follows a normal distribution, with scores ranging from 85 to 146, thus showing good variability.

    • ↵cGestational age, birth weight, and parental socioeconomic status (McMillan et al., 2009) were obtained from parental reports, either when the twins were 12 or 16 years. There were no significant mean or variance differences between co-twins or by zygosity. Males had slightly higher FIQ (d = 0.34, p < 0.01) and birth weight (d = 0.28, p < 0.05) than females.

    • ↵*p < 0.05;

    • ↵**p < 0.01.

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    Table 2.

    Twin correlations and variance component estimates for task performance

    PhenotypesTwin correlations (95% CI)Model fit: −2LL (Δχ2 (Δdf), p value)ACE estimates (%) full ACE model (95% CI)ACE estimates (%) best fitting model (95% CI)
    MZDZACEAECEEACEAE
    0-Back
        Accuracy (%)0.33* (0.13, 0.50)0.08 (0.00, 0.31)
        RT (ms)0.54* (0.38, 0.66)0.19 (0.00, 0.42)3464.943464.94 (0.00 (1), ns)3471.29 (6.34 (1), <0.05)3497.69 (32.75 (2), <0.001)53 (14, 66)0 (0, 33)47 (34, 63)53 (37, 66)47 (34, 63)
    2-Back
        Accuracy (%)0.55* (0.38, 0.68)0.34* (0.12, 0.53)2732.062732.42 (0.36 (1), ns)2734.96 (2.90 (1), ns)2765.43 (33.37 (2), <0.001)42 (0, 68)13 (0, 52)45 (32, 62)57 (41, 69)44 (31, 59)
        RT (ms)0.29* (0.11, 0.44)0.20 (0.00, 0.35)3895.923895.92 (0.00 (1), ns)3896.52 (0.60 (1), ns)3907.90 (11.98 (2), <0.01)34 (0, 50)0.00 (0, 34)66 (50, 87)34 (15, 50)66 (50, 85)
        FIQ0.77* (0.67, 0.84)0.52* (0.32, 0.66)2371.022373.00 (1.98 (1), ns)2380.60 (9.58 (1), <0.01)2455.34 (84.32 (2), <0.001)50 (18, 82)27 (0, 56)23 (16, 33)78 (68, 84)22 (16, 32)
    • Maximum-likelihood twin correlations, univariate genetic model fitting results, and variance component estimates from the full ACE and best fitting models for the performance measures and FIQ. The best fitting model is shown in bold. Nested submodels are compared to the full ACE model by testing whether dropping a parameter resulted in a significant increase in the goodness-of-fit χ2 (the difference in −2 times the log likelihood (−2LL) of a model and a nested submodel follows a χ2 distribution with degrees of freedom equal to the difference in the number of parameters). Estimates are corrected for age and sex; assumption testing supported homogeneity of means and variances across birth order and zygosity. −2LL = minus 2*log-likelihood; Δχ2 = change in χ2; Δdf = change in degrees of freedom; CI, confidence interval; ns, not significant.

    • ↵*p < 0.05.

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The Journal of Neuroscience: 31 (30)
Journal of Neuroscience
Vol. 31, Issue 30
27 Jul 2011
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Heritability of Working Memory Brain Activation
Gabriëlla A. M. Blokland, Katie L. McMahon, Paul M. Thompson, Nicholas G. Martin, Greig I. de Zubicaray, Margaret J. Wright
Journal of Neuroscience 27 July 2011, 31 (30) 10882-10890; DOI: 10.1523/JNEUROSCI.5334-10.2011

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Heritability of Working Memory Brain Activation
Gabriëlla A. M. Blokland, Katie L. McMahon, Paul M. Thompson, Nicholas G. Martin, Greig I. de Zubicaray, Margaret J. Wright
Journal of Neuroscience 27 July 2011, 31 (30) 10882-10890; DOI: 10.1523/JNEUROSCI.5334-10.2011
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