Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins

Scamvougeras, Anton; Kigar, Debra L.; Jones, Douglas W.; Weinberger, Daniel R.; Witelson, Sandra F.

doi:10.1016/s0304-3940(02)01333-2

Cited by 69 publications

(37 citation statements)

References 18 publications

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“…For both methods, the volumetric correlation was higher, as expected, in the MZ twins than DZ twins, both subcortically and in the corpus callosum. These regions have previously been shown to be heritable ( [7] [26] [23]). We found that the parietal lobe volumes are relatively highly susceptible to shared environmental influences (exhibiting a high c 2 variance component), at least compared to occipital lobe volumes, which were predominantly under genetic control (exhibiting a high value for a 2 , the genetic variance component).…”

Section: Resultsmentioning

confidence: 99%

A Tensor-Based Morphometry Study of Genetic Influences on Brain Structure Using a New Fluid Registration Method

Brun¹,

Leporé²,

Pennec

et al. 2008

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008

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Abstract. We incorporated a new Riemannian fluid registration algorithm into a general MRI analysis method called tensor-based morphometry to map the heritability of brain morphology in MR images from 23 monozygotic and 23 dizygotic twin pairs. All 92 3D scans were fluidly registered to a common template. Voxelwise Jacobian determinants were computed from the deformation fields to assess local volumetric differences across subjects. Heritability maps were computed from the intraclass correlations and their significance was assessed using voxelwise permutation tests. Lobar volume heritability was also studied using the ACE genetic model. The performance of this Riemannian algorithm was compared to a more standard fluid registration algorithm: 3D maps from both registration techniques displayed similar heritability patterns throughout the brain. Power improvements were quantified by comparing the cumulative distribution functions of the p-values generated from both competing methods. The Riemannian algorithm outperformed the standard fluid registration.

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Section: Resultsmentioning

confidence: 99%

A Tensor-Based Morphometry Study of Genetic Influences on Brain Structure Using a New Fluid Registration Method

Brun¹,

Leporé²,

Pennec

et al. 2008

Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008

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“…The corpus callosum is known to vary widely across individuals (Beaton, 2004) and is also known to be variable in response to environmental conditions (Castro-Caldas et al, 1999;Kopcik, Juraska, & Washburne, 1986;Schlaug, Jäncke, Huang, Staiger, & Steinmetz, 1995;Strauss & Wada, 1993). Its size is also known to be highly heritable (Scamvougeras, Kigar, Jones, Weinberger, & Witelson, 2003). Thus, in families we might expect to reduce variability between participants, better revealing differences in the morphology of the corpus callosum related to reading ability.…”

Section: Study Questionsmentioning

confidence: 99%

Reading and the corpus callosum: An MRI family study of volume and area.

Fine¹,

Semrud‐Clikeman²,

Keith³

et al. 2007

Neuropsychology

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This study examines the corpus callosum in 68 readers nested in 24 families. Callosa were measured and controlled for whole brain volume, intelligence, and gender. The relation of corpus callosum size to the within-family variance of oral reading was investigated with various measurements: volume, midsagittal area, and anterior-to-posterior one-fifth area segmentations. Because this is the first known publication of MRI calculations of corpus callosum volume, some basic questions about bilateral symmetry and the efficacy of area versus volumetric measurements were explored. Results suggest that better readers within families have larger midsagittal areas at the midbody. Although reliably measured, volume did not contribute to oral reading but was highly correlated with area. Bilateral volumes of the corpus callosum were symmetric.

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“…More generally, this same argument applies to any claim of genetic biases causing cultural differences between human populations. Components (i) and (ii), concerning interindividual variability, are generally well-established for language either independently (Bartley et al, 1997;Lenroot et al, 2007;Scamvougeras et al, 2003;Thompson et al, 2001;Wright et al, 2002) or as a conglomerate in studies involving the heritability of language (Bishop, 2003;Bonneau et al, 2004;Felsenfeld, 2002;Fisher et al, 2003;Plomin and Kovas, 2005;Stromswold, 2001). Component (iii) concerns interpopulation variability and asserts that populations with different genetic structures could develop overt linguistic differences.…”

Section: Introductionmentioning

confidence: 99%

The role of genetic biases in shaping the correlations between languages and genes

Dediu

2008

Journal of Theoretical Biology

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It has recently been proposed (Dediu, D., Ladd, D.R., 2007. Linguistic tone is related to the population frequency of the adaptive haplogroups of two brain size genes, ASPM and Microcephalin. Proc Natl Acad Sci USA 104, 10944-10949) that genetically coded linguistic biases can influence the trajectory of language change. However, the nature of such biases and the conditions under which they can become manifest have remained vague. The present paper explores computationally two plausible types of linguistic acquisition biases in a population of agents implementing realistic genetic, linguistic and demographic processes. One type of bias represents an innate asymmetric initial state (Initial Expectation bias)while the other an innate asymmetric facility of acquisition (Rate of Learning bias). It was found that only the second type of bias produces detectable effects on language through cultural transmission across generations and that such effects are produced even by weak biases present at low frequencies in the population. This suggests that learning preference asymmetries, very small at the individual level and not very frequent at the population level, can bias the trajectory of language change through the process of cultural transmission.

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Size of the human corpus callosum is genetically determined: an MRI study in mono and dizygotic twins

Cited by 69 publications

References 18 publications

A Tensor-Based Morphometry Study of Genetic Influences on Brain Structure Using a New Fluid Registration Method

A Tensor-Based Morphometry Study of Genetic Influences on Brain Structure Using a New Fluid Registration Method

Reading and the corpus callosum: An MRI family study of volume and area.

The role of genetic biases in shaping the correlations between languages and genes

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