Morphometry of the corpus callosum in Chinese children: relationship with gender and academic performance

Ng, Wing Hung Alex, Chan, Yu Lung, Au, Kit Sum Agnes, Yeung, Ka Wai David, Kwan, Ting Fai, and To, Cho Yee (2005) Morphometry of the corpus callosum in Chinese children: relationship with gender and academic performance. Pediatric Radiology, 35 (6). pp. 565-571.

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Abstract

Background: the corpus callosum has been widely studied, but no study has demonstrated whether its size and shape have any relationship with language and calculation performance.

Objective: to examine the morphometry of the corpus callosum of normal Chinese children and its relationship with gender and academic performance.

Materials and methods: One hundred primary school children (63 boys, 37 girls; age 6.5–10 years) were randomly selected and the standardized academic performance for each was ascertained. On the mid-sagittal section of a brain MRI, the length, height and total area of the corpus callosum and its thickness at different sites were measured. These were correlated with sex and academic performance.

Results: apart from the normal average dimension of the different parts of the corpus callosum, thickness at the body-splenium junction in the average-to-good performance group was significantly greater than the below-average performance group in Chinese language (P=0.005), English language (P=0.02) and mathematics (P=0.01). The remainder of the callosal thickness showed no significant relationship with academic performance. There was no significant sex difference in the thickness of any part of the corpus callosum.

Conclusions: these findings raise the suggestion that language and mathematics proficiency may be related to the morphometry of the fibre connections in the posterior parietal lobes.

Item ID: 8995
Item Type: Article (Refereed Research - C1)
Keywords: brain; anatomy; Corpus callosum; intellect; gender; MRI; children
ISSN: 1432-1998
Date Deposited: 10 Mar 2010 01:33
FoR Codes: 17 PSYCHOLOGY AND COGNITIVE SCIENCES > 1702 Cognitive Science > 170205 Neurocognitive Patterns and Neural Networks @ 100%
SEO Codes: 97 EXPANDING KNOWLEDGE > 970117 Expanding Knowledge in Psychology and Cognitive Sciences @ 100%
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