Erratum to “Positive association between cognitive ability and cortical thickness in a representative US sample of healthy 6 to 18 year-olds”

• Published in: Intelligence (Norwood) Vol. 37; no. 4; pp. 432 - 442
• Main Authors: Karama, S., Ad-Dab'bagh, Y., Haier, R.J., Deary, I.J., Lyttelton, O.C., Lepage, C., Evans, A.C.
• Format: Journal Article
• Language: English
• Published: Elsevier Inc 2009
• Subjects: Adolescents; Brain imaging; Children; Cognitive ability; Cortical thickness; Intelligence; Cortical thickness; Brain imaging; Intelligence; Cognitive ability; IQ; Children; Adolescents
• ISSN: 0160-2896; 1873-7935
• DOI: 10.1016/j.intell.2009.03.010

Neuroimaging studies, using various modalities, have evidenced a link between the general intelligence factor (
g) and regional brain function and structure in several multimodal association areas. While in the last few years, developments in computational neuroanatomy have made possible the
in vivo quantification of cortical thickness, the relationship between cortical thickness and psychometric intelligence has been little studied. Recently, cortical thickness estimations have been improved by the use of an iterative hemisphere-specific template registration algorithm which provides a better between-subject alignment of brain surfaces. Using this improvement, we aimed to further characterize brain regions where cortical thickness was associated with cognitive ability differences and to test the hypothesis that these regions are mostly located in multimodal association areas. We report associations between a general cognitive ability factor (as an estimate of
g) derived from the four subtests of the Wechsler Abbreviated Scale of Intelligence and cortical thickness adjusted for age, gender, and scanner in a large sample of healthy children and adolescents (ages 6–18,
n
=
216) representative of the US population. Significant positive associations were evidenced between the cognitive ability factor and cortical thickness in most multimodal association areas. Results are consistent with a distributed model of intelligence.