Literature DB >> 27329671

Fronto-Parietal gray matter and white matter efficiency differentially predict intelligence in males and females.

Sephira G Ryman1, Ronald A Yeo2, Katie Witkiewitz2, Andrei A Vakhtin2, Martijn van den Heuvel3, Marcel de Reus3, Ranee A Flores2, Christopher R Wertz2, Rex E Jung2.   

Abstract

While there are minimal sex differences in overall intelligence, males, on average, have larger total brain volume and corresponding regional brain volumes compared to females, measures that are consistently related to intelligence. Limited research has examined which other brain characteristics may differentially contribute to intelligence in females to facilitate equal performance on intelligence measures. Recent reports of sex differences in the neural characteristics of the brain further highlight the need to differentiate how the structural neural characteristics relate to intellectual ability in males and females. The current study utilized a graph network approach in conjunction with structural equation modeling to examine potential sex differences in the relationship between white matter efficiency, fronto-parietal gray matter volume, and general cognitive ability (GCA). Participants were healthy adults (n = 244) who completed a battery of cognitive testing and underwent structural neuroimaging. Results indicated that in males, a latent factor of fronto-parietal gray matter was significantly related to GCA when controlling for total gray matter volume. In females, white matter efficiency and total gray matter volume were significantly related to GCA, with no specificity of the fronto-parietal gray matter factor over and above total gray matter volume. This work highlights that different neural characteristics across males and females may contribute to performance on intelligence measures. Hum Brain Mapp 37:4006-4016, 2016.
© 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Entities:  

Keywords:  efficiency; fronto-parietal gray matter; intelligence; sex differences

Mesh:

Year:  2016        PMID: 27329671      PMCID: PMC6867415          DOI: 10.1002/hbm.23291

Source DB:  PubMed          Journal:  Hum Brain Mapp        ISSN: 1065-9471            Impact factor:   5.038


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