Environmental influences on infant cortical thickness and surface area

Shaili C. Jha, Kai Xia, Mihye Ahn, Jessica B. Girault, Gang Li, Li Wang, Dinggang Shen, Fei Zou, Hongtu Zhu, Martin Styner, John H. Gilmore, Rebecca C. Knickmeyer

Research output: Contribution to journalArticlepeer-review

59 Citations (Scopus)

Abstract

Cortical thickness (CT) and surface area (SA) vary widely between individuals and are associated with intellectual ability and risk for various psychiatric and neurodevelopmental conditions. Factors influencing this variability remain poorly understood, but the radial unit hypothesis, as well as the more recent supragranular cortex expansion hypothesis, suggests that prenatal and perinatal influences may be particularly important. In this report, we examine the impact of 17 major demographic and obstetric history variables on interindividual variation in CT and SA in a unique sample of 805 neonates who received MRI scans of the brain around 2 weeks of age. Birth weight, postnatal age at MRI, gestational age at birth, and sex emerged as important predictors of SA. Postnatal age at MRI, paternal education, and maternal ethnicity emerged as important predictors of CT. These findings suggest that individual variation in infant CT and SA is explained by different sets of environmental factors with neonatal SA more strongly influenced by sex and obstetric history and CT more strongly influenced by socioeconomic and ethnic disparities. Findings raise the possibility that interventions aimed at reducing disparities and improving obstetric outcomes may alter prenatal/perinatal cortical development.

Original languageEnglish
Pages (from-to)1139-1149
Number of pages11
JournalCerebral Cortex
Volume29
Issue number3
DOIs
Publication statusPublished - 2019 Mar 1

Bibliographical note

Publisher Copyright:
© The Author(s) 2018. Published by Oxford University Press. All rights reserved.

Keywords

  • brain development
  • neonate
  • neuroimaging
  • premature birth
  • socioeconomic status

ASJC Scopus subject areas

  • Cognitive Neuroscience
  • Cellular and Molecular Neuroscience

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