Cortical surface complexity in a population-based normative sample

Brynn A. Dombroski, Matthew J. Nitzken, Ahmed A. Elnakib, Fahmi Khalifa, Andrew E. Switala, Ayman S. El-Baz, Manuel F. Casanova

Research output: Contribution to journalArticlepeer-review

20 Scopus citations

Abstract

MRI studies on abnormal brain development are dependent on the quality, quantity, and type of normative development data available for comparison. Limitations affecting previous studies on normative development include small sample sizes, lack of demographic representation, heterogeneous subject populations, and inadequate longitudinal data. The National Institutes of Health Pediatric MRI Data Repository (NIHPD) for normative development was designed to address the aforementioned issues in reliability measures of control subjects for comparison studies. The subjects were recruited from six Pediatric Study Centers nationwide to create the largest, non-biased, longitudinal database of the developing brain. Using the NIHPD, we applied a 3D shape analysis method involving spherical harmonics to identify the cortical surface complexity of 396 subjects (210 female; 186 male) between the ages of 4.8 y and 22.3 y. MRI data had been obtained at one, two, or three time points approximately two years apart. A total of 144 participants (79 female; 65 male) provided MRI data from all time points. Our results confirm a direct correlation between cortical complexity and age in both males and females. Additionally, within the examined age range, females displayed consistently and significantly greater cortical complexity than males. Findings suggest that the underlying neural circuitry within male and female brains is different, possibly explaining observations of sexual dimorphism in social interaction, communication, and higher cognitive processes.

Original languageEnglish (US)
Pages (from-to)17-24
Number of pages8
JournalTranslational Neuroscience
Volume5
Issue number1
DOIs
StatePublished - Mar 2014

All Science Journal Classification (ASJC) codes

  • General Neuroscience

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