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Title: Development of subcortical volumes across adolescence in males and females: A multisample study of longitudinal changes.

Authors: Herting, Megan M; Johnson, Cory; Mills, Kathryn L; Vijayakumar, Nandita; Dennison, Meg; Liu, Chang; Goddings, Anne-Lise; Dahl, Ronald E; Sowell, Elizabeth R; Whittle, Sarah; Allen, Nicholas B; Tamnes, Christian K

Published In Neuroimage, (2018 05 15)

Abstract: The developmental patterns of subcortical brain volumes in males and females observed in previous studies have been inconsistent. To help resolve these discrepancies, we examined developmental trajectories using three independent longitudinal samples of participants in the age-span of 8-22 years (total 216 participants and 467 scans). These datasets, including Pittsburgh (PIT; University of Pittsburgh, USA), NeuroCognitive Development (NCD; University of Oslo, Norway), and Orygen Adolescent Development Study (OADS; The University of Melbourne, Australia), span three countries and were analyzed together and in parallel using mixed-effects modeling with both generalized additive models and general linear models. For all regions and across all samples, males were found to have significantly larger volumes as compared to females, and significant sex differences were seen in age trajectories over time. However, direct comparison of sample trajectories and sex differences identified within samples were not consistent. The trajectories for the amygdala, putamen, and nucleus accumbens were most consistent between the three samples. Our results suggest that even after using similar preprocessing and analytic techniques, additional factors, such as image acquisition or sample composition may contribute to some of the discrepancies in sex specific patterns in subcortical brain changes across adolescence, and highlight region-specific variations in congruency of developmental trajectories.

PubMed ID: 29353072 Exiting the NIEHS site

MeSH Terms: Adolescent; Adolescent Development*; Brain/diagnostic imaging*; Brain/growth & development*; Datasets as Topic; Female; Humans; Image Processing, Computer-Assisted/methods; Longitudinal Studies; Magnetic Resonance Imaging/methods; Male; Neuroimaging/methods; Sex Characteristics*

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