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Dataset factors associated with age‐related changes in brain structure and function in neurodevelopmental conditions.

Authors :
Vandewouw, Marlee M.
Ye, Yifan
Crosbie, Jennifer
Schachar, Russell J.
Iaboni, Alana
Georgiades, Stelios
Nicolson, Robert
Kelley, Elizabeth
Ayub, Muhammad
Jones, Jessica
Arnold, Paul D.
Taylor, Margot J.
Lerch, Jason P.
Anagnostou, Evdokia
Kushki, Azadeh
Source :
Human Brain Mapping. Sep2024, Vol. 45 Issue 13, p1-15. 15p.
Publication Year :
2024

Abstract

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium‐based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age‐related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age‐related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting‐state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age‐related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
10659471
Volume :
45
Issue :
13
Database :
Academic Search Index
Journal :
Human Brain Mapping
Publication Type :
Academic Journal
Accession number :
179639491
Full Text :
https://doi.org/10.1002/hbm.26815