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

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.

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Publication Details

Journal
Human Brain Mapping
Published
2024-09-01
DOI
https://doi.org/10.1002/hbm.26815
Citations
4
Primary Topic
Functional Brain Connectivity Studies
Type
article
Field-Weighted Citation Impact
1.37

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article

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

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4 citations
Human Brain Mapping
Functional Brain Connectivity Studies
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article

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

Elizabeth Kelley, Evdokia Anagnostou, Jennifer Crosbie, Rob Nicolson, Jason P. Lerch, Muhammad Ayub, Stelios Georgiades, Azadeh Kushki, Marlee M. Vandewouw, Russell Schachar, Jessica Jones, Yifan Ye, Alana Iaboni, Paul D. Arnold, Margot J. Taylor
article en
4 citations

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.

Human Brain MappingVol. 45(13)
Western University (CA), University of Calgary (CA), University of Toronto (CA), Queen's University (CA), Hospital for Sick Children (CA), Holland Bloorview Kids Rehabilitation Hospital (CA), University of Oxford (GB), Wellcome Centre for Integrative Neuroimaging (GB), University College London (GB), McMaster University (CA)
Ontario Brain Institute, Government of Ontario, Child Mind Institute, Canadian Institutes of Health Research
Openalex Percentile: Top 20%
Functional Brain Connectivity Studies
1.37
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