Marlee M. Vandewouw, Yifan (Julia) Ye, Jennifer Crosbie, Russell J. Schachar, Alana Iaboni, Stelios Georgiades, Robert Nicolson, Elizabeth Kelley, Muhammad Ayub, Jessica Jones, Paul D. Arnold, Margot J. Taylor, Jason P. Lerch, Evdokia Anagnostou, Azadeh Kushki
{"title":"与神经发育状况下大脑结构和功能的年龄相关变化有关的数据集因素","authors":"Marlee M. Vandewouw, Yifan (Julia) Ye, Jennifer Crosbie, Russell J. Schachar, Alana Iaboni, Stelios Georgiades, Robert Nicolson, Elizabeth Kelley, Muhammad Ayub, Jessica Jones, Paul D. Arnold, Margot J. Taylor, Jason P. Lerch, Evdokia Anagnostou, Azadeh Kushki","doi":"10.1002/hbm.26815","DOIUrl":null,"url":null,"abstract":"<p>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; <i>N</i> = 1218) and function (resting-state functional connectivity strength; <i>N</i> = 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.</p>","PeriodicalId":13019,"journal":{"name":"Human Brain Mapping","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.26815","citationCount":"0","resultStr":"{\"title\":\"Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions\",\"authors\":\"Marlee M. Vandewouw, Yifan (Julia) Ye, Jennifer Crosbie, Russell J. Schachar, Alana Iaboni, Stelios Georgiades, Robert Nicolson, Elizabeth Kelley, Muhammad Ayub, Jessica Jones, Paul D. Arnold, Margot J. Taylor, Jason P. Lerch, Evdokia Anagnostou, Azadeh Kushki\",\"doi\":\"10.1002/hbm.26815\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>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; <i>N</i> = 1218) and function (resting-state functional connectivity strength; <i>N</i> = 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.</p>\",\"PeriodicalId\":13019,\"journal\":{\"name\":\"Human Brain Mapping\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/hbm.26815\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Human Brain Mapping\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/hbm.26815\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"NEUROIMAGING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Human Brain Mapping","FirstCategoryId":"3","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/hbm.26815","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"NEUROIMAGING","Score":null,"Total":0}
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.
期刊介绍:
Human Brain Mapping publishes peer-reviewed basic, clinical, technical, and theoretical research in the interdisciplinary and rapidly expanding field of human brain mapping. The journal features research derived from non-invasive brain imaging modalities used to explore the spatial and temporal organization of the neural systems supporting human behavior. Imaging modalities of interest include positron emission tomography, event-related potentials, electro-and magnetoencephalography, magnetic resonance imaging, and single-photon emission tomography. Brain mapping research in both normal and clinical populations is encouraged.
Article formats include Research Articles, Review Articles, Clinical Case Studies, and Technique, as well as Technological Developments, Theoretical Articles, and Synthetic Reviews. Technical advances, such as novel brain imaging methods, analyses for detecting or localizing neural activity, synergistic uses of multiple imaging modalities, and strategies for the design of behavioral paradigms and neural-systems modeling are of particular interest. The journal endorses the propagation of methodological standards and encourages database development in the field of human brain mapping.