Journal
HUMAN BRAIN MAPPING
Volume 40, Issue 1, Pages 125-136Publisher
WILEY
DOI: 10.1002/hbm.24359
Keywords
brain; brain development; lifespan aging; MRI; structural covariance; T1w
Funding
- National Institutes of Health
- National Science Foundation [1452485]
- National Institute of Neurological Disorders and Stroke [N01-NS-9-2320, N01-NS-9-2319, N01-NS-9-2317, N01-NS-9-2316, N01-NS-9-2315, N01-NS-9-2314]
- National Institute of Mental Health [N01-MH9-0002]
- National Institute on Drug Abuse
- National Institute of Child Health and Human Development [N01-HD02-3343]
- National Institute on Aging, NIH [NCATS/NIH UL1 TR000445, U54 HD083211, R01 HD044073, R01 HD067254, R03EB012461, R21NS064534, NIH R21EY024036, NIH R01EB017230]
- NATIONAL INSTITUTE ON AGING [ZIAAG000191] Funding Source: NIH RePORTER
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Recent studies have revealed that brain development is marked by morphological synchronization across brain regions. Regions with shared growth trajectories form structural covariance networks (SCNs) that not only map onto functionally identified cognitive systems, but also correlate with a range of cognitive abilities across the lifespan. Despite advances in within-network covariance examinations, few studies have examined lifetime patterns of structural relationships across known SCNs. In the current study, we used a big-data framework and a novel application of covariate-adjusted restricted cubic spline regression to identify volumetric network trajectories and covariance patterns across 13 networks (n = 5,019, ages = 7-90). Our findings revealed that typical development and aging are marked by significant shifts in the degree that networks preferentially coordinate with one another (i.e., modularity). Specifically, childhood showed higher modularity of networks compared to adolescence, reflecting a shift over development from segregation to desegregation of inter-network relationships. The shift from young to middle adulthood was marked by a significant decrease in inter-network modularity and organization, which continued into older adulthood, potentially reflecting changes in brain organizational efficiency with age. This study is the first to characterize brain development and aging in terms of inter-network structural covariance across the lifespan.
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