Structural covariance across the lifespan: Brain development and aging through the lens of inter‐network relationships

Abstract

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 = 5019, 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.

The developing relations between networks of cortical myelin and neurophysiological connectivity

“…Consistent with previous studies examining typical development from childhood to young adulthood, the age-related changes of both structural covariance (24)(25)(26)(27) and MEG functional connectivity (28)(29)(30) follow predominantly nonlinear, quadratic trajectories. The differences in functional connectivity with age was marked by increases in functional connectivity with age in the alpha and beta bands and decreases in the gamma bands, consistent with developmental changes reported in both phase-based (31) and amplitude (30, 32) connectivity measures.…”

OUP accepted manuscript

“…Structural covariance networks are more similar to patterns of functional connectivity than the architecture of white matter connections, suggesting that areas that co-vary in morphological characteristics also belong to the same functional network (Zielinski et al, 2010;Soriano-Mas et al, 2013). Such networks are thought to be shaped by genetic and environmental influences from early childhood (Richmond et al, 2016) and may continue to be reshaped during the lifespan (Alexander-Bloch et al, 2013;Aboud et al, 2019;Qi et al, 2019) by a range of trophic influences (Ferrer et al, 1995;Draganski et al, 2004;Mechelli et al, 2005).…”

Prenatal stress and its association with amygdala-related structural covariance patterns in youth

“…Given the literature on changes in structural covariance in young adulthood (e.g. increases until 21 years followed by decreases until 30 years) ( Aboud et al, 2019 ), one possible reason for this discrepancy may be the fact that participants from the ALSPAC cohort were younger at the time of scan ( Sierra-Mercado et al, 2011 , McEwen, 2007 , Janak and Tye, 2015 ) than the young adults from ELSPAC ( Tottenham and Sheridan, 2009 , Humphrey, 1968 ) and thus the amygdala networks might not have been fully mature yet. Another possible reason might be the fact that the prenatal stress experienced by the ALSPAC cohort was lower than the prenatal stress experienced by the ELSPAC/VULDE cohort.…”