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 = 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.

Keywords: MRI; T1w; brain; brain development; lifespan aging; structural covariance.

Figure 1

Analytical pipeline. Analysis included multi‐atlas segmentation of n = 5,019 images and subsequent division into 13 networks of interest, TICV‐correction of gray matter volumes, growth curve fitting using a covariate‐adjusted restricted cubic spline regression, and hierarchical clustering analysis to identify inter‐network correlations [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 2

Hypotheses and networks of interest (NOIs). (a) selected studies suggest that there are age‐related differences in regional structural covariance networks (SCNs), which the present study extended to inter‐network hypotheses. Current studies of structural covariance are restricted to either early (light gray) or later (dark gray) life examinations, and only one study that we are aware of (Chen et al., 2011) has examined inter‐network structural correlation patterns in any age group. (b) the current study examined 13 core SCNs (left and right of those displayed here, with the exception of the cerebellum) that are seen in development, young adulthood, and later life (see Section 2 for full description). See Table 2 for regions included in each network [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 3

Subjects per age group per site. Final subject inclusion numbers after quality control steps show that each age bin was represented by multiple sites, and each site was represented across multiple age bins. See Table 1 for specific number of images per age per site [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 4

Network covariance trajectories across the lifespannetwork covariance trajectories across the lifespan. (a) De‐meaned GMV growth curves per age bin for 13 networks. The network color legend is as follows: left visual (dark blue), right visual (cyan), left auditory (dark green), right auditory (light green), left sensorimotor (dark purple), right sensorimotor (light purple), cerebellum (black), left anterior cingulate (dark yellow), ¬¬right anterior cingulate (light yellow), left anterior default mode network (DMN; red), right anterior DMN (pink), left posterior DMN (orange), right posterior DMN (dark orange). (b) Box plots of inter‐network modularity metrics per age bin. Box color represents the age bin's lateral coordination (LC) measure (scaled to group maximum). Significant differences in modularity were seen between children and adolescence; young and middle adults; and older adults and later life adults (indicated by asterisk [*]). See Table 3 for modularity and LC metrics, and Supporting Information Table S1 for growth curve values [Color figure can be viewed at http://wileyonlinelibrary.com]

Figure 5

Network clustering patterns across the lifespannetwork hierarchical clustering patterns across the lifespan. Dendrograms demonstrate different hierarchical clustering patterns of network trajectories per age group. Clusters were identified through the Silhouette algorithm and are represented by different colors [Color figure can be viewed at http://wileyonlinelibrary.com]