Associations between Neighborhood SES and Functional Brain Network Development. (11th April 2019)

• Record Type: Journal Article
• Authors: Tooley, Ursula A; Mackey, Allyson P; Ciric, Rastko; Ruparel, Kosha; Moore, Tyler M; Gur, Ruben C; Gur, Raquel E; Satterthwaite, Theodore D; Bassett, Danielle S
• Is Part Of: Cerebral cortex. Volume 30:Number 1(2020)
• Page Start: 1
• Page End: 19
• Publication Date: 2019-04-11
• Subjects: development -- fMRI -- graph theory -- regional homogeneity -- socioeconomic status; Cerebral cortex -- Periodicals; Brain -- Periodicals; 612.825
• DOI: 10.1093/cercor/bhz066
• Languages: English
• ISSNs: 1047-3211

Abstract

Abstract: Higher socioeconomic status (SES) in childhood is associated with stronger cognitive abilities, higher academic achievement, and lower incidence of mental illness later in development. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large cross-sectional community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8–22 years, n = 1012) to examine associations between age, SES, and functional brain network topology. We characterize this topology using a local measure of network segregation known as the clustering coefficient and find that it accounts for a greater degree of SES-associated variance than mesoscale segregation captured by modularity. High-SES youth displayed stronger positive associations between age and clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The moderating effect of SES on positive associations between age and clustering was strongest for connections of intermediate length and was consistent with a stronger negative relationship between age and local connectivity in these regions in low-SES youth. Our findings suggest that, in late childhood and adolescence, neighborhood SES is associated with variation in the development of functional network structure in the human brain.