A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Abstract

ABSTRACT Our minds and brains are highly unique. Despite the long-recognized importance of the environment in shaping individual differences in cognitive neurodevelopment, only with the combination of deep phenotyping approaches and the availability of large-scale datasets have we been able to more comprehensively characterize the many inter-connected features of an individual’s environment and experience (“exposome”). Moreover, despite clear evidence that brain organization is highly individualized, most neuroimaging studies still rely on group atlases to define functional networks, smearing away inter-individual variation in the spatial layout of functional networks across the cortex (“functional topography”). Here, we leverage the largest longitudinal study of brain and behavior development in the United States to investigate how an individual’s exposome may contribute to functional brain network organization leading to differences in cognitive functioning. To do so, we apply three previously-validated data driven computational models to characterize an individual’s multidimensional exposome, define individual-specific maps of functional brain networks, and measure cognitive functioning across broad domains. In pre-registered analyses replicated across matched discovery ( n =5,139, 48.5% female) and replication ( n =5,137, 47.1% female) samples, we find that a child’s exposome is associated with multiple domains of cognitive functioning both at baseline assessment and two years later – over and above associations with baseline cognition. Cross-validated ridge regression models reveal that the exposome is reflected in children’s unique patterns of functional topography. Finally, we uncover both shared and unique contributions of the exposome and functional topography to cognitive abilities, finding that models trained on a single variable capturing a child’s exposome can more accurately and parsimoniously predict future cognitive performance than models trained on a wealth of personalized neuroimaging data. This study advances our understanding of how childhood environments contribute to unique patterns of functional brain organization and variability in cognitive abilities.