Developmental Ramifications of the Screen Age: Associations between Screen Time and Neural Maturation in a Massive Adolescent Cohort

Author:

Atalay Alexander S.ORCID,Newman Benjamin T.ORCID,Druzgal T. JasonORCID

Abstract

AbstractA growing body of literature associates increases in electronic screen time with a vast array of psychological consequences amongst adolescents, but little is known about the neurological underpinnings of this relationship. This longitudinal study examines structural and diffusion brain MRI scans from the Adolescent Brain Cognitive Development (ABCD)Study: a large multi-site study with thousands of participants. By assessing both gray matter density (GMD) and grey matter measurements of diffusion microstructure in the adolescent brain, we describe how the developmental trajectory of the brain changes with screen-based media consumption at the sub-cellular level. Grey matter microstructure was measured across 13 bilateral regions functionally implicated with screen time use, and associated with either the control or reward system. After controlling for age, sex, total brain volume, scanning site, sibling relationships, physical activity, and socioeconomic status, this study finds significant positive correlations between increased screen time and axonal signal across 6 of the 13 regions while also finding significantly decreased intracellular signal in 8 regions. Comparing these associations to normal developmental trajectories suggests adolescent age-related brain development may be accelerated by increased screen time in brain areas associated with reward processing while age-related brain development may be decelerated in regions of the control system. Highlighting the sensitivity of microstructural analysis, no significant cross-sectional or longitudinal relationship with increased screen time was found using GMD, or fractional anisotropy. This work suggests that increased screen usage during adolescent development has a complex association with brain tissue that cannot be completely described by traditional quantifications of tissue microstructure.

Publisher

Cold Spring Harbor Laboratory

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