Screen Time Is Associated with Altered Neural Maturation in a Massive Adolescent Cohort

Background: A 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. Methods: This longitudinal study examines structural and diffusion brain MRI scans from two timepoints collected 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 gray 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 subcellular level. Gray matter microstructure was measured across 13 bilateral regions functionally implicated with screen time use and associated with either the control or reward system. Results: 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 six of the 13 regions selected, while also finding significantly decreased intracellular signaling in eight regions, primarily in regions functionally associated with cognitive control. 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 relationships with increased screen time were found using GMD or fractional anisotropy. Conclusions: 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.