# Use of advanced analytics to understand brain-behavior screen media activity relationships in ABCD data > **NIH NIH RF1** · YALE UNIVERSITY · 2021 · $1,303,989 ## Abstract Project Summary/Abstract Growing up in a media-saturated world, the current generation of children and adolescents spend on average 6- 9 hours each day on screen media activities (SMAs). Therefore, SMA is a topic of considerable concern in the USA and elsewhere. Given changes in digital technologies and their usage over the past several decades, there is a significant gap in our understanding of shorter- and longer-term impacts of SMA on brain-behavior relationships. Prior studies suggest that problematic patterns of internet use (e.g., internet gaming disorder (IGD)) are linked to brain structural and functional alterations. However, the majority of research focuses on identifying individual SMA-related brain regions, which provide a crude approximation or an incomplete view of factors underlying these complex behaviors. We believe that consideration of brain networks is crucial to understanding neurodevelopmental mechanisms of SMA and associated behaviors. In this application, we propose to use data from the longitudinal Adolescent Brain Cognitive Development (ABCD) study to investigate network-level neural substrates linked to SMA, sleep disturbances and other clinically relevant measures. Multiple advanced analytical approaches will be used to extract novel features at both structural and functional levels. For example, the Joint and Individual Variance Explained (JIVE) method will be used to extract biologically meaningful cortical-subcortical covariation patterns. In this project, we aim to (1) establish relationships between SMA and brain structural and functional development in children aged 9-10 years; and, (2) investigate a potential mediating role of sleep disturbances on the relationship between SMA and brain structural and functional development. Our study uses innovative analytical methods to understand complex SMA-brain-behavior relationships in a large, developing sample recruited at 21 sites across the United Sates. Results from this application should provide important insights into understanding the neural processes involved in SMA, sleep disturbances and other clinically relevant behaviors within a developmental context. ## Key facts - **NIH application ID:** 10358692 - **Project number:** 1RF1MH128614-01 - **Recipient organization:** YALE UNIVERSITY - **Principal Investigator:** Marc N Potenza - **Activity code:** RF1 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2021 - **Award amount:** $1,303,989 - **Award type:** 1 - **Project period:** 2021-09-10 → 2026-03-09 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10358692 ## Citation > US National Institutes of Health, RePORTER application 10358692, Use of advanced analytics to understand brain-behavior screen media activity relationships in ABCD data (1RF1MH128614-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10358692. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*