Use of advanced analytics to understand brain-behavior screen media activity relationships in ABCD data

项目摘要/摘要 在媒体饱和的世界中长大的当代儿童和青少年平均花费6- 每天9小时的屏幕媒体活动(SMA)。因此，SMA是一个备受关注的话题。 美国和其他地方。鉴于过去几十年来数字技术及其使用的变化， 是我们对SMA对大脑行为的短期和长期影响的理解上的一个重大差距 两性关系。先前的研究表明，有问题的互联网使用模式(例如，互联网游戏障碍) (IGD)与大脑结构和功能改变有关。然而，大多数研究都集中在 识别与SMA相关的单个大脑区域，这些区域提供了粗略的近似或不完整的视图 这些复杂行为背后的因素。我们认为，对大脑网络的考虑对于 了解SMA的神经发育机制及相关行为。在此应用程序中，我们 建议使用青少年大脑认知发展(ABCD)纵向研究的数据来研究 网络水平的神经底物与SMA、睡眠障碍和其他临床相关措施有关。 将使用多种先进的分析方法来提取结构和功能上的新特征 级别。例如，将使用联合和个别方差解释(JIVE)方法提取生物 有意义的皮质-皮质下协变模式。在这个项目中，我们的目标是(1)建立以下关系 SMA与9-10岁儿童的脑结构和功能发育；以及，(2)调查潜在的 睡眠障碍在SMA与脑结构和功能关系中的中介作用 发展。我们的研究使用创新的分析方法来理解复杂的SMA大脑行为 在全美21个地点进行了一次大规模的、发展中的样本调查。由此产生的结果 应用应该为理解SMA、睡眠中涉及的神经过程提供重要的见解 发育背景下的精神障碍和其他临床相关行为。

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.