Project Summary Attention is the gateway to all we perceive, learn, and remember, and disorders of attention are a national public health concern. Although we live in a world of overlapping, dynamic, multimodal events, little is known about the development of attention amidst this complexity. Infants must learn to selectively attend to unitary multimodal events (intersensory processing, IP) by detecting synchronous sights and sounds (e.g., face and voice of a speaker), and to flexibly shift and maintain attention in the context of competing stimulation. These basic “multisensory attention skills” (MASks) provide a cornerstone for language, socio-emotional (SE), and cognitive development. However, there is no systematic database depicting the typical development of these foundational MASks or the developmental pathways leading to optimal outcomes. A key obstacle to progress has been the lack of individual difference measures appropriate for infants and children. To address this gap, we created the first such protocols. Our measures index IP, attention maintenance, and shifting in the context of overlapping audiovisual social and nonsocial events at a grain of analysis needed for characterizing skills of individual children, developmental change, and risk for atypical development. In our current RO1, we assessed longitudinal growth in MASks (across 3-72 mos; N=133). Our findings have modeled developmental pathways demonstrating that infant MASks cascade to an impressive range of critical child outcomes including language, school readiness, SE, and executive functioning. In the current proposal, we build on these novel findings: a) We extend our longitudinal testing through preadolescence (PreAd; 9, 10, 11 yrs; N=178), a particularly vulnerable period for SE development. b) We assess a new outcome domain, academic achievement, and broaden assessment of the SE domain given their importance for successful functioning in PreAd. c) We add a new predictor domain, family context (SES, maternal SE functioning, maternal sensitivity) known to predict child outcomes but never before linked to MASks. Using cutting-edge SEM-based growth curve and panel modeling, we will model how infant MASks develop and cascade to these important domains in childhood and PreAd. The specific aims are to characterize the typical longitudinal growth of MASks and define values signifying risk for delays (Aim 1), characterize pathways from infant MASks to all outcome domains (Aim 2), and assess the role of family context in shaping MASks and pathways to outcomes (Aim 3). With the larger sample at 9-11 yrs, we can test hypothesized and alternative models of developmental pathways in greater detail. Findings will be shared via Databrary and promise to advance theory, methodology, and knowledge by providing the first tools, data, and knowledgebase of developmental processes through which basic MASks influence a host of later outcomes. This has potential to catalyze a shift in the stu...