Project Summary Behavior dysregulation emerges early in life, is persistent, and often has lasting associations with more intractable symptoms of child psychopathology. Attempting to isolate early risk factors is difficult due to the varying presentations of behavior dysregulation, including comorbidities, differing developmental trajectories, and varying responses to treatments. Consequently, it is vital to isolate early developmental risk groups by characterizing early risk mechanisms in clearly identifiable subgroups at risk for behavioral disorders, such as children with prenatal nicotine exposure. These children are at least 1.5 times more likely to develop attention- deficit hyperactivity disorder ADHD, and often display early attention, motor, and sleep dysregulation commonly associated with the disorder. Yet, the etiological pathways from infant risk factors to later behavior dysregulation are unclear. Attention, motor, and sleep behavior are transdiagnostic constructs that are hypothesized to underlie many behavioral disorders, including ADHD, and internalizing and externalizing disorders. Thus, they may be important phenotypic markers predicting early behavior dysregulation. This K99/R00 proposal will help to identify infants who may develop persistent behavior dysregulation from infants exhibiting transient behaviors or no/low risk symptoms through multiple Research Domain Criteria (RDoC) constructs. This project seeks to incorporate more sensitive, scalable, and automated measure to identify behavior dysregulation earlier in development than current assessments allow. The first aim (K99) will leverage integrative data analysis techniques to identify modifiable, RDoC-informed mechanisms that increase risk for behavior dysregulation in toddlers. Through data aggregation and advanced statistical techniques, this project will uncover meaningful insights from a large integrated cohort (N > 3,000) composed of multiple independent datasets on nicotine exposure during pregnancy and neurodevelopmental outcomes from birth to 3 years of age. The second aim (R00) will track trajectories and timing of attention, motor, and sleep behavior using early, sensitive, and scalable measures to pinpoint risk for later behavior dysregulation in infants exposed to nicotine in utero. For this aim, we will recruit a new sample of birthing parents and infants across the first postnatal year (< 5 days old, and 4-, 8-, and 12-month-old infants) to characterize trajectories of attention, motor, and sleep to determine how these trajectories predict risk for behavior dysregulation at 1-year of age. To accomplish these aims, the mentored training will focus on furthering knowledge on the risk phenotypes of behavior dysregulation, and data harmonization and advanced causal modeling. This project will provide advanced training to support future research on using sensitive, scalable, and automated measures to detect risk for psychopathology in early childhood. It will a...