PROJECT SUMMARY Primary language impairment (PLI) affects 6-8% of children in the U.S. and the longer it goes undetected or untreated, the greater the negative cascading effect on children’s functioning. Late talking (LT) in toddlerhood (not meeting expressive language milestones between 18-24m) is an often-used marker of PLI risk (approximately 40% of LT have persistent delays and go on to receive a diagnosis of PLI). To date, research on LT has identified several factors that are associated with poorer language in the second year, including demographic, family history, and child neurocognitive variables. However, there is little extant research focusing on predictors of delayed expressive language in the first year, before the onset of major language milestones. For the proposed secondary data analysis, we will analyze data from three existing longitudinal studies conducted in our lab. These projects collectively provide a rich, densely sampled longitudinal dataset from 2-36m encompassing a diverse sample of children (n>300) with distinct factors (e.g., socioeconomic, familial history of language disorder or autism) that put them at elevated likelihood of developmental language delay. From these projects, we have access to a suite of demographic and environmental data, language measures, resting-state electroencephalogram (EEG) data, and videos of parent-child interactions (PCX). We plan to process EEG data, code PCX videos for language and parenting behaviors, and harmonize variables across studies to establish a unified dataset to retrospectively investigate the biopsychosocial factors that contribute to late talking and predict risk for PLI in early infancy. We have identified approximately n=64 late talkers in this sample and plan to select a group of matched peers who met typical expressive language milestones at 24m. The specific aims of the project are: 1. To trace longitudinal trajectories of EEG features from 2-24 months that are associated with late talking. 2. To identify features of the psychosocial environment with the greatest explanatory power for individual differences in EEG developmental trajectories and language outcomes at 24 and 36m. Our goal for this project is to establish a comprehensive foundation for identifying the neural mechanisms and environmental factors associated with language development that may, in combination, improve predictive models of delay and impairment. In addition, we plan to make this dataset available on NIH and public databases to facilitate future secondary analyses that may uncover nuanced patterns in the neurodevelopmental trajectories and psychosocial environments of late talkers.