PROJECT SUMMARY In 2015, over 30% of 4th graders did not show proficiency in reading and math. Given the central importance of these academic skills for success in school and employment, understanding more about the mechanisms underlying academic success/failure is an important public health issue. While early reading and math growth each correlate with distinct cognitive skills (phonological awareness for reading and symbolic magnitude processing for math), they also substantially overlap, as seen by: (1) the comorbidity between reading and math difficulties; (2) the significant overlap in genetic variance for reading and math; and (3) the fact that several similar cognitive processes, including executive functions (EFs), are important cognitive correlates of reading and math. Considerable theoretical and empirical evidence also supports the importance of EF to reading and math. For example, while fMRI tasks elicit skill-specific areas [reading: left occipito-temporal; math: intraparietal sulcus], EF regions also are engaged. Although the predictive relations between EF and intervention response are inconsistent, early EF (in preschool/Kindergarten) does significantly predict later academic success. Despite the observed relations between EF and reading and math, however, there is little understanding of the neural mechanisms by which such EF-academic linkages develop. While the brain networks supporting reading, math, and EF have been investigated separately, their integration has not been studied within a developmental and intervention context. However, our recent work strongly supports a role for EF brain networks in academics: we find that EF neural networks facilitate connections between skill-specific nodes in the brain. We also find that the way EF brain regions interact with reading regions predicts poor readers' response to reading intervention with 95% accuracy. In the current study, we leverage our team's expertise in longitudinal multimodal neuroimaging studies in young children to examine how the neural networks supporting EF and skill-specific regions develop and interact. We hypothesize that the interaction between EF and skill-specific neural networks, not the individual networks themselves, will be highly predictive of: (a) reading and math growth from Kindergarten through 1st grade (Aim 1) and (b) response to reading intervention in 1st grade poor readers (Aim 2). We also experimentally manipulate EF by implementing EF training in a subset of Kindergarteners, which allows us to examine at the neural level whether and how early EF training may impact academic growth and reading intervention response. This approach may provide important insights regarding the ongoing debates about EF training. In sum, our proposal aims to elucidate how EF influences early academic growth, specifically whether interactions between networks (vs individual networks) are core driving factors in EF-academic links, and if/how EF predicts reading interve...