ABSTRACT Children from adverse developmental environments demonstrate varied reading achievement. The overarching hypothesis of the proposed research is that genetic and neural canalization provide a buffer against the negative impacts of developmental risks to ensure normative reading and language achievement. Specific Aim 1 tests the hypothesis that genetic canalization protects against the well-established negative effects of low socioeconomic status on written and oral language development. We focus on the polygenic and environmental interactions to characterize canalization, including the extent to which the prevalence of low written and oral language achievement decreases with (better) polygenic scores for children from environments with high developmental risk. Here, we will examine: 1) specific social determinants of health where genetic canalization may be critically important for ensuring normal development; 2) the specificity of canalization to reading and language relative to executive functions; 3) and the degree to which there are brain structure endophenotypes for genetic canalization. Specific Aim 1 examines population-level effects, whereas Specific Aim 2 examines the instantiation of canalization within individuals and tests the hypothesis that a cortical network shown to optimize task performance can explain reading performance in children with risks for adverse development. For both aims, large datasets and novel topological analyses are used to provide optimal rigor for these experiments that will be pre-registered. Specific Aim 3 is to grow an existing data repository of data from neuroimaging studies on reading disability and development, as well as enhance the functions and our data delivery and sharing resource. This resource includes the integration of methods to generate data that can be used to replicate previous reading disability findings. This will include deep learning approaches for identifying neural predictors of reading disability, with a focus on features that canalize reading development. Together, the theoretically motivated study of large datasets will generate results to advance our understanding about the development of reading disability, particularly for children from adverse developmental environments, and further an open science initiative that is expected to advance reading disability research through data access, replication, and new discovery.