PROJECT SUMMARY Anxiety and depression are increasingly recognized as disorders that are developmental in origin. While vulnerability to anxiety and depression is heightened prior to adulthood, the developmental factors that give rise to this increased risk are not well understood. Two characteristic learning and memory biases are implicated in the etiology of anxiety and depression: preferential processing of negatively valenced information and a tendency to form overly general memories and value associations. Despite their apparent clinical relevance, studies to date linking these learning and memory biases to psychiatric risk have relied largely on recollective measures that do not enable the study of how they may arise over development through value-based learning and memory encoding processes. In this proposal, we will leverage computational modeling and neuroimaging approaches to elucidate how mechanistic relations between learning computations and memory formation underlie valence and overgeneralization biases across development from childhood to adulthood. Aim 1 will characterize how valence biases in learning change over development, how they influence incidental memory for episodic details of valenced outcomes, and how they arise through neural computations. Aim 2 will characterize, across development, how generality of learned representations adapts across contexts, how the specificity of memory representations changes with time, and how neural representations support the use of multiple levels of abstraction to guide learning and memory. Aim 3 will characterize how valence and generalization biases change longitudinally with age and assess their relation to real-world autobiographical memory and clinical symptomatology. The significance of the proposed research lies in its potential to: 1) provide a theoretical account relating valence and generalization biases in value-based learning and corresponding biases in episodic and autobiographical memory; 2) elucidate the neurocognitive mechanisms underlying these biases; 3) delineate normative longitudinal developmental changes in these processes from childhood to adulthood; and 4) establish whether computational phenotypes capturing these biases predict anxious and depressive symptomatology.