# Interactive development of reinforcement learning and adaptive memory

> **NIH NIH R01** · NEW YORK UNIVERSITY · 2021 · $784,565

## Abstract

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.

## Key facts

- **NIH application ID:** 10200405
- **Project number:** 1R01MH126183-01
- **Recipient organization:** NEW YORK UNIVERSITY
- **Principal Investigator:** Catherine Alexandra Hartley
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $784,565
- **Award type:** 1
- **Project period:** 2021-06-15 → 2026-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10200405

## Citation

> US National Institutes of Health, RePORTER application 10200405, Interactive development of reinforcement learning and adaptive memory (1R01MH126183-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10200405. Licensed CC0.

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