# Neural mechanisms of stress effects across hippocampal encoding and prediction

> **NIH NIH R21** · YALE UNIVERSITY · 2023 · $209,375

## Abstract

PROJECT SUMMARY
Stressful events, or acute stressors, are an inescapable part of daily life and can precipitate the onset of mental
health disorders. One powerful mechanism by which acute stress contributes to the development of mental
health problems is through altering the structure and function of the hippocampus, a crucial brain structure for
learning. However, this relationship is complex: acute stress can both enhance and impair hippocampal learning,
making target mechanisms for treatment unclear. Research in rodents has shown that these contradictory
findings can be partly explained by distinct stress actions on different pathways and subregions within the
hippocampus. Whether these mechanisms extend to humans is unknown. To mitigate acute stress actions on
learning that contribute to psychopathology and design targeted interventions, there is a pressing need to
understand the mechanisms by which stress alters hippocampal learning in humans. This exploratory R21
proposal leverages recent advances in cognitive neuroscience to develop innovative functional neuroimaging
and behavioral protocols targeting distinct hippocampal pathways in order to translate stress findings from animal
models and uncover the mechanisms by which stress biases different types of learning in humans. We will test
the novel hypothesis that episodic encoding, which involves the trisynaptic pathway (shown to be impaired by
stress in rodent models: entorhinal cortex, dentate gyrus, cornu ammonis [CA] 3, and CA 1) will be impaired by
acute stress, whereas statistical learning, which involves the monosynaptic pathway (shown to be spared or
enhanced by stress: entorhinal cortex, CA1) will be enhanced by acute stress. This work marks the first
investigation of stress effects on statistical learning, a ubiquitous learning process recently implicated in mental
illness and treatment outcomes. Preliminary data indicate that a single behavioral paradigm can provide indices
of episodic encoding and statistical learning that map distinct hippocampal correlates. In Aim 1.1, we will optimize
this behavioral paradigm for detecting stress effects, and in Aim 1.2 we will determine the consequences of an
acute stress induction for learning and delayed retrieval of these episodic and statistical representations. In Aim
2, we will use functional neuroimaging (fMRI) together with hippocampal subfield segmentation and sophisticated
univariate, multivariate, and connectivity analyses, to quantify the neural mechanisms by which stress modulates
these distinct learning processes. Successful completion of these aims lays the foundation for translating
neurobiological mechanisms of stress actions from rodents to humans, providing critical information to reveal
novel targets for interventions that mitigate the risk of negative mental health outcomes resulting from stress.

## Key facts

- **NIH application ID:** 10678949
- **Project number:** 5R21MH128740-02
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Elizabeth Goldfarb
- **Activity code:** R21 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $209,375
- **Award type:** 5
- **Project period:** 2022-08-15 → 2025-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10678949

## Citation

> US National Institutes of Health, RePORTER application 10678949, Neural mechanisms of stress effects across hippocampal encoding and prediction (5R21MH128740-02). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10678949. Licensed CC0.

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