# Inferring latent contexts to guide behavior and memory

> **NIH NIH F32** · COLUMBIA UNIV NEW YORK MORNINGSIDE · 2022 · $67,174

## Abstract

PROJECT SUMMARY
Our everyday experiences are defined by environmental regularities. These regularities form stable contexts
that enable us to make predictions about our environment (e.g., you are more likely to see your co-worker on a
weekday than a weekend). In these cases, your context (day of the week) is inferred based on integrating
across experiences: in other words, it is latent. However, laboratory investigations of context have largely used
observable manipulations (e.g., background color of the screen, task judgements, stimulus class). Latent
contexts require cross-talk between mnemonic and perceptual systems to compare incoming evidence to
previously learned expectations. Here, we propose a novel experiment to determine the impact of latent
contexts on brain activity and behavior. We will use item co-occurrences to instantiate latent contexts (e.g.,
seeing your co-worker, then the office cleaning staff, and then your boss is predictive of a weekday context).
We hypothesize that latent contexts will affect the way we represent information and perceive the environment.
We will test this across 3 Aims using functional magnetic resonance imaging (fMRI), computational models,
eye tracking, and behavioral assays. Across these aims we will interrogate the impact of latent states on the
brain’s representations of contexts (Aim 1) and items (Aim 2), and how these representations influence the
allocation of attention (Aim 3). We predict that latent contexts require accumulation of evidence in regions that
can integrate across experiences like hippocampus and posterior medial cortex. These regions will show shifts
in activity patterns that can be detected with machine learning models. Across the course of learning latent
contexts, regions of the brain will re-shape how they represent associated items. Once item/context
associations have been learned, patterns of activity will contain information about both the items themselves
and their contextual associations. We hypothesize that this shift in representations will predominately happen
in regions that integrate across related items to track contexts, like the hippocampus and medial prefrontal
cortex. However, representations in other regions that are attuned to perceptual information but not contextual
relationships, like visual cortex and perirhinal cortex, will not change across the course of learning. We also
hypothesize that being in a latent context will facilitate predictions of upcoming information at the expense of
detecting perceptual changes in the environment. Understanding latent contexts has important consequences
for how we characterize psychological and neural functioning in many psychiatric conditions like PTSD and
anxiety in addition to the fundamental basic science questions about interactions between memory and
perception that this proposal will answer.

## Key facts

- **NIH application ID:** 10389349
- **Project number:** 1F32EY032352-01A1
- **Recipient organization:** COLUMBIA UNIV NEW YORK MORNINGSIDE
- **Principal Investigator:** Halle Dimsdale-Zucker
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $67,174
- **Award type:** 1
- **Project period:** 2022-02-11 → 2025-02-10

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10389349

## Citation

> US National Institutes of Health, RePORTER application 10389349, Inferring latent contexts to guide behavior and memory (1F32EY032352-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10389349. Licensed CC0.

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