# Modeling Correlated Signals in Memory Systems

> **NIH NIH F32** · UNIVERSITY OF CALIFORNIA, SAN DIEGO · 2021 · $65,994

## Abstract

Project Summary
The dominant method for measuring short- and long-term memory in the laboratory is a
straightforward recognition memory test in which people are presented with a single item and
asked whether the item was or was not seen during the experiment. Recent work in the
eyewitness domain suggests, however, that when people are presented with multiple similar
items at test —instead of a single item at test— their memory performance is facilitated.
However, currently there is no mechanistic explanation regarding how presenting similar items
at test may improve memory. Furthermore, the formal study of this effect of similar items has not
been extended outside of the context of eyewitness memory. It is virtually unexamined in the
context of other memory systems, particularly, long- versus short-term memory, or stimuli that
are similar in different ways (i.e., across visual versus semantic dimensions). The aim of this
proposal is thus two-fold. The overarching aim is theoretical: To develop and test a theoretical
framework for how correlations amongst memory signals at test may arise from shared neural
populations representing items, and may facilitate memory. Not only will the project ask how
generalizable previous work from the eyewitness domain is, but a major novel aspect of the
project approach to this problem is that it will leverage computational modeling to develop an
integrative theoretical framework that helps address the question of how, specifically, similarity
between items presented at test facilitate memory. The second aim is empirical: To examine
how generalizable the finding is that similarity amongst stimuli presented at test affects memory,
across the long- and short-term memory systems, and for stimuli that are related on visual and
semantic dimensions. Thus, the project will be the first to test these effects across the study of
different memory systems, and across the study of items that are related based on their
semantic or visual similarity. Regardless of what empirical results are obtained, this line of work
will have broad implications for memory researchers and practitioners because it will, for the first
time, provide insight into the generality or boundary conditions for the effects of similar items in
memory test; furthermore, the current work will equip cognitive neural researchers with the
conceptual and computational tools to examine the neural signatures of these effects.

## Key facts

- **NIH application ID:** 10313319
- **Project number:** 1F32MH127823-01
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN DIEGO
- **Principal Investigator:** Maria Robinson
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $65,994
- **Award type:** 1
- **Project period:** 2021-08-01 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10313319

## Citation

> US National Institutes of Health, RePORTER application 10313319, Modeling Correlated Signals in Memory Systems (1F32MH127823-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10313319. Licensed CC0.

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