# Long-term consequences of visual working memory

> **NIH NIH K99** · UNIVERSITY OF CHICAGO · 2022 · $107,215

## Abstract

Project Summary
The ability to remember information, whether after short or long delays, is a fundamental human ability. There is
enormous research into understanding working memory and long-term memory in isolation, but also a
longstanding debate about the interactions between working memory and long-term memory. This research
proposal would address a critical knowledge gap by investigating and dissecting the gateway hypothesis, to
characterize how working memory delay activity predicts what information is later remembered and to build brain-
computer interfaces that leverage real-time insight into working memory delay activity to alter later memory. A
better understanding how working memory and long-term memory interact would be beneficial for the numerous
psychiatric disorders which are characterized by deficits in these systems. Recent empirical research has
revealed links between working memory capacity and long-term memory, however multiple sub-processes
underlie maintaining multiple items in working memory. For example, there are neural signatures that correspond
to the number of items in working memory, and distinct neural signatures that correspond to the spatial locations
of items in working memory. Either or both of those sub-processes, number and location, could predict long-term
memory. I will use multivariate decoding in conjunction with time resolved neuroscience techniques, EEG (Aim
1) and intracranial EEG (Aim 2) to characterize these working memory sub-processes and their relationship to
long-term memory. Then, as an independent investigator, I will build tools that can track delay activity in real
time and adaptively design experiments contingent to the number and location of items of working memory. This
will test a detailed and specific conceptualization of the relationship between working memory and long-term
memory. The research and training goals of this research proposal will be furthered by an advising team of
cognitive, systems, and clinical neuroscientists at the University of Chicago and UC Berkeley. This research
proposal encompasses cognitive processes that are often siloed (working memory and long-term memory),
complementary temporally resolved methods (EEG and iEEG), and computationally sophisticated multivariate
analyses capable of sensitively decoding information in working memory. Finally, this research proposal will
develop innovative real-time tools to track information held in mind and forecast future long-term memory
performance. The short-term goal of this research proposal is to develop a composite model of how distinct
moment-by-moment subprocesses of working memory delay activity predict long-term memory outcome. This
will provide new insights into the relationship between working memory and long-term memory. The long-term
goal for my research program is to comprehensively characterize the diverse factors that influence what we
remember, in order to build tools that can enhance memory.

## Key facts

- **NIH application ID:** 10523326
- **Project number:** 1K99MH128893-01A1
- **Recipient organization:** UNIVERSITY OF CHICAGO
- **Principal Investigator:** Megan Teresa deBettencourt
- **Activity code:** K99 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $107,215
- **Award type:** 1
- **Project period:** 2022-07-08 → 2023-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10523326

## Citation

> US National Institutes of Health, RePORTER application 10523326, Long-term consequences of visual working memory (1K99MH128893-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10523326. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*