# Semantic contributions to episodic memory

> **NIH NIH F32** · UNIVERSITY OF PENNSYLVANIA · 2020 · $15,032

## Abstract

This application describes a 3-year training plan that will enable me, a cognitive neuroscientist with a
background in memory consolidation and neuroimaging methods, to conduct research on the interaction
between semantic knowledge and episodic memory. Co-supervised by Dr. Sharon Thompson-Schill, an expert
in the field of the cognitive and neural organization of concepts and semantic knowledge, and Dr. H. Branch
Coslett, a neurologist with extensive experience in brain stimulation, I propose to examine how semantic
knowledge shapes new episodic memories, and how changes their cortical representation may determine the
extent to which episodic memories are influenced by semantic knowledge. The proposed experiments aim to
address two gaps in the literature on semantic knowledge and episodic memory consolidation. First, memory
consolidation research typically treats new episodic memories as distinct (orthogonalized) from other past
experiences, when in reality, episodic memories are virtually always made up of re-combinations of elements
(e.g. locations, places, objects) for which we already have acquired rich semantic knowledge. How such
semantic elements interact with, or bias, new episodic elements in memories over time is unclear. Second,
past work investigating the role of prior knowledge on new memories is often focused on how prior knowledge
facilitates the encoding and retrieval of new memories, rather than how they may be biased by prior
knowledge. To address this limitation of prior work, I propose a series of experiments that probe how semantic
knowledge systematically biases episodic memories, and how this bias may be influenced by the
representation of the memory in the anterior temporal lobe (ATL), a cortical structure critical for intact semantic
knowledge. In Aim 1, I propose a behavioral experiment that leverages the hierarchical organization of
semantic knowledge, namely category typicality and levels of abstraction, to understand how semantic
knowledge influences new episodic memories. I employ a continuous measure of retrieval to disentangle
biases driven by semantic knowledge from errors due to forgetting. In Aim 2, I adapt this experiment for
patients with post-stroke lesions to understand how specific impairments in category knowledge influence
retrieval. While I outline specific predictions for patients with greater extent of damage in ATL, I adopt an
exploratory approach to identify other potential sites of integration between semantic and episodic information.
In Aim 3, I employ transcranial magnetic stimulation to test whether episodic memories are more biased by
semantic knowledge as they become increasingly represented in ATL over time. The proposed research will
contribute to our understanding of the neural mechanisms underlying the contributions of semantic knowledge
to new episodic memory, and it may inspire novel rehabilitation strategies for individuals suffering from memory
impairments.

## Key facts

- **NIH application ID:** 10026293
- **Project number:** 5F32NS108511-02
- **Recipient organization:** UNIVERSITY OF PENNSYLVANIA
- **Principal Investigator:** Alexa Tompary
- **Activity code:** F32 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $15,032
- **Award type:** 5
- **Project period:** 2019-09-30 → 2020-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10026293

## Citation

> US National Institutes of Health, RePORTER application 10026293, Semantic contributions to episodic memory (5F32NS108511-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10026293. Licensed CC0.

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