# Neural Mechanisms for memory-guided visual behavior in humans

> **NIH NIH K00** · COLUMBIA UNIV NEW YORK MORNINGSIDE · 2022 · $84,624

## Abstract

Project Summary
Memory allows us to use previous experience to guide current behavior. Computational models of episodic
memory propose that recalling an event from the past involves reinstating patterns of cortical activity that were
evoked when the event occurred. While there is considerable evidence for reinstatement within early sensory
areas, recent evidence suggests that reinstatement also occurs in higher-level regions, such as lateral parietal
cortex, that are strongly predictive of memory success. However, the significance of reinstatement in lateral
parietal cortex and its relation to reinstatement in sensory areas is not well understood. Understanding how
areas like lateral parietal cortex represent, transform, and prioritize information from sensory areas will be
critical to building a full model of how distributed brain networks support healthy and dysfunctional memory.
Addressing these gaps in understanding will require a multidisciplinary approach that relies on innovative fMRI
analyses, computational modeling, and integrating evidence from neuroimaging and electrophysiology. My
dissertation work so far has used fMRI approaches to test the hypothesis that lateral parietal cortex represents
sensory content during memory retrieval. This work has produced several significant results in favor of this
hypothesis and has involved the development of new fMRI methods. In the proposed research and training
program, I will use computational models of visual encoding to discriminate between competing hypotheses of
how topographic maps in parietal cortex encode spatial information during memory retrieval. This experience
will provide training in visual neuroscience and computational modeling, allowing me to develop expertise with
diverse approaches to studying episodic memory. In the proposed postdoctoral training phase, I will gain
theoretical and methodological training in electrophysiological measurements collected from humans. The
combination of fMRI and electrophysiology measurements will allow me to test novel hypotheses about how
memory signals propagate through time across distinct brain regions, and to generate findings that unify
research performed in human and non-human animal systems. This research program has significant potential
to generate novel understanding of the cortical mechanisms that support memory retrieval, to bridge findings
across measurements techniques, and to inform the treatment of aging- and disease-related memory
disorders. I am confident that the training provided by this research program will allow me to develop the
diverse theoretical and methodological expertise needed to conduct independent research on a core set of
questions in systems and cognitive neuroscience.

## Key facts

- **NIH application ID:** 10348760
- **Project number:** 5K00EY031607-05
- **Recipient organization:** COLUMBIA UNIV NEW YORK MORNINGSIDE
- **Principal Investigator:** Serra E Favila
- **Activity code:** K00 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $84,624
- **Award type:** 5
- **Project period:** 2017-09-28 → 2024-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10348760

## Citation

> US National Institutes of Health, RePORTER application 10348760, Neural Mechanisms for memory-guided visual behavior in humans (5K00EY031607-05). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10348760. Licensed CC0.

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