# Supplement: Topological bridges between circuits, models, and behavior

> **NIH NIH RF1** · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · 2022 · $408,101

## Abstract

Project summary (for this supplement)
 The goal of our parent grant (R01NS121913) is to use novel mathematical methods derived from
algebraic topology to uncover the relationship between cognition, behavior, and populations of neurons in
sensory and parietal cortex. Alzheimer’s disease (AD) affects many of the visual and cognitive functions that
are the focus of our basic science efforts, but the way affects neural populations is completely unexplored.
Doing so has the potential to transform the way AD is diagnosed and treated, because neural changes can
suggest specific behaviors that distinguish AD from related dementias or treatments that, for example, affect
the coordinated activity of neural populations in different brain areas (which is a function of stimulants that are
used to treat other neuropsychiatric disorders).
 Previous studies of AD have focused almost exclusively on anatomical or microscopic experiments in
animal models or in postmortem human tissue or on difficult to control behavioral experiments in human
patients, neither of which are good candidate for a neural population approach.
 Our collaborator, John Morrison at the California Primate Center, has developed a potentially
revolutionary monkey model of AD, in which disease progression is induced by injecting double-mutant human
tau into entorhinal cortex. This creates a remarkably similar progression of pathological disruption as does AD
in humans. Of particular interest is that this model shows microscopic changes in visual and parietal areas
during a 3-6 month period, which leads to our hypothesis that the neural and behavioral signatures of visual
perception and cognition that study in the parent project will be affected in this monkey model.
 This model provides an unprecedented opportunity to study the onset and progression of AD in a model
organism whose brain and visuospatial behavior is more similar to humans than other existing models. We
propose to record longitudinally from groups of neurons in three brain areas (visual areas V1, V4, and parietal
area 7a) before and during disease progression. We will develop and use a simple but flexible visual foraging
task that allows us to measure and manipulate many aspects of vision and cognition.
These studies have great potential for understanding the behavioral and neurophysiological changes that
occur during AD progression, and to lead to tools for early diagnosis and treatment of human patients. They
will also inform and enhance the basic science goals of our parent project by further constraining models and
informing mechanistic predictions that can be tested using a variety of methods in monkeys, mice, and models.

## Key facts

- **NIH application ID:** 10499278
- **Project number:** 3RF1NS121913-01S1
- **Recipient organization:** UNIVERSITY OF PITTSBURGH AT PITTSBURGH
- **Principal Investigator:** Marlene Rochelle Cohen
- **Activity code:** RF1 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $408,101
- **Award type:** 3
- **Project period:** 2021-05-01 → 2024-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10499278

## Citation

> US National Institutes of Health, RePORTER application 10499278, Supplement: Topological bridges between circuits, models, and behavior (3RF1NS121913-01S1). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10499278. Licensed CC0.

---

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