# Impaired spatial decoding and neural population code rescaling in AD mice

> **NIH NIH K01** · COLUMBIA UNIVERSITY HEALTH SCIENCES · 2020 · $106,190

## Abstract

Impaired spatial decoding and neural population code rescaling in AD mice
Project Summary: Considerable evidence exists to support the notion that amyloid beta (Aβ) and tau pathology
impair neuronal circuit integrity and function in Alzheimer’s disease (AD). Unfortunately, few studies have tested
the direct influence of AD pathology on spatial computation within affected neuronal populations, resulting in an
information gap at the neuronal network level. Moreover, in vivo experiments that examine large scale, neuronal
network activity in mouse models of Aβ and tau pathology are lacking. In this proposal, I test the overarching
hypothesis that Aβ and tau associated neuronal network dysfunction impairs task-relevant, spatial
information encoding in large populations of neurons within the EC-HIPP circuit, and that combating
this aberrant activity can restore order and improve spatial information processing in AD mice. In Aim 1,
I will test the hypothesis that oligomeric forms of Aβ and tau disturb spatial information content encoded within
large populations of neurons in the entorhinal cortex – hippocampal (EC-HIPP) circuit. I will also test if these
oligomeric peptides alter the number of neurons recruited into the population code responsible for memory
encoding in a spatial learning and memory task. In Aims 2 & 3, I will leverage the predictive power of machine
learning to decipher the neural code for spatial information processing in EC-HIPP population activity.
Specifically, my goals in Aim 2 will be to examine the individual and combined impact of Aβ and tau pathologies
on features of spatial information encoding in the EC-Tau/hAPP mouse line. In Aim 3, I will employ
chemogenetics using a novel DREADDs ligand to combat aberrant neuronal activity in AD mouse models, with
the ultimate goal of improving spatial information processing in neuronal networks burdened with pathology.
Excitatory neurons will be specifically targeted in an effort to better understand their contribution to impaired
spatial information processing in AD mouse models.
 The proposed research aims are designed to bridge an information gap between AD-related cognitive
impairment and the underlying circuit pathology. This Mentored Research Scientist Development (K01) Award
will afford me the opportunity to accomplish this major goal while enriching my technical skillset and expanding
my knowledge of AD pathophysiology. In addition, the integrated training and mentorship that I will receive will
help me develop additional expertise in machine learning for spatial decoding analyses. Together, the proposed
studies and career development plan will ensure that I achieve my long-term career goal of launching a
competitive, independent research career at a major research university.

## Key facts

- **NIH application ID:** 10041102
- **Project number:** 1K01AG068598-01
- **Recipient organization:** COLUMBIA UNIVERSITY HEALTH SCIENCES
- **Principal Investigator:** Gustavo A Rodriguez
- **Activity code:** K01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $106,190
- **Award type:** 1
- **Project period:** 2020-08-15 → 2025-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10041102

## Citation

> US National Institutes of Health, RePORTER application 10041102, Impaired spatial decoding and neural population code rescaling in AD mice (1K01AG068598-01). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10041102. Licensed CC0.

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