Modeling Functional Connectivity With Learning and Memory in a Mouse Model of Alzheimer’s Disease

Authors

Lindsay Fadel
Elizabeth Hipskind
Steen E Pedersen
Jonathan Romero
Caitlyn Ortiz
Eric Shin
Md Abul Hassan Samee
Robia G Pautler

Language

English

Publication Date

1-1-2025

Journal

Frontiers in Neuroimaging

DOI

10.3389/fnimg.2025.1558759

PMID

40353249

PMCID

PMC12062036

PubMedCentral® Posted Date

4-25-2025

PubMedCentral® Full Text Version

Post-print

Abstract

Introduction: Functional connectivity (FC) is a metric of how different brain regions interact with each other. Although there have been some studies correlating learning and memory with FC, there have not yet been, to date, studies that use machine learning (ML) to explain how FC changes can be used to explain behavior not only in healthy mice, but also in mouse models of Alzheimer's Disease (AD). Here, we investigated changes in FC and their relationship to learning and memory in a mouse model of AD across disease progression.

Methods: We assessed the APP/PS1 mouse model of AD and wild-type controls at 3-, 6-, and 10-months of age. Using resting state functional magnetic resonance imaging (rs-fMRI) in awake, unanesthetized mice, we assessed FC between 30 brain regions. ML models were then used to define interactions between neuroimaging readouts with learning and memory performance.

Results: In the APP/PS1 mice, we identified a pattern of hyperconnectivity across all three time points, with 47 hyperconnected regions at 3 months, 46 at 6 months, and 84 at 10 months. Notably, FC changes were also observed in the Default Mode Network, exhibiting a loss of hyperconnectivity over time. Modeling revealed functional connections that support learning and memory performance differ between the 6- and 10-month groups.

Discussion: These ML models show potential for early disease detection by identifying connectivity patterns associated with cognitive decline. Additionally, ML may provide a means to begin to understand how FC translates into learning and memory performance.

Keywords

Alzheimer's disease, rs-fMRI, functional connectivity, modeling, behavior, mouse model

Published Open-Access

yes

Recommended Citation

Fadel, Lindsay; Hipskind, Elizabeth; Pedersen, Steen E; et al., "Modeling Functional Connectivity With Learning and Memory in a Mouse Model of Alzheimer’s Disease" (2025). Faculty and Staff Publications. 723.
https://digitalcommons.library.tmc.edu/baylor_docs/723