Modeling functional connectivity with learning and memory in a mouse model of Alzheimer's disease
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.
Authors
- Elizabeth Hipskind (ORCID: https://orcid.org/0000-0002-7859-529X)
- Steen E. Pedersen (ORCID: https://orcid.org/0000-0001-8755-8899)
- Eric Shin
- Jonathan Romero (ORCID: https://orcid.org/0000-0001-7044-8765)
- Lindsay Fadel
- Caitlyn Ortiz
- Robia G. Pautler (ORCID: https://orcid.org/0000-0001-7952-8526)
- Md. Abul Hassan Samee (ORCID: https://orcid.org/0000-0002-7472-1156)
Institutions
- Baylor College of Medicine (US)
- Texas Children's Hospital (US)
Publication Details
- Journal
- Frontiers in Neuroimaging
- Published
- 2025-04-25
- DOI
- https://doi.org/10.3389/fnimg.2025.1558759
- Citations
- 3
- Primary Topic
- Functional Brain Connectivity Studies
- Type
- article
- Field-Weighted Citation Impact
- 4.29
Funders
- Texas Children's Hospital
- National Institutes of Health
- National Institute on Aging