Modeling structural and functional connectomics with proteomics in a preclinical model of tauopathy

Motivation: Identifying neurological changes in Alzheimer’s Disease (AD) is critical for early intervention. Tau accumulation is a key pathological feature in AD and other neurodegenerative diseases. Goal(s): This project investigates how tau accumulation impacts structural and functional connectivity in the brain and cognitive decline. Approach: We use behavioral assessments of learning and memory in the rTg4510 mouse model of tauopathy with awake resting-state fMRI and diffusion tensor imaging at three timepoints during the course of tau accumulation. Results: As tau accumulates, we identify patterns of functional connectivity changes. We plan to use machine learning to link these changes to cognitive decline. Impact: We study how tau accumulation affects brain functional connectivity and cognitive decline in a mouse model of tauopathy. Magnetic resonance imaging may offer non-invasive tools for assessing Alzheimer's Disease pathology, potentially aiding in early diagnosis.