Imaging the Heart–Brain Connection and Metabolic Modulation

Timeline

2026

Description

A team of students led by researchers in the Quantitative Imaging and Analysis Laboratory will use deep learning to decode the 'neurocardiac circuits' that link cardiometabolic health to cognitive aging. By relating heart metrics from cardiac imaging to brain data, students will identify how metabolic health modulates pathways that influence healthy aging and deviations from normal aging. This work will bridge data science and biology to build predictive models of cognitive resilience, providing a foundation for new strategies in healthy aging.

View the team's poster here:

HeartBrainImg.pdf (2.77 MB)

Team

Members

Aidan Lee, Harbor Gao, Jimin Xu, Yu Liang

Leaders

Project Lead: Alexandra Badea

Project Manager: Rohan Nadkarni (BME)