VISE researchers receive $1M grant to explore brain-body connections and advance understanding of how brains age
An assistant professor of electrical and computer engineering has received a $1.1 million NIH grant to investigate connections between the brain and body to advance the understanding of aging in normal and pathological brains.
Catie Chang, assistant professor of electrical and computer engineering, leads the research team, which will focus on developing machine learning methods that can automatically reconstruct physiological signals from functional magnetic resonance imaging (fMRI) data.
Increased availability of large datasets from fMRI has supported deeper research into functional systems of the human brain. Changes in breathing and heart rate are known to perturb fMRI measurements of brain activity, yet such physiological effects are often disregarded as confounds or noise in functional imaging studies.
“fMRI signals related to breathing and heart rate are often discarded, but there is increasing recognition that they may carry valuable information about brain health,” Chang said.
The research team includes co-investigator Yuankai Huo, assistant professor in computer science and consultant, and Bennett Landman, professor of electrical and computer engineering, as well co-investigator Mara Mather from the University of Southern California. She is a professor of gerontology, psychology, and biomedical engineering.
Vanderbilt graduate students Roza Bayrak and Sarah Goodale and postdoctoral researcher Jorge Salas (NEURDY Lab) contributed key ideas and methods to the proposal and direction of this research.“I am excited for the potential of this project to increase our understanding of aging and Alzheimer’s disease, and to create new tools for studying physiological effects.”
Such tools could enhance the large amount of existing fMRI datasets with information about physiology and brain-body interactions.
This project is funded by the National Institutes of Health (NIH RF1MH125931-01A1 BRAIN Initiative R01).