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Model Students
Model Students
Computational Brain Health Graduates Join New Fellowship

Photography by Agsandrew/istock.com

By Shavantay Minnis

Aided by a $1M gift from the Palm Health Foundation, graduate students sponsored by the FAU Stiles-Nicholson Brain Institute are using sophisticated computational modeling techniques to understand the origins and treatment of brain disorders.

Gifted last fall by the Palm Health Foundation (PHF) Brain Health Innovation Fund, the institute launched its inaugural Computational Brain Science and Health Graduate Fellowships. PHF’s award aims to support new technologies, treatments, resources and educational tools that advance brain health in the community.

“With generous support from PHF, we are training talented junior researchers who will contribute important knowledge and discoveries that will help to address some of our most pervasive and debilitating brain disorders,” said Randy D. Blakely, Ph.D., executive director, FAU Stiles-Nicholson Brain Institute and a professor in biomedical science of FAU’s Schmidt College of Medicine.

Recently four doctoral students: Jasmine Chan, Hadi Esfandi, Joseph McKinley and Yosun Yoon became Palm Health Fellows. They will collaborate with FAU faculty researching brain mechanisms and disorders using cutting edge computational tools.

Chan, a fourth-year graduate student, focuses her work on using machine learning to dissect the patterns of brain activity in Alzheimer’s disease patients. Esfandi in his third year as a graduate student utilizes a computational model to understand how brain cells control the flow of blood to support neural function and health, and how when altered it affects Alzheimer’s.

McKinley, another fourth-year graduate student, is developing computational models to provide a theoretical foundation for the dynamic responses to neurostimulation, a health intervention that disrupts pathological states of neuronal activity seen when treating Parkinson’s disease.

Lastly, Yoon, in her final year as a graduate student is using a non-invasive brain stimulation technique to examine and model how the frontoparietal network synchronizing alters cognitive flexibility, a goal relevant to the treatment of multiple learning and mood disorders.

“These outstanding doctoral students will gain important experience in using data-intensive, computational approaches to model neural function and dysfunction, joining the battle to diagnose and treat brain disorders that range from those affecting the brain in early development to those impacting the minds of seniors,” Blakely said.

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