Shella Keilholz, associate professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory, has been selected to receive up to $40,000 from the Georgia Tech Fund for Innovation in Research and Education (GT FIRE). The program has two purposes. The first aims to facilitate planning for large extramural proposals — those that are of strategic value to the Institute. The second provides support for feasibility studies of transformative ideas in research or education.
“Innovation in research is critical for us to lead and set the science, technology and policy agenda for the United States and the world,” said Steve Cross, executive vice president for research at Georgia Tech.
“With our improved understanding of resting state functional magnetic resonance imaging (rs‐fMRI), we have come to realize that the blood oxygenation level dependent signal that is the basis for rs‐fMRI contains multiple components that correspond to brain function at different spatial and temporal scales,” said Keilholz. “Multiple levels of information can be extracted from a single, noninvasive rs‐fMRI scan, providing unprecedented insight into the brain’s functional architecture.”
To truly understand the interactions within and between processes, she wants to build a data‐based model that captures the complexity of the system and allows testable predictions about how network activity will respond to perturbation.
The outcome of this work will be a model based on rs‐fMRI data and designed to explicitly capture multiple spatial and temporal scales of activity along with a new method for characterizing the spatiotemporal evolution of brain activity. This project is an excellent fit for BRAIN Initiative proposals, which emphasize multidisciplinary, multiscale, multimodal approaches to understanding brain function. It is also in line with the joint NIH/NSF Collaborative Research in Computational Neuroscience program. Her team, along with other researchers, will use the period of GT FIRE funding to develop and test an initial model which will serve as preliminary data for one or more proposals that can provide sustained funding.
The development of a predictive model of brain function is one of the holy grails of neuroscience. Eventually, she hopes scientists can routinely examine the network dynamics in the brain on an individual basis, partly in order to understand variations in cognitive activity, but also to find and ultimately fix deficits induced by dysfunction. They want to create models for individual patients that can be used for diagnosis, evaluation, and even treatment of psychiatric and neurological disorders.
This project is an excellent fit with Georgia Tech’s recent initiatives in high performance computing, big data, and data science. It leverages the established connection between the engineers at Georgia Tech and the clinicians at Emory facilitating translation.
According to Keilholz, “we are one of the groups with the most expertise at understanding multiscale brain function, and our collaboration with experts in nonlinear dynamics and complex networks will allow us to take on a project that no other group has been able to tackle yet.”
Wallace H. Coulter Department of Biomedical Engineering
Georgia Institute of Technology