Professor Eli Upfal of Brown University's Department of Computer Science and his collaborators, Jerome Sanes of the Department of Neuroscience and Xi Luo of the Department of Biostastistics, have just received a Brown Institute for Brain Science Innovation Award. It supports their recent work ("Advanced Neuroimaging of Functional Connectivity and Networks") with funding aimed at helping launch new, creative research projects with great potential that are too risky for external funding sources.
The project stands at the forefront of recent efforts to better understand the activity of specific neural networks in the brain and how they change dynamically during learning.
"It's a collaboration," explains Upfal, "combining expertise in brain imaging, biostatistics, and computer science to create new methods for analyzing this activity. We're going to develop and implement an integrated and scalable computational and statistical framework to assess activity in local and longer-range brain networks, as revealed through simultaneously recorded electroencephalography and functional magnetic resonance imaging (fMRI) signals in humans while they learn and perform action sequences. Then, we'll integrate these activity maps with anatomical information about interconnections in the brains of individual people using a specific MRI technique called diffusion spectrum imaging."
"Our goal," he says, "is to track brain activity associated with specific tasks as it flows through large regions of the brain in real time and show how it changes dynamically as people learn or change their attention."