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NSF NCS: Extracting Functional Cortical Network Dynamics at High Spatiotemporal Resolution

Funding Agency 

National Science Foundation

Description 

Professor Jonathan Simon (ECE/Biology/ISR) and ISR-affiliated Assistant Professor Behtash Babadi (ECE) have received a $900,000 grant for research that will take advantage of recent technological advances in noninvasive neuroimaging to learn more about how the brain’s neural mechanisms work in adaptive auditory processing. It is one of 19 research grants announced Aug. 8, 2017 by the National Science Foundation through its Integrative Strategies for Understanding Neural and Cognitive Systems (NCS) program. The grants are an indication of the university’s current and growing strengths in brain and behavior research, robotics and mechanical and electrical engineering. Maryland's portion of these grants is worth more than $1.2 million.

Recent, growing evidence suggests that sophisticated brain functions happen when more than one region of the brain is activated at the same time, and the brain forms networks that dynamically reconfigure between these regions. These networks allow humans to rapidly adapt to changes in the environment. Currently, little is known about the workings of these networks that bind, organize, and give meaning to higher cognitive functions.

Adaptive auditory processing is one such function. It the brain’s ability to attend to, segregate, and track one of many sound sources, to learn its identity, commit it to memory, robustly recognize it, and use it to make decisions.

“Deciphering the neural mechanisms underlying the brain’s network dynamics is critical to understanding how the brain carries out universal cognitive processes such as attention, decision-making and learning,” notes Simon. “However, the sheer high-dimensionality of dynamic neuroimaging data, together with the complexity of these networks, has created serious challenges, in practice, in its data analysis, signal processing, and neural modeling.”

The researchers will use modern signal processing techniques to combine high temporal resolution, non-invasive recordings with high spatial resolutions.

“Our work will bring new insight as to the dynamic organization of cortical networks at unprecedented spatiotemporal resolutions, and can thereby impact technology in the areas of brain-computer interfacing and neuromorphic engineering,” says Babadi. “It will also allow for the creation of engineering solutions for early detection and monitoring of cognitive disorders involving auditory perception and attention.”