NSF Funds $1.2 M in UMD Work on Neural Engineering of Complex Behaviors
Three University of Maryland engineers have been awarded new National Science Foundation (NSF) grants to research how human neural and cognitive systems interact and intersect with advances in engineering, computer science and education.
Lee Tune , 301-405-4679 email@example.com
Three University of Maryland engineers have been awarded new National Science Foundation (NSF) grants through an NSF program that fosters research on how human neural and cognitive systems interact and intersect with advances in engineering, computer science and education.
These grants are among 19 NSF awards issued to U.S. cross-disciplinary teams to conduct work that is “bold, risky, and transcends the perspectives and approaches typical of single-discipline research efforts.” According to the agency, the awards will contribute to NSF’s investments in fundamental brain research, in particular support of Understanding the Brain and the BRAIN Initiative, a coordinated research effort that seeks to accelerate the development of new neurotechnologies.
Professor Jonathan Simon, who holds joint appointments in electrical and computer engineering (ECE), biology and UMD’s Institute for Systems Research (ISR), and Assistant Professor Behtash Babadi, who holds joint appointments in ECE and ISR, have received a $900,000 grant for research that will take advantage of recent advances in noninvasive neuroimaging to learn more about how the brain’s neural mechanisms work in adaptive auditory processing. Simon and Babadi are two of more than 140 UMD faculty in the university’s Brain and Behavior Initiative, which seeks to revolutionize the interface between engineers and neuroscientists by generating novel tools and approaches to understand complex behaviors produced by the human brain.
UMD Associate Professor Sarah Bergbreiter, who holds a joint appointment in mechanical engineering and ISR, and two colleagues from Northwestern University, L. Catherine Brinson and Mitra Hartmann, were awarded a $1,000,000 grant to better understand how animals use the sense of touch to gather information and then use this information to perform complex behaviors. The University of Maryland’s portion of the grant is $320,000.
Using brain imaging to study how our brains adapt to varying sound environments
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 between these regions that can dynamically reconfigure. These networks allow humans to rapidly adapt to changes in their sound environment, such as when walking from a quiet street into a noisy party. Currently, little is known about the workings of these brain networks, which bind, organize, and give meaning to higher cognitive functions.
Adaptive auditory processing is one such higher function. It is 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. And it is in this area that the new NSF funding will support new research by Simon and Babadi.
“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 [brain] 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 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.”
Neuromorphic engineering is the use of a very large-scale system of integrated circuits to mimic neuro-biological architectures present in the nervous system.
Using robotic whiskers to help understand how animal brains’ use real ones
The research by Bergbreiter and her two Northwestern colleagues will advance understanding of how animals first gather information through the sense of touch and then how the use this information to perform complex behaviors. At Maryland, Bergbreiter will be developing artificial, modular, reconfigurable whiskers that imitate the functions of animal whiskers.
The whiskers will be mounted on robotic platforms that can mimic the head movements of animals, contributing to the development of novel robots and sensors that use touch to sense an object’s location, shape, and texture, to track fluid wakes in water, and to sense the direction of airflow.
“Engineering arrays of sensors to serve as physical models of a rat's whiskers will allow us to better understand the connections between what a rat senses and its actions,” Bergbreiter says. “Using this understanding, we can design robots with the ability to explore dark areas or work in other challenging environments that require a sense of touch or flow.”
The NSF Neural and Cognitive Science Program
The complexities of brain and behavior pose fundamental questions in many areas of science and engineering, drawing intense interest across a broad spectrum of disciplinary perspectives while eluding explanation by any one of them. Rapid advances within and across disciplines are leading to an increasingly interconnected fabric of theories, models, empirical methods and findings, and educational approaches, opening new opportunities to understand complex aspects of neural and cognitive systems through integrative multidisciplinary approaches. According to NSF this program seeks to support innovative, integrative, boundary-crossing proposals that can best capture those opportunities.
"It takes insight and courage to tackle these problems," said Ken Whang, NSF program director in the Computer and Information Science and Engineering Directorate (CISE). "These teams are combining their expertise to try to forge new paths forward on some of the most complex and important challenges of understanding the brain. They are posing problems in new ways, taking intellectual and technical risks that have huge potential payoff."
Brain and Behavior Information Systems Machine Learning Mechanical Engineering Robotics Research
A. James Clark School of Engineering Brain & Behavior Institute
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