BrainHub Engineers Receive NSF Grant To Study Neuron Variability and Motor Learning
Grant Is Part of the NSF’s Support of the BRAIN InitiativeBy Jocelyn Duffy / 412-268-9982 / email@example.com
When we move, we rarely move in the exact same way twice. The National Science Foundation (NSF) has awarded Carnegie Mellon University Assistant Professor of Biomedical Engineering Steven Chase and Associate Professor of Electrical and Computer Engineering and Biomedical Engineering Byron Yu, and their long-time collaborator, University of Pittsburgh Associate Professor of Bioengineering Aaron Batista, an $869,000 grant to conduct basic research that will establish how variability in movement is encoded in the brain and how this variability contributes to learning and performance.
The award is one of 16 NSF grants totaling $13.1 million to support potentially transformative research in neural and cognitive systems. The awards are among the first from the cross-disciplinary NSF Integrative Strategies for Understanding Neural and Cognitive Systems program, which is part of the NSF’s support of the federal BRAIN Initiative.
“These teams are building on creative ideas from within and beyond neuroscience,” said Kenneth Whang, NSF program director in the Computer & Information Science & Engineering Directorate, which co-funds the awards. “We're seeing some dynamic new research collaborations that will have huge impacts on fundamental questions, and on what we can discover or invent in the future.”
“On the surface, variability seems like it could be a detriment to reliable, short-term performance. But, if we look closer, variability also promotes learning by encouraging us to explore different movements in order to find out the most efficient and effective way to move.” — Steven Chase
The CMU-led team, which is made up of researchers from the university’s BrainHubSM initiative and the University of Pittsburgh, will bring together expertise in neuroscience, engineering and computer science to establish a fundamental understanding of neural variability in motor learning.
“Movements are inherently variable. If you threw a dart the exact same way every time, you’d either always get a bulls-eye or never get one,” said Chase, who is a member of the joint CMU/University of Pittsburgh Center for the Neural Basis of Cognition. “On the surface, variability seems like it could be a detriment to reliable, short-term performance. But, if we look closer, variability also promotes learning by encouraging us to explore different movements in order to find out the most efficient and effective way to move.”
Chase, Yu and Batista will take recordings from neurons in the motor and premotor cortices of an animal model as it performs movement-related tasks. They will use these recordings to establish how variability in neuronal responses exists, with the hopes of establishing connections between variability, performance and learning.
As the birthplace of artificial intelligence and cognitive psychology, Carnegie Mellon has been a leader in the study of brain and behavior for more than 50 years. The university has created some of the first cognitive tutors, helped to develop the Jeopardy-winning Watson, founded a groundbreaking doctoral program in neural computation, and completed cutting-edge work in understanding the genetics of autism. Building on its strengths in biology, computer science, psychology, statistics and engineering, CMU recently launched BrainHubSM, a global initiative that focuses on how the structure and activity of the brain give rise to complex behaviors.