Arkansas, New Mexico Researchers Part of Teams Awarded NSF Funding for New Multi-Discilinary Approaches to Study the Brain
The National Science Foundation (NSF) made 19 awards to cross-disciplinary teams from across the United States to conduct innovative research focused on neural and cognitive systems. Each award provides a research team with up to $1 million over two to four years.
The awards will contribute to NSF's investments in support of Understanding the Brain and the BRAIN Initiative, a coordinated research effort that seeks to accelerate the development of new neurotechnologies.
The awards will advance frontiers in cognitive science and neuroscience with an emphasis on four themes:
- Neuroengineering and brain-inspired concepts and designs.
- Individuality and variation.
- Cognitive and neural processes in realistic, complex environments.
- Data-intensive neuroscience and cognitive science.
The award titles, principal investigators and sponsor institutions are listed below.
- Ground-truth analysis and modeling of entire individual C. elegans nervous systems: Edward Boyden of Massachusetts Institute of Technology and Albert-Laszlo Barabasi of Northeastern University
- Decoding and reconstructing the neural basis of real world social perception: Avniel Ghuman of University of Pittsburgh and Max G'Sell of Carnegie Mellon University
- Relationship of cortical field anatomy to network vulnerability and behavior: Thomas Grabowski of University of Washington and Wanpracha Chaovalitwongse of University of Arkansas
- Understanding the neural basis for sensorimotor control loops using whisker-based robotic hardware platforms: Mitra Hartmann of Northwestern University and Sarah Bergbreiter of University of Maryland, College Park
- A neurally inspired, event-based computer vision pipeline: Garrett Kenyon of the New Mexico Consortium and Michael Flynn of University of Michigan Ann Arbor
- Neurobehavioral integration of visual and semantic number knowledge and its role for individual variation in the math ability of children and adults: Melissa Libertus of University of Pittsburgh
- A computational theory to model the neurobiological basis of a visuo-cognitive neuroprosthetic: Stephen Macknik of SUNY Health Science Center at Brooklyn
- Active listening and attention in 3-D natural scenes: Cynthia Moss of Johns Hopkins University
- Seizure control through state-specific manipulation of cell assemblies: Sarah Muldoon of SUNY at Buffalo and Ethan Goldberg of The Children's Hospital of Philadelphia
- Super resolution mapping of multi-scale neuronal circuits using flexible transparent arrays: Piya Pal of University of California, San Diego
- Connecting spikes to cognitive algorithms: Il Memming Park of SUNY at Stony Brook and Alexander Huk of University of Texas at Austin
- Connectome mapping algorithms with application to community services for big data neuroscience: Franco Pestilli of Indiana University
- Integrative foundations for interactions of complex neural and neuro-inspired systems with realistic environments: Terrence Sejnowski of The Salk Institute for Biological Studies and John Doyle of California Institute of Technology
- Data-driven modeling of visual cortex: Robert Shapley of New York University
- Extracting functional cortical network dynamics at high spatiotemporal resolution: Jonathan Simon of University of Maryland, College Park
- Neuroimaging to advance computer vision, NLP and A.I.: Jeffrey Siskind of Purdue University
- Fully passive and wireless multi-channel neural recording for chronic in-vivo studies in animals: John Volakis of Ohio State University and Junseok Chae of Arizona State University
- The impact of real world stressors on problem-solving: Ying Choon Wu of University of California, San Diego
- Volitional modulation of neural activity in the visual cortex: Byron Yu of Carnegie Mellon University and Matthew Smith of University of Pittsburgh