NeuroTech: Neuroscience at NSF

1. NeuroTech:Neuroscience at NSF D. H. Whalen Program Director, Cognitive Neuroscience

2. Current NSF Neuroscience • Across virtually all directorates. • About $60 million in FY06. • Difficult to assess, because neuroscience is not coded directly. • Depends on your definition as well, of course. • Even this number does not include centers. • Still not seen as a priority despite this rather large outlay.

3. Current Reassessment • Neuroscience at NSF is being examined Foundation-wide. • Objective: Redefine NSF’s mission in this area. • Takes NIH into account. • Input from most directorates. • Primary tools: three workshops.

4. Workshop 1: July 2006 • “Grand Challenges of Mind and Brain.” • Four member Steering Committee. • Sheila Blumstein (chair). • Thomas Carew. • Nancy Kanwisher. • Terry Sejnowski. • Twelve more in Workshop Panel. • Report available on CogNeuro web page.

5. “Grand Challenge” Areas • Adaptive Plasticity. • Conflict and Cooperation. • Spatial Knowledge. • Time. • Language. • Causal Understanding.

6. “Grand Challenge” Tools • Human Brain Circuitry. • Imaging, of course. • Also specifically mentions nonhuman species. • Mathematical Innovations. • Non-linear varieties in particular. • Information Databases. • Molecular Tools. • Cyberinfrastructure.

7. Workshop 2: August 2006 • Primarily MPS. • “Brain Science as a Mutual Opportunity for the Physical and Mathematical Sciences, Computer Science, and Engineering.” • Somewhat less grand. • Chaired by Chris Wood (Santa Fe Inst.). • Thirteen other participants. • Report available on CogNeuro website.

8. Three Broad Areas • A Shift in the Scope and Scale of Experimental Investigations. • Recordings from multiple events and sites. • A Shift in the Character of Theoretical Understanding. • Simultaneously bottom-up and top-down. • A Shift in How Knowledge Can Be Used. • Greater ability to model complex systems. • More potential for direct brain/machine links.

9. Instrumentation and Measurement • Functional measurements in neurons and circuits. • Labeling in neurons and circuits. • Controlling activity in neurons and circuits. • The importance of model organisms.

10. Data Analysis, Statistical Modeling and Informatics. • Multidisciplinary input to new measurement techniques. • Methods to integrate Diverse Data Sources. • Statistics, Signal Processing and Machine Learning. • New Tools for Control Theory. • Analyzing Multiple Levels and Time Scales. • Inferring Causality in Neural Systems. • New Approaches to Data Management/Sharing.

11. Conceptual and Theoretical Approaches • Fundamental Role of Mathematics. • Dynamical Systems. • Statistical Physics/Large Degrees of Freedom. • Engineering Approaches. • Machine Learning Tools. • Large-Scale Simulations.

12. Brain-Like Devices and Systems • Analog Approaches. • Stochastic Semiconductor Circuits. • Neural Coding and Functional Biomimetic Systems. • Brain-Like Robots. • Biocompatible Neural Interfaces.

13. Now, Four Broad Areas • Instrumentation and Measurement. • Data Analysis, Statistical Modeling, and Informatics. • Conceptual and Theoretical Approaches. • Building Brain-Like Devices and Systems.

15. Workshop 3: March 2007 • The workshop was organized around seven interdisciplinary themes, and led by: • Chris Wood, Vice President, Santa Fe Institute. • Ted Berger, Dept of Biomedical Engineering, USC. • Emery Brown, Dept of Brain/Cognitive Sciences, MIT. • Eve Marder, Dept of Biology, Brandeis University. • Tom Mitchell, Machine Learning, Carnegie Mellon U. • Partha Mitra, Cold Spring Harbor Laboratory. • Marcus Raichle, Dept of Radiology, Washington U. • Jonathan Sweedler, Dept of Chemistry, U. of Illinois.

16. Workshop 3: March 2007 • The workshop was organized around seven interdisciplinary themes, and led by: • Chris Wood, Vice President, Santa Fe Institute. • Ted Berger, Dept of Biomedical Engineering, USC. • Emery Brown, Dept of Brain/Cognitive Sciences, MIT. • Eve Marder, Dept of Biology, Brandeis University. • Tom Mitchell, Machine Learning, Carnegie Mellon U. • Partha Mitra, Cold Spring Harbor Laboratory. • Sheila Blumstein, Dept of Linguistics, Brown U. • Jonathan Sweedler, Dept of Chemistry, U. of Illinois.

17. SBE in this Workshop • Main working group of interest to SBE is Raichle’s/Blumstein’s: • “Cognitive Systems: Neural Bases of Thought and Behavior.” • Meant to convey the extensive interaction of systems seen in every cognitive domain. • Many other relevant topics in other working groups.

18. Various Promising Topics • Navigation and Spatial Cognition. • Speech Perception. • Face Recognition. • Reading. • Perception and Action. • Number Skills. • Tools for the Future.

19. The Big Question • How does the brain create thought and behavior? • Despite many interesting findings, the fundamentals are still not known. • Converging techniques, in imaging and in theory (e.g., complexity), are making new advances possible.

20. The Specific Big Question • As Dr. Bement asked at the workshop, how does consciousness arise? • Nancy Kanwisher, our presenter, pointed out that this is still too difficult a question to answer directly. • However, we have interesting components that have been located, such as face perception with and without awareness.

21. SBE: Cognitive Neuroscience • Most of the SBE-specific topics were in cognitive neuroscience, but not necessarily the Cognitive Neuroscience program: • Perception, Action and Cognition • Linguistics • Social Psychology • Economics • Decision, Risk and Management Sciences • Developmental and Learning Sciences • Cultural Anthropology • Physical Anthropology • Human Origins (HOMINID)

22. Other Potential Areas • Neural imaging of voting decisions. • Culturally-specific patterns of perception. • MRI lie detectors? • New statistical tools. • Neural study of ethics decisions. • Basic questions posed by diseases (“nature’s knock-out experiments”).

23. Support from Other Programs • Cyber-enabled Discovery and Innovation • Data-Net • Community-based Data Interoperability Networks (INTEROP) • Collaborative Research in Computational Neuroscience (CRCNS) (soon)

24. Challenges • Enormous area, dominated by biology. • Differentiating NSF from NIH. • Choosing right level of problem within SBE parameters. • International collaboration (at least, getting the word out, if not providing new mechanisms).

25. Opportunities • Additional funds may be forthcoming. • Partnering with European funders. • New tools and techniques may truly make future advances happen at a currently unimaginable pace. • 2010’s: Decade of the Mind.

26. Thank you.