NeuroTech:Neuroscience at NSF

D. H. Whalen

Program Director, Cognitive Neuroscience

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.

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.

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.

“Grand Challenge” Areas

• Adaptive Plasticity.

• Conflict and Cooperation.

• Spatial Knowledge.

• Time.

• Language.

• Causal Understanding.

“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.

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.

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.

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.

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.

Conceptual and Theoretical Approaches

• Fundamental Role of Mathematics.

• Dynamical Systems.

• Statistical Physics/Large Degrees of Freedom.

• Engineering Approaches.

• Machine Learning Tools.

• Large-Scale Simulations.

Brain-Like Devices and Systems

• Analog Approaches.

• Stochastic Semiconductor Circuits.

• Neural Coding and Functional Biomimetic Systems.

• Brain-Like Robots.

• Biocompatible Neural Interfaces.

Now, Four Broad Areas

• Instrumentation and Measurement.

• Data Analysis, Statistical Modeling, and Informatics.

• Conceptual and Theoretical Approaches.

• Building Brain-Like Devices and Systems.

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.

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.

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.

Various Promising Topics

• Navigation and Spatial Cognition.

• Speech Perception.

• Face Recognition.

• Reading.

• Perception and Action.

• Number Skills.

• Tools for the Future.

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.

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.

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)

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”).

Support from Other Programs

• Cyber-enabled Discovery and Innovation

• Data-Net

• Community-based Data Interoperability Networks (INTEROP)

• Collaborative Research in Computational Neuroscience (CRCNS) (soon)

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).

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.

Thank you.