Remarks

[Slide 1: Title]
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I'm so pleased to be here. It’s great to see so many friends and colleagues. And I'm just as delighted to meet those of you who are just starting your careers in neuroinformatics! This is an exploding field that will thrive on fresh talent.

I'd like to thank Professor Sten Grillner for inviting me to speak with you today. When Sten calls, I listen! He has provided exceptional leadership for INCF, and we all owe him our gratitude for helping to put neuroinformatics on the global map.

Today I want to say a few words about past contributions to neuroscience and neuroinformatics, and highlight our current challenges. The past and the present can help us map an exciting future in neuroinformatics.

I'll focus on neuroscience activities at the U.S. National Science Foundation--my balliwick--but mention important collaborations with the National Institutes of Health (NIH) and others. NSF has an important role in expanding the frontiers of basic neuroscience and Neuroinformatics research.

[Slide 2: History of Neuroscience & Neuroinformatics #1]
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NSF gave its first award in neuroscience in 1951. We were also the first U.S. federal agency to support brain science and neuroscience, in general, during the decade of brain.

A whole host of programs were formed during this period: Molecular Neuroscience, Integrative Neurosciences, Behavioral Neuro-endochronology, and the Cognitive and Theoretical Neuroscience programs, to name a few. That isn't too long ago when you consider the age of many scientific disciplines.

[Slide 3: History of Neuroscience & Neuroinformatics #2]
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This slide brings us up to present-day.

I want you to note two dates here. First, in 2001, NSF and the National Institutes of Health launched an important joint effort called Collaborative Research in Computational Neuroscience. I'll talk about that later.

Second, in 2004 the international drafting committee for the International Neuroinformatics Coordinating Facility met for the first time and INCF was born! You may recall that in 2002, the INCF was recommended by the US-led Global Science Forum Neuroinformatics Working Group.

[Slide 4: Where are we headed now?]
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The Decade of the Brain and other research efforts ushered in some astounding new discoveries, but they didn't fundamentally change the way we do neuroscience. In other words, EVERYTHING HAS CHANGED!

• Complex
• Large-scale and multi-scale
• Interdisciplinary, and
• Collaborative.

Neuroscience challenges are complex, large-scale scientific and engineering opportunities with broad scientific interest and societal impact.

A wide range of traditionally unrelated disciplines are now engaged in neuroscience research (e.g. physics, computer science, engineering, chemistry, mathematics).

Collaborations are now the norm, and many are international in scope.

Major improvements in tools and techniques have made significant advances.

Today, large data sets are increasingly available, and there are many analysis and visualization tools across multiple temporal and spatial scales.

[Slide 5: What is driving progress...]
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New tools and techniques are now driving progress in neuroscience. Computer and networking technologies--combined with new imaging tools that generate vast quantities of observational and experimental data--have opened up entirely new horizons.

[Slide 6: Complexity spiral]
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We are now in a new era of discovery, innovation and promise. We are beginning to unravel the mysteries of complexity, and learning how to link phenomena across time and space.

We can foresee, in the not too distant future, the development in neuroscience of the comprehensive, multi-scale models that are the Holy Grail of all fields of science today.

[Slide 7: BCI Grand Challenges]
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Recently the US National Academy of Engineering compiled a list of 13 Engineering Grand Challenges. One of these is "Reverse engineer the brain." Now, that's what I call a GRAND challenge.

Beginning in December 2005, NSF organized and supported a series of benchmarking meetings to evaluate the current and future status of Brain-Computer Interface research in North America, Europe and Asia. Among other visits, the team paid a call to Dr. Henry Markram's lab to have a look at the Blue Brain.

Here you see the Grand Challenges that emerged from these meetings. Clearly, these are highly detailed and refined problems for multi-disciplinary teams to solve as they move towards the larger goal of "Reverse Engineering the Brain."

One of the top priorities for the Neuroscience and neuroinformatics communities should be to articulate a broad set of Grand Challenges that covers the entire field.

[Slide 8: The purpose of all this....Transformative Discoveries]
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Formulating "Grand Challenges" can guide us in designing specific research efforts. For one thing, it can help us keep our eyes on the prize: Transformative Discoveries.

NSF's goal is nothing short of supporting transformational research--that's research that requires THINKING OUTSIDE the NORM.

The new era of interdisciplinary engineering and neuroscience is right in line with NSF's vision and mission--to support frontier research that is transformational discovery and learning at the fringe. We lead the U.S. effort to develop the fundamental building blocks that drive innovation.

That means supporting research that can radically change our understanding of an existing scientific or engineering concept, or lead to a new paradigm or new discipline.

[Slide 9: Transformative Research]
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In other words, we aim to support those endeavors that have the potential to change the way we address challenges in science and engineering and also provide grist for the innovation mill. Supporting transformative research is of critical importance in the fast-paced, science and technology-intensive world of the 21st Century.

[Slide 10: NSF]
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At NSF, we can bring to bear the necessary scientific, computational, mathematical and engineering disciplines to explore the interface between engineering, the physical sciences and the life science.

Just consider these opportunities:

• The life-blood of the NSF enterprise is support for research.
  
  
• We also invest in instrumentation and cyber-infrastructure to get the job done.
  
  
• We are unique in encouraging education and training elements in every research program we support.
  
  
• We have strong programs for the development of partnerships and Centers.
  
  
• And, we strongly encourage international collaboration.
  
  

[Slide 11: All this and more...]
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In fact, we are the only federal agency mandated to support all fields of basic science and engineering...from A to Z...astronomy to zoology.

We invite proposals for research and education projects in all fields of science and engineering. We support work in each of your fields, and have throughout our history.

This breadth has given us the confidence to be leaders in supporting work at the interface among disciplines. In fact, we are often the first to see these connections and opportunities arise.

[Slide 12: NSF Programs for Advancing Neuroinformatics]
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I'd like to say a few words now about our neuroscience activities at NSF.

NSF has a rich and varied portfolio of brain research--from the study of creativity to computational neuroscience. To bring together everything we know about the mind, and everything we have yet to discover, we need powerful techniques for processing vast amounts of information, and cyberinfrastructure to share those resources broadly.

Here are five from that rich diversity!

• Collaborative Research in Computational Neuroscience (CRCNS)
• Cognitive Optimization and Predication: From Neuro Systems to Neurotechnology (COPN)
• Adaptive Systems Technology (AST)
• Cyber-enabled Discovery & Innovation (CDI)
• Cyberinfrastructure

[Slide 13: CRCNS]
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Now let me turn to a few examples.

The joint NSF-NIH Collaborative Research in Computational Neuroscience program is one attempt to pursue collaboration driven by scientific challenges. At the same time, the program aims to take advantage of opportunities provided by the current resource and data-rich research environment to promote truly innovative research.

Collaboration is at the heart of the program. Projects crossing traditional academic boundaries often bring about increased creativity—and productivity—because scientists and engineers from different fields bring widely varying experience and training to projects. In this case, the program also brings together researchers from the NSF and NIH communities.

[Slide 14: CRCNS so far...]
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Here is a snapshot of CRCNS achievements so far.

There have been five competitions so far, beginning in 2002. Two more are slated for 2009 and 2010.

The program has funded 92 collaborative research projects, with an investment of more than $100M in US funding.

These projects cover a broad spectrum of multidisciplinary topics and approaches.

Just recently, we added a new data-sharing component to the program.

[Slide 15: crcns.org and Data Sharing Neuroscience]
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NSF is a "bottoms-up" organization. We listen to the community to discover the best ideas and to meet the most pressing needs. Interest in data-sharing came from the computational neuroscience community. We responded.

In June 2007, we sponsored a workshop that led to the launch of crcns.org and the CRCNS data sharing track.

The crcns.org portal provides services and infrastructure for sharing computational neuroscience data. The hub is being developed by Fritz Sommer and colleagues at the Redwood Center at UC-Berkeley.

Crcns.org and the first shared data resources made their debut in March 2008.

[Slide 16: Emerging Frontiers in Research and Innovation]
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Now, let me turn to EFRI, Emerging Frontiers in Research and Innovation. This program is one of the first at NSF that aims specifically to stimulate transformative research.

Transformative research is generally riskier, but the reward in path-breaking knowledge is also higher.

One of the topics for the 2008 EFRI awards is Cognitive Optimization and Prediction: From Neural Systems to Neurotechnology, or COPN for short.

COPN aims to understand how massively parallel circuits in brains address complex tasks in adaptive optimal decision-making and prediction.

The program hopes to stimulate and enlarge the new interdisciplinary communities whose research takes advantage of neuroinformatics combined with high quality experimental data, and of fast changing cyberinfrastructure and collaborative environments.

[Slide 17: COPN: Reverse Engineering the Human Brain's Ability to Control the Hand]
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Here is one example of the work that will be conducted in the COPN program. Francisco Valero-Cuevas at the University of Southern California is attempting to quantify the sensori-motor capabilities of the brain-hand system that allows us to manipulate objects with great dexterity. By constructing a computer model, he hopes to "reverse-engineer" the brain's ability to control the hand.

The research has already shown that healthy people all have a very consistent limit of dexterity. Specific diseases, however, have "signatures," which enable quantification of impairment and recovery. He is now applying his research to the development of dexterity in children.

Neurotech challenges are among the top priorities for the EFRI transformational program. The competition for 2008 is over.

[Slide 18: (Possible) EFRI Topics for 2009]
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But keep a watch on the NSF Website for more information on the 2009 competition. We expect to see many of you in this audience bringing the highest quality ideas to NSF.

Although NSF has a number of programs that directly address neuroinformatics, our investments in neuroscience are by no means limited to these. A number of overarching and cross-disciplinary programs offer great opportunities in neuroinformatics.

[Slide 19: CDI: Cyber-enabled Discovery and Innovation #1, general]
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NSF has just launched a new initiative called Cyber-enabled Discovery and Innovation, or CDI. Our intent is to create new computational concepts, methods, and tools that promise a wave of innovation in science and engineering. Three broad themes characterize this first round of awards.

First is Knowledge extraction. To move from "data" to "knowledge," we will need new fundamental mathematical and computational abstractions to represent and manage data, novel data mining strategies, and the development of sophisticated data visualization and delivery tools.

Second, simulation and computational models have emerged as important investigative tools for understanding and predicting complex physical, social, engineering, and life science phenomena. Progress in understanding complexity may be the most rewarding challenge of the 21st Century.

And finally, as scientists, engineers and students around the globe work more collaboratively and cooperatively, we must find new ways to enable and support these interactions. We need to develop more systematic knowledge about the intertwined social and technical factors that characterize virtual organizations.

[Slide 20: CDI #2, Example, Brian Scassellati's research]
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One of the researchers in the first round of awards is Brian Scassellati, at Yale University. He and his team are studying visual attention in children in an effort to better understand autism.

The research aims to understand the regulation of visual attention through both computational and robotic modeling.

The robots used in these modeling efforts will range from an upper-torso robot that has the kinematics of the 50th percentile male 1-year-old child (left)...

to more human-looking robots that are currently under development (those are the drawings in the center)...

to remarkably REAL robots. This "Einstein" is a finished system developed by one of the industrial partners in this research, Hanson Robotics.

[Slide 21: Adaptive Systems Technology]
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A second Investment Priority is called Adaptive Systems Technology. I like to think of this new field as "the next big thing."

Beneath the "skin" of modern computers, robots and machines, lies a physical nervous system of wires, circuits, sensors, fiber optics, and wireless communication modules.

The parallels between this "hardware" and the human brain and nervous system are striking, and they are no accident.

[Slide 22: Brain gears]
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We have an amazing "central processor" in this 3-pound organ we call our brain. Researchers are only now beginning to exploit its secrets and probe the many possible applications of neuroscience to the development of engineered systems, especially at the human-machine interface.

We envision neuroscience and neuroinformatics enabling an innovative new field we call Adaptive Systems Technology--the use of nervous-system inspired concepts in the development of engineered systems, especially at the human-machine interface.

Such pursuits must be integrated with education and training in ways such that there is mutual benefit from shared data and analysis capability, and work is enhanced through real-time collaboration.

[Slide 23: NSF Engineering Research Center, Biomimetic Microelectric Systems]

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Another NSF program with broad aims supports the establishment of Engineering Research Centers. These Centers have long been a success in building the critical mass needed to move a field forward rapidly.

ERCs encourage the participation of industry partners, and are highly skilled in transferring new knowledge to the workplace and new talent to the workforce.

This slide shows Ted Berger's work for the ERC in Biomimetic Microelectric Systems at the University of Southern California. The image is the group's conception of an implantable memory-device. This and other devices are what Ted has labeled "Replacement Parts for the Brain" in his book on the subject.

For his efforts, Popular Science magazine has labeled Ted, "The Memory Hacker!"

[Slide 24: NSF Science and Technology Centers]
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NSF supports a number of centers in addition to the Engineering Research Centers, including Science and Technology Centers and Science of Learning Centers.

Dr. Elliott Albers leads the Center for Behavioral Neuroscience at Georgia State University. CBN is an NSF Science and Technology Center that focuses on basic research on the neurobiology of social behaviors and how the environment shapes them.

In 2009, NSF intends to fund a new class of Science and Technology Centers.

We are fortunate to have Dr. Yuan Liu with us today.

Dr. Liu is involved in a number of programs and activities at NIH that are central to advancing neuroscience and neuroinformatics. Let me mention just a few:

1. Interagency Modeling and Analysis Group (IMAG)
2. NSF-NIH Collaborative Research in Computational Neuroscience (CRCNS)
3. NIH Roadmap National Centers for Biomedical Computing
4. Trans-NIH Biomedical Information Science and Technology Initiative (BISTI)
5. Neuroimaging Informatics Technology Initiative (NIfTI)
6. NIH Neuroscience Blueprint
• Neuroscience Information Framework
• Neuroimaging Informatics Tools and Resources Clearing House (NITRC)

[Slide 25: NSF Cyberinfrastructure Vision for 21st Century Discovery]
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As NSF looks into the future of neuroinformatics, we see an even more important role for advanced Cyberinfrastructure.

The NSF vision for cyberinfrastructure--or CI for short--encompasses all computing and communication tools, observational implements and platforms, and data sets, together with analysis and visualization tool. CI also includes educational resources.

As a result of the vision, we are focusing on additional computational resources for the NSF-supported TeraGrid. The TeraGrid is the world's largest, most comprehensive distributed cyberinfrastructure for open scientific research.

The TeraGrid is increasingly an integration of all types of CI services. Through the TeraGrid, researchers can access more than 100 discipline-specific databases.

[Slide 26: TeraGrid linkages on US Map]
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Through the TeraGrid, researchers have access to more than 100 discipline-specific databases.

TeraGrid also supports 23 gateways, which enable an entire community of users associated with a common scientific goal to use national resources through this common interface.

You can find the list of gateways on the TeraGrid Website.

In fact, many communities have used computational and cyberinfrastructure advances to further their own disciplinary advances. The portals and grids provide some excellent examples of how scientists are sharing resources to reach new frontiers.

This is a good point to mention Mark Ellisman, who has been instrumental in using supercomputer and TeraGrid resources in the establishment of BIRN.

[Slide 27: BIRN: Bio-informatics Research Network]
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BIRN--the Biomedical Informatics Research Network--hosts a collaborative environment rich with tools that permit uniform access to hundreds of researchers, enabling cooperation on multi-institutional investigations.

This unique partnership between the NIH-supported BIRN and the NSF-supported San Diego Supercomputing Center synchronizes developments in wide area networking, multiple data sources, and distributed computing with cutting-edge bioinformatics research.

BIRN also designs, tests, and releases new integrative software tools that enable researchers to pose questions and share knowledge across multiple animal models (mouse, human, and non-human primate).

[Slide 28: International Networking: Platform for Virtual Organizations]
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Grid networks are now a feature of every region of the globe. Here you see some of the European, Asian and Latin American connections that provide researchers around the world with networking capabilities.

International networking is the perfect platform for a new generation of Virtual organizations that share cyber resources of all kinds.

[Slide 29: Petascale Computing]
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Of course, nothing stands still in the computing field. The University of Illinois at Urbana-Champaign, with support from NSF, is designing a petascale computer, "Blue Waters," which is 500 times more powerful than today's typical supercomputers.

The Blue Waters project will build the world's first sustained petascale computational system dedicated to open scientific research. The project will include intense support for application development, system software development, interactions with business and industry, and educational programs. This comprehensive approach will ensure that users across the country will be able to use Blue Waters to its fullest potential.

As you can see, we are readying the horsepower to help herald in a new age of neuroscience research.

Blue Waters is a joint effort of the National Center for Supercomputing Applications, the University of Illinois at Urbana-Champaign, IBM, and the Great Lakes Consortium for Petascale Computation. It is supported by the National Science Foundation.

[Slide 30: PetaApps]
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Starting this year (2008) and continuing throughout the project, the National Science Foundation will award Petascale Computing Resource Allocations. These PetaApps awards will enable application teams to work closely with the Blue Waters project team in preparing their codes to take full advantage of petascale resources.

Applications that require petascale computing are very large projects. To give you some indication of how large, one of these awards is a three-year research and development effort, aimed at enabling a broad climate science capability for petascale computing. Investigators will use novel interactive techniques to obtain new insights about many basic but poorly understood questions in climate dynamics that depend on the stochastic nature of fluctuations in the Earth’s atmosphere, oceans, cryosphere, and land surface.

Researchers will work with the CCSM, a community climate model used by hundreds of researchers, and one of the climate models used in the International Panel on Climate Change (IPCC) assessments. This research will provide a basis for improving our understanding of the role of noise in climate system dynamics for seasonal prediction and global climate change.

[Slide 31: Cluster Exploratory CluE]
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In the last five years, private sector companies have launched a number of highly effective Internet-scale applications powered by massively scaled, highly distributed computing resources known as data clusters--or clouds.

In 2007, Google and IBM created a large-scale computer cluster of approximately 1600 processors to give the academic community access to otherwise prohibitively expensive resources. NSF joined in this initiative to create the Cluster exploratory, or CluE. CluE will provide NSF-funded researchers access to software and services running on a Google-IBM cluster to explore innovative research ideas in data-intensive computing.

NSF will allocate cluster computing resources for a broad range of proposals to explore the potential of this technology to contribute to science and engineering research.

Here is another opportunity to ask, "What are the BIG questions and opportunities for neuroscience and neuroinformatics?"

[Slide 32: Integrating Research and Education]
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Educational activities are an integral part of the planning for all NSF activities. This central theme of the National Science Foundation--integrating research and education—has remained constant throughout the Foundation's history.

We recognize the long-term value in university research laboratories serving as a training-ground for graduate and undergraduate students. As students work side-by-side with researchers, they learn the cutting-edge of discovery first hand and share in the excitement of exploring unknown territory.

I don't want to conclude without mentioning a very important aspect of NSF's work. Developing a passion for science doesn’t happen overnight. And it doesn't happen without effort.

NSF has long supported informal science and math education to reach a broad audience of youngsters with the excitement of discovery.

[Slide 33: "Wired to Win" video]
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"Wired to Win" is a recent IMAX feature that explores how the nervous system and the brain function as athletes compete in the Tour de France. This is a wonderful film for youngsters.

You are watching a clip from the movie that illustrates how synapses begin to form connections as the cyclist learns and absorbs new information from the challenges of the race.

There can be nothing more important to our future and the future of the nation than instilling curiosity and a passion to ask WHY? in our youngsters.

[Slide 34: Clark quote]
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There has never been a time more pregnant with possibilities for understanding the brain and behavior--even the human mind--than our own times. Whole new territories of knowledge are on the horizon, with the promise of major advances just ahead.

We can begin to envision how this new knowledge and technological innovation can help us solve old problems--in health, in the organization of human institutions, and much more.

This quote from the late Arthur Clark has always been one of my favorites:

"The only way to discover the limits of the possible is to go beyond them into the impossible."

I think that says it all.

Thank you!