Neuroinformatics, the ICONIC Grid, and Oregon’s Science Industry

1. Neuroinformatics, the ICONIC Grid, and Oregon’s Science Industry Allen D. Malony University of Oregon Professor Department of Computerand Information Science Director NeuroInformatics Center Computational Science Institute May 10, 2004 Oregon’s 2004 Bioscience Conference

2. Outline • Computational science • High-performance computing research at UO • Brain, Biology, and Machine Initiative • Neuroinformatics and the ICONIC Grid • NeuroInformatics Center (NIC) • Electrical Geodesics, Inc. (EGI) • ICONIC Grid system and application • HPC / Grid computing for Oregon’s science industry • Services delivery (research, clinical, medical, …) • HPC resource centers • High-bandwidth state-wide networking 2004 Bioscience Conference

3. Computational Science • Integration of computerscience in traditionalscientific disciplines • Increasingly acceptedmodel of scientificresearch • Application of high-performancecomputation, algorithms, networking, database,and visualization • Parallel and grid computing • Integrated problem-solving environments • Computer science research at the core Math Biology Computer Science Geoscience Neuroscience Psychology Paleontology 2004 Bioscience Conference

4. Computational Science Projects at UO • Geological science • Model coupling for hydrology • Bioinformatics • Zebrafish Information Network (ZFIN) • Evolution of gene families • Oregon Bioinformatics Toolkit • Neuroinformatics • Paleontology • Dinosaur skeleton and motion modeling • Artificial intelligence • Computational Intelligence Research Lab (CIRL) • Oregon Computational Science Institute 2004 Bioscience Conference

5. HPC Research Project Areas at UO • Parallel performance evaluation and tools • Parallel language systems • Tools for parallel system and software interaction • Source code analysis • Parallel component software • Computational services • Grid computing • Parallel modeling and simulation • Scientific problem solving environments 2004 Bioscience Conference

6. HPC Research Affiliations at UO • Strong associations with DOE national laboratories • Los Alamos National Lab, Lawrence Livermore National Lab, Sandia National Lab, Argonne National Lab, Pacific Northwest National Lab • DOE funding • Office of Science, Advance Scientific Computing Research • Accelerated Strategic Computing Initiative (ASCI/NNSA) • NSF funding • Academic Research Infrastructure • Major Research Instrumentation 2004 Bioscience Conference

7. Brain, Biology, and Machine Initiative • UO interdisciplinary research in cognitive neuroscience, biology, computer science • Human neuroscience focus • Understanding of cognition and behavior • Relation to anatomy and neural mechanisms • Linking with molecular analysis and genetics • Enhancement of neuroimaging resources • Magnetic Resonance Imaging (MRI) systems • Dense-array EEG systems • Computation clusters for high-end analysis • Establish and support institutional centers 2004 Bioscience Conference

8. BBMI Sponsored Research • $40 million research attracted by BBMI • DoD TATRC funding • Telemedicine Advanced Technology Research Center • $10 million gift from Robert and Beverly Lewis family • Established Lewis Center for Neuroimaging (LCNI) • Dr. Ray Nunnally, Director • NIH • NSF • Oregon bond funds • UO foundation funds 2004 Bioscience Conference

9. BBMI Research and Development Plan • Imaging technology and integration • Dense-array EEG and MRI • Coil development • Simultaneous measurement • Computational analysis problems • Image segmentation, analysis, identification • EEG signal decomposition, component analysis, source localization • Internet-based capabilities for analysis services, data archiving, and data mining • Computation and data grid for bio and neuro sciences 2004 Bioscience Conference

10. Computational Science and Human Neuroscience • Computational methods applied to scientific research • High-performance simulation of complex phenomena • Large-scale data analysis and visualization • Understand functional activity of the human cortex • Multiple cognitive, clinical, and medical domains • Multiple experimental paradigms and methods • Need for coupled/integrated modeling and analysis • Multi-modal (electromagnetic, MR, optical) • Physical brain models and theoretical cognitive models • Need for robust tools • Computational, informatic, and collaborative 2004 Bioscience Conference

11. Brain Dynamics Analysis Problem • Identify functional components • Different cognitive neuroscience research contexts • Clinical and medical applications • Interpret with respect to physical and cognitive models • Requirements: spatial (structure), temporal (activity) • Imaging techniques for analyzing brain dynamics • Blood flow neuroimaging (PET, fMRI) • good spatial resolution  functional brain mapping • temporal limitations to tracking of dynamic activities • Electromagnetic measures (EEG/ERP, MEG) • msec temporal resolution to distinguish components • spatial resolution sub-optimal (source localization) 2004 Bioscience Conference

12. Integrated Electromagnetic Brain Analysis good spatial poor temporal Cortical Activity Knowledge Base Head Analysis Source Analysis Structural / Functional MRI/PET spatial pattern recognition temporal dynamics Cortical Activity Model Experiment subject Constraint Analysis IndividualBrain Analysis Component Response Model neural constraints Dense Array EEG / MEG temporal pattern recognition Signal Analysis Response Analysis Component Response Knowledge Base poor spatial good temporal neuroimaging integration 2004 Bioscience Conference

13. Experimental Methodology and Tool Integration 16x256bits permillisec (30MB/m) CT / MRI segmentedtissues EEG NetStation BrainVoyager processed EEG mesh generation source localization constrained to cortical surface Interpolator 3D EMSE BESA 2004 Bioscience Conference

14. NeuroInformatics Center (NIC) • Application of computational science methods to human neuroscience problems (cognitive, clinical) • Understand functional activity of the brain • Help to diagnosis brain-related disorders • Utilize high-performance computing and simulation • Support large-scale data analysis and visualization • Advanced techniques for integrated neuroimaging • Coupled modeling (EEG/ERP and MR analysis) • Advanced statistical analysis (PCA, ICA) • FDM/FEM brain models (EEG, CT, MRI) • Source localization (dipole, linear inverse models) • Problem-solving environment for brain analysis 2004 Bioscience Conference

15. Electrical Geodesics Inc. (EGI) • EGI Geodesics Sensor Net • Dense-array sensor technology • 64/128/256 channels • 256-channel geodesics sensor net • AgCl plastic electrodes • Carbon fiber leads • Net Station • Advanced EEG/ERP data analysis • Stereotactic EEG sensor registration • Research and medical services • Stroke monitoring and localization 2004 Bioscience Conference

16. UO MRI Facility (Lewis Center for Neuroimaging) • Siemens Head-Only 3T MRI System • Tailored to performingfunctional imaging • Human subjects • Monitor commonphysiologic parameters • heart rate, respiration • peripheral pulse oxygenation • eye location and eye movement • Audio and visual stimulus • Special RF screening room • MRI coil development 2004 Bioscience Conference

17. Source Localization Problem • Mapping of scalp potentials to cortical generators • Single time sample and time series • Requirements • Accurate head model and physics • High-resolution 3D structural geometry • Precise tissue identification and segmentation • Correct tissue conductivity assessment • Computational head model formulation • Finite element model (FEM) • Finite difference model (FDM) • Forward problem calculation • Dipole search strategy 2004 Bioscience Conference

18. Advanced Image Segmentation • Native MR gives high gray-to-white matter contrast • Edge detection finds region boundaries • Segments formed by edge merger • Color depicts tissue type • Investigate more advanced level set methods and hybrid methods 2004 Bioscience Conference

19. Building Finite Element Brain Models • MRI segmentation of brain tissues • Conductivity model • Measure head tissue conductivity • Electrical impedance tomography • small currents are injectedbetween electrode pair • resulting potential measuredat remaining electrodes • Finite element forward solution • Source inverse modeling • Explicit and implicit methods • Bayesian methodology 2004 Bioscience Conference

20. Computational Integrated Neuroimaging System raw … … virtual services storage resources compute resources 2004 Bioscience Conference

21. UO ICONIC Grid • NSF Major Research Instrumentation (MRI) proposal • “Acquisition of the Oregon ICONIC Grid for Integrated COgnitive Neuroscience Informatics and Computation” • PIs • Computer Science: Malony, Conery • Psychology: Tucker, Posner, Nunnally • Senior personnel • Computer Science: Douglas, Cuny • Psychology: Neville, Awh, White • Computational, storage, and visualization infrastructure 2004 Bioscience Conference

22. ICONIC Grid graphics workstations interactive, immersive viz other campus clusters Internet 2 Gbit Campus Backbone CNI NIC NIC CIS CIS 4x8 16 16 2x8 2x16 SMP Server IBM p655 Shared Memory IBM p690 Graphics SMP SGI MARS Distributed Memory IBM JS20 Distributed Memory Dell Pentium Xeon TapeBackup 5 Terabytes SAN Storage System 2004 Bioscience Conference

23. Human Neuroscience and ICONIC Grid • Common questions to be explored • Identifying brain networks • Critical periods during normal development • Network involvement in psychopathologies • Training interventions in network development • Research areas • Development of attentional networks • Brain plasticity in normal & altered development • Attention and emotion regulation • Spatial working memory and selective attention • Psychopathology 2004 Bioscience Conference

24. Computer Science and ICONIC Grid • Scheduling and resource management • Assign hardware resources to computation tasks • Scheduling of workloads for quality of service • Problem-solving computational science environments • Provide scientists an entrée to the ICONIC Grid without requiring specialized knowledge of parallel execution • Interactive / immersive three-dimensional visualization • Explore multi-sensory visualization • Merge 3D graphics with force-feedback haptics • Parallel performance evaluation 2004 Bioscience Conference

25. NIC Relationships Academic Labs / Centers Utah OHSU LANL Argonne Internet2 UCSD OSU LLNL SDSC PSU USC Industry Intel IBM Psychology NIC EGI SGI Biology Math CIS Physics CSI CDSI BBMI UO Departments NSI LCNI UO Centers/Institutes 2004 Bioscience Conference

26. Technology Transfer in Human Neuroscience • UO’s BBMI is conducting pioneering research and development in human neuroscience, genetics and proteomics, and computational science for future neurological medicine and health care • Greater precision and speed in brain imaging has high research and medical relevance • Integrated medical imaging (EEG/MEG, MRI, radiology) • Automatic image assessment (detection and diagnosis) • Neurological evaluation and surgical planning • Linking of genetics factors with complex cognitive traits (personality, learning, attention) has potential for therapies and pharmaceutical clinical drug development 2004 Bioscience Conference

27. Leveraging Internet, HPC, and Grid Computing • Telemedicine imaging and neurology • Distributed EEG and MRI measurement and analysis • Neurological medical services • Shared brain data repositories • Remote and rural imaging capabilities • Neet to enhance HPC and grid infrastructure in Oregon • Build on emerging web services and grid technology • Establish HPC resources with high-bandwidth networks • Create institutional and industry partnerships • UO is working closely with EGI to develop high-end EEG analysis services framework • Pilot neuroimaging services model on ICONIC Grid 2004 Bioscience Conference

28. Region 2 Internet 2 /National LambdaRail Region 1 Regional networks Region 5 Region 4 HPC servers Regional clients Region 3 Oregon E-Science Grid 2004 Bioscience Conference