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

Allen D. Malony

University of Oregon

Oregon’s 2004 Bioscience ConferenceMay 10, 2004

ProfessorDepartment of Computerand Information Science

DirectorNeuroInformatics Center

Computational Science Institute

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

ComputerScience

Biology

Neuroscience

PsychologyPaleontology

Geoscience

Math

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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)

May 10, 2004 2004 Bioscience Conference

Integrated Electromagnetic Brain Analysis

IndividualBrain Analysis

Structural /FunctionalMRI/PET

DenseArray EEG /

MEG

ConstraintAnalysis

Head Analysis

Source Analysis

Signal Analysis

Response Analysis

Experimentsubject

temporaldynamics

neuralconstraints

CorticalActivity Model

ComponentResponse Model

spatial patternrecognition

temporal patternrecognition

Cortical ActivityKnowledge Base

Component ResponseKnowledge Base

good spatialpoor temporal

poor spatialgood temporal neuroimaging

integration

May 10, 2004 2004 Bioscience Conference

Experimental Methodology and Tool Integration

source localization constrained to cortical surface

processed EEG

BrainVoyager

BESA

CT / MRI

EEG segmentedtissues

16x256bits permillisec(30MB/m)

mesh generation

EMSEInterpolator 3D

NetStation

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

UO MRI Facility (Lewis Center for Neuroimaging)

Siemens Head-Only 3T MRI System Tailored to performing

functional imaging Human subjects Monitor common

physiologic parameters heart rate, respiration peripheral pulse oxygenation eye location and eye movement

Audio and visual stimulus Special RF screening room MRI coil development

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

Computational Integrated Neuroimaging System

… …

raw

storageresources

virtualservices

compute resources

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

SMPServerIBM p655

GraphicsSMP

SGI MARS

SAN Storage System

Gbit Campus Backbone

NIC CIS CIS

Internet 2

SharedMemory

IBM p690

DistributedMemory

IBM JS20

CNI

DistributedMemory

Dell Pentium Xeon

NIC4x8 16 16 2x8 2x16

graphics workstations interactive, immersive viz other campus clusters

ICONIC Grid

5 TerabytesTapeBackup

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

NIC Relationships

Biology

CISCSI

OHSUUtah

UCSD

USC

Academic Labs / Centers

LANL Argonne

SDSCInternet2

EGI

Industry

Intel IBMNIC

UO Departments

UO Centers/Institutes

BBMI CDSI

LCNI

Physics

NSI

LLNL

SGI

OSU

PSU

Psychology

Math

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

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

May 10, 2004 2004 Bioscience Conference

Region 4

Region 1Region 2

Region 3

Region 5

Oregon E-Science Grid

Internet 2 /National LambdaRail

Regional networks

HPC serversRegional clients