Presentation on the NeuroInformatics Center

Oregon NeuroInformatics Center (NIC) : 

Oregon NeuroInformatics Center (NIC) Allen D. Malony Department of Computer and Information Science University of Oregon Don Tucker Department of Psychology Electrical Geodesics, Inc. University of Oregon

Experimental Methodology and Tool Integration : 

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

NeuroInformatics Center (NIC) : 

NeuroInformatics Center (NIC) Application of computational science methods to cognitive neuroscience problems 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 Advance techniques for integrated neuroimaging Address multiple domains of application Allow alternative experimental paradigms and methods Couple tools of different imaging modalities Build grid environments for tool interoperation

NIC Organization : 

NIC Organization Allen D. Malony, Director Professor, Computer and Information Science Don M. Tucker, Associate Director Professor, Psychology; CEO, EGI Kevin Glass, Computational Scientist Ph.D., Computer Science; B.S., Physics Sergei Turovets, Computational Physicist Ph.D., Computer Science; B.S., Physics Sameer S. Shende, Computer Scientist Ph.D., Computer Science; parallel computing specialist Bob Frank, Mathematician M.S., Mathematics

Funding Support : 

Funding Support BBMI federal appropriation DoD Telemedicine Advanced Technology Research Command (TATRC) Budget Approximately $750K for 1.5 years Start date: Oct. 1, 2002 New proposals NSF Major Research Instrumentation (MRI) awarded, $1.1M with $950K for computer infrastructure highest ranked in NSF Social, Behavioral, and Economic Sciences (SBE) directorate competition NIH Human Brain Project Neuroinformatics

NIC Approaches : 

NIC Approaches Optimize spatial resolution MRI structural information Measurement of skull conductivity Convergence / co-recording with MEG and fMRI Optimize temporal resolution Use EEG/MEG time course for fMRI signal extraction Decomposition of component analysis (ICA, PCA) Single-trial analysis Computational brain models BEM, FDM, and FEM brain models Brain information databases and atlases

Source Localization : 

Source Localization 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

Building Finite Element Brain Models : 

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 scalp CSF skull cortex

Applying ICA for EEG Blink Removal : 

Applying ICA for EEG Blink Removal Blinks are a major source of noise in EEG data Blink signals are separable from cognitive responses Apply Independent Component Analysis (ICA) Blink removal workflow Raw EEG Formatting EEG preprocessing Event info Time markers Blink events Bad channel removal Baseline correction Etc. ICA Analysis ICA algorithm - binICA - fastICA - laICA (parICA) ICA components Identify blinks and remove Blink templates Reconstitute EEG w/out blink data ERP Analysis

NIC Relationships : 

NIC Relationships Psychology CIS BDL BEL CSI OHSU/ OGI Utah UCSD USC Academic Labs / Centers LANL Argonne NCSA Internet2 EGI Industry Intel IBM NIC UO Departments UO Centers/Institutes BBMI CDSI CNI Physics NSI Sandia

NIC Computational Cluster (“Neuronic” Cluster) : 

NIC Computational Cluster (“Neuronic” Cluster) Dell computational cluster 16 dual-processor nodes 2.8 MHz Pentium Xeon 4 Gbyte memory 36 Gbyte disk (576 Gbyte total) Dual Gigabit ethernet adaptors Master node (same specs) 2 Gigabit ethernet switches Brain model development ICA development

NSF MRI Proposal : 

NSF MRI Proposal Major Research Instrumentation (MRI) “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 Approximately $1.1M over three years

ICONIC Grid : 

ICONIC Grid Shared Memory SMP Server Distributed Memory SAN Storage System Gbit Campus Backbone graphics workstations interactive visualization campus clusters NIC CIS CNI Internet 2 NSF Major Research Instrumentation (MRI) grant

Cognitive Neuroscience and ICONIC Grid : 

Cognitive 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 development and deprived Attention and emotion regulation Spatial working memory and selective attention Attention and psychopathology

EEG/ERP Methodology : 

EEG/ERP Methodology Electroencephalogram (EEG) Event-Related Potential (ERP) Stimulus-locked measures of brain dynamics Generated from subject- and trial-based analysis Raw EEG datasets processed and analyzed Segmentation to time series waveforms Blink removal and other cleaning ERP analysis Averaging for increasing signal to noise Characterization with respect to trial conditions Results visualization Source localization

EEG/ERP Experiment Management System : 

EEG/ERP Experiment Management System Support EEG-based cognitive neuroscience research Based on experiment model Experiment type Subjects measured for trial types Management of experiment data Raw and processed datasets and derived statistics Per experiment/subject/trial database Secure protection and storage with selective access Analysis tools and workflows Generation of results (across experimental variables) Analysis processes with multi-tool workflows

EEG/ERP Experiment Analysis Environment : 

EEG/ERP Experiment Analysis Environment … … raw processed datasets / derived results analysis workflow storage resources virtual services compute resources

Posters : 

Posters “The FastICA Algorithm” R. Frank,, J. Dien, G. Frishkoff, C. Davey, K. Glass “Blind Separation of Blinks from EEG Data: Evaluation of Infomax and FastICA Algorithms ” G. Frishkoff, R. Frank, C. Davey, J. Dien, K. Glass “Finite Difference and Finite Element Human Head Modeling: Forward Problem” S. Turovets, K. Glass, A. Malony, V. Volkov “ICA Code Development and Performance Analysis” K. Glass, R. Frank, A. Malony