1. GENII: Grid-based Environment for Neuroimaging Integration and Interoperation Human Brain Project – Neuroinformatics Proposal Allen D. Malony Don Tucker Scott Makeig Gregor von Laszewski Dennis Gannon NeuroInformatics Center, Department of Computer and Information Science, University of Oregon Electrical Geodesics, Inc., University of Oregon Swartz Center for Computational Neuroscience, Institute for Neural Computation, University of California San Diego Argonne National Laboratory Pervasive Technologies Laboratory, Department of Computer Science, Indiana University

2. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Aim 1  Develop a grid-based computing environment for dynamic neuroimaging  We will apply state-of-the-art technology from the Open Grid Computing Environment (OGCE) consortium to build GENII  Grid-based domain-specific Environment for dynamic Neuroimaging of human brain activity with support for analysis and modeling tool Integration and Interoperation  Provide access to shared time-series data repositories, and analysis workflow creation and execution on a grid of computational and storage resources  GENII will be publicly-available open-source software designed to maintain both technological and operational consistency with the NIH Biomedical Informatics Research Network (BIRN)

3. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Aim 2  Enable leading Matlab-based time-series neuroimaging tools to efficiently and conveniently access the GENII environment and benefit from the emerging grid computing infrastructure  We will develop mechanisms for Matlab to interface with GENII using the Java Virtual Machine (JVM) support inherent in current Matlab (R14) installations and the Java CoG and portlet technologies from the OGCE  Utilize this interface to make the widely used Matlab toolsets EEGLAB, BrainStorm, SPM, APECS, and FieldTrip able to access GENII computational, storage, and workflow services  GENII will mediate a high-level interaction between freely available (front-end) Matlab tools and a user’s (back-end) grid computing infrastructure

4. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Aim 3  Build high-performance analysis and modeling components as GENII neuroimaging services  We will select and implement several essential time- intensive algorithms in signal processing, computational head modeling, image segmentation, and dipole source localization in high-performance sequential and parallel forms  The implementations will support scaling in data size, model resolution, and degree of parallelism  These programs will be wrapped as grid-enabled components to operate as prototypical computational services available within the GENII environment

5. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Aim 4  Create computational workflows that capture complex, multi-step neuroanalysis processes  We will support processing of neurophysiological time- series data involving a series of analysis steps performed by multiple tools across multiple subjects over multiple experiments  Utilize emerging grid workflow programming technologies (e.g., XCAT and GridAnt) to create multi-component neuroimaging pipelines as high-level GENII services  The workflows can be reused with pluggable analysis components and composed with other workflow processes

6. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Aim 5  Design and implement a storage schema for managing time-series neuroimaging information  Support storage and management of large, multi- dimensional, and multi-model neurophysiological data (raw, intermediate analyses, final results)  We will develop a robust schema for the storage of neuroimaging data and experimental information compatible with the SRB technology and incorporating a streamlined interface for GENII software access  A range of time-series data formats and types will be supported as well as tools for data conversion and correlation

7. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Specific Aims – Neuroinformatics Software  The results of the project will be publicly-available open-source software for managing the storage and analysis of neuroinformatic experiment data and for leveraging the power of grid-accessible Unix-based clusters for high-performance computation  The GENII software will allow users to extend freely available Matlab toolsets with grid-enabled capabilities for workflow processing and shared storage

8. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Integrated Dynamic Brain Analysis Problem Individual Brain Analysis Structural / Functional MRI/PET Dense Array EEG / MEG Constraint Analysis Head Analysis Source Analysis Signal Analysis Response Analysis Experiment subject temporal dynamics neural constraints Cortical Activity Model Component Response Model spatial pattern recognition temporal pattern recognition Cortical Activity Knowledge Base Component Response Knowledge Base good spatial poor temporal poor spatial good temporal neuroimaging integration

9. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Experimental Methodology and Tool Integration source localization constrained to cortical surface processed EEG BrainVoyager BESA CT / MRI EEG segmented tissues 16x256 bits per millisec (30MB/m) mesh generation EMSE Interpolator 3D NetStation

10. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Experiment Tool Integration (Selected)  Geodesic Sensor Net (EGI)  EEGLAB (Swartz Center)  NetStation (EGI)  BrainStorm, USC/LANL

11. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation SMP Server IBM p655 Graphics SMP SGI Prism SAN Storage System IBM SAN FS Gbit Campus Backbone NICCIS Internet 2 Shared Memory IBM p690 Distributed Memory IBM JS20 CNI Distributed Memory Dell Pentium Xeon NIC 4x816 2x82x16 graphics workstationsinteractive, immersive vizother campus clusters ICONIC Grid at University of Oregon 5 Terabytes Tape Backup

12. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation ICONIC Grid – Hardware p690  16 processors p655  4 nodes  8 processors per node Dell cluster  16 nodes  2 processors per node JS20 Blade  16 nodes  2 processors per node FAStT storage  5 TB SAN FS Fibre Channel

13. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation Computational Integrated Neuroimaging System

14. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation 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  Enhanced HPC / grid infrastructure for neuroinformatics  Build on emerging web services and grid technology  Establish HPC resources with high-bandwidth networks  Further institutional and industry partnerships

15. GENII - Grid-based Environment for Neuroinformatics Integration and Interoperation InstitutionYear 1Year 2Year 3Year 4Year 5Total UO$300K $1500K UCSD$175K $875K Indiana$175K $875K Argonne$175K $875K Total$825K $4125K Proposed Budget  Direct costs