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Distributed Computational Architectures for Integrated Time-Dynamic Neuroimaging. Dr. Allen D. Malony [email protected] Computer & Information Science Department Computational Science Institute CIBER University of Oregon. Who Am I. Associate Professor, CIS Department, UO - PowerPoint PPT Presentation
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Distributed Computational Architectures forIntegrated Time-Dynamic Neuroimaging
Dr. Allen D. Malony
Computer & Information Science DepartmentComputational Science Institute
CIBER
University of Oregon
April 19, 2023 Hill Center
Who Am I
Associate Professor, CIS Department, UO Computer Science specialties / interests
parallel performance analysis (primary) environments computational science (secondary)
software development environments distributed and parallel computing environment
Cognitive Neuroscience interests two-year association with Don Tucker (Psychology, UO) Carmel Neuroinformatics workshop (2000, presentation) HBP Neuroinformatics Review Panel (2000, 2001) HBP Annual Meeting (2000, presentation)
April 19, 2023 Hill Center
Talk Outline
Computational science and cognitive neuroscience Brain dynamics analysis problem (my view)
integrated electromagnetic analysis system Motivating case studies
observations: computation and informatics Computational architectures
models and technology key ideas
Opportunities and the Neural Informatics Center Final Thoughts
April 19, 2023 Hill Center
Computational Science & Cognitive 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 domains multiple experimental paradigms and methods
Need for coupled/integrated modeling and analysis electrical and magnetic, cortical and theoretical
Need for robust tools: computational & informatic
Problem solving environment for brain analysis
April 19, 2023 Hill Center
Brain Dynamics Analysis Problem (My View)
Identify functional components in cognitive contexts Interpret with respect to cognitive theoretical 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) potential to map electrical activity to cortex surface
April 19, 2023 Hill Center
Electromagnetic Analysis Methodology Multi-trial analysis
signal analysis and response analysis averaging across subjects and trials (S/N ratio)
distortion (smearing) of estimated source response noise artifacts, signal variation (individuals, trials) improvements: artifact removal, selective averaging
create component response models ERP identification factor analysis: PCA, ICA, … error in source factors: variability, statistics
Multi-subject and single-subject analysis quantify differences of individual from population
April 19, 2023 Hill Center
Single-Trial Analysis Capability
Improve fidelity of single-subject response model higher information content than multi-trial/subject reduce analysis error from trial/subject variability knowledge of subject population, stimulus deviations
Diagnosis (identification) of cognitive state known stimulus blind stimulus match response to known component response model
Problems greater noise greater complexity
April 19, 2023 Hill Center
Single-Trial Analysis Methodology
Integrate methods for analyzing brain dynamics Improve resolution and robustness of techniques
increase measurement density (128 to 256 channels) Coupled modeling: constraints and cross-validation
component response model cortical activity model tuned models for single individual
Build models in experimental paradigm context Match single-trial measurements to models
known stimulus multiple trial models blind stimulus multiple stimulus/trial models
Training and learning
April 19, 2023 Hill Center
Integrated Electromagnetic Brain Analysis
Single-trialAnalysis
Structural /Functional
MRI
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
EEGMEG
Carmel Workshop
Integrated Electromagnetic Analysis System
April 19, 2023 Hill Center
Case Study: Readiness Potential
Self-paced button pressing task slow negative shifts in potential contralateral to hand
Single subject examination multi-trial (150 trials) averaged ERP analysis
Dense-array scalp electrical measurement 129 electrode array (EGI Geodesic Sensor Net)
Modeling of brain electrical activity MRI and CT data analysis with tissue segmentation realistic boundary element meshes (2K ’s for brain) source localization with dipole modeling
Can ERP analysis accurately localize cortical activity?
April 19, 2023 Hill Center
mesh generation,source localization constrained to cortical surface
processed EEG
Experimental Methodology
BrainVoyager
EMSE
CT / MRI
Interpolator 3D
NetStationEEG segmented
tissues
16x256bits permicrosec(30MB/m)
April 19, 2023 Hill Center
Electrical Activity of Scalp and Brain
Expected brain activity Correlated with fMRI
experimental studies Topographic and cortex
mapped spatial analysis
-404 ms -56 ms 0 ms 160 ms
Lateralize Readiness Potential (LRP)
April 19, 2023 Hill Center
Optimizing Spatial Resolution for ERP
Adequate spatial sampling Accurate head surface mapping Accurate sensor registration Measured skull conductivity Convergence with MEG MEG-compatible EEG Convergence with fMRI fMRI-compatible EEG Test spatial resolution with know pathological sources
EEG as link for converging analysis? What problems exist?
April 19, 2023 Hill Center
Electrical Impedance Tomography
Small (10µA) currents are injectedbetween electrode pair
Resulting potential is measuredfrom all remaining electrodes
Measures used to estimateconductivity of each tissue compartment
Boundary element forward solution 4-shell polyhedron model (1280 faces) direct (31244 sec) and iterative approaches (933 sec)
Finite element forward solution greater computational requirements
April 19, 2023 Hill Center
Case Study: Self-Monitored Motivated Action
Learning task with feedback (Gehring et al. (1993)) left- or right-hand button press response "incorrect" feedback on error "OK" or “late” feedback if correct timed expectancy and motivated response
Error-Related Negativity (ERN) large medial negative response on error self-monitoring when motivated action goes wrong
What is the nature and complexity of the ERN withrespect to dynamic components of brain activity?
April 19, 2023 Hill Center
Cognitive Experiments and Brain Dynamics
Visualize the dynamic operations of brain Example: fMRI blood flow response to reading a word Dense-array EEG / MEG frontal lobe activity (ERN)
significant changes in milliseconds frontal oscillations and separate time courses
BrainVoyager
April 19, 2023 Hill Center
ERN Analysis using ICA (Makeig, Salk Institute)
Average analysis smears temporal/spatial dynamics Single-trial analysis may expose greater detail Independent Components Analysis (ICA)
find independent EEG component contributors temporal and spatial components accounting for artifacts components accounting for functional sources (ERN)
analysis over single trials Two components account for averaged ERN
response-locked ERN difference wave dominated show temporal and functional independence
April 19, 2023 Hill Center
ERP and Component Envelopes (Left/Correct)
Component #2
Component #7
• Complementary behavior
• Both active at strongest ERN channels
April 19, 2023 Hill Center
ERPs averaged across response hand
Neither C2nor C7 explainthe waveforms
Component sumdoes explain the waveforms and shows ERN response
April 19, 2023 Hill Center
Topographic Imaging and Dipole Modeling
Component #2 Component #7
Averaged ERN
Brain ElectricalSource Analysis
(BESA)
April 19, 2023 Hill Center
ICA Component #2 Dynamics
Stimulus locked Memory of deadline
April 19, 2023 Hill Center
ICA Component #7 Dynamics
Phase reset byresponse, largestafter incorrect
April 19, 2023 Hill Center
Optimize Temporal Information
Inherent problem – both electrical and magnetic Trial averaging methodologies can mask dynamics Techniques to boost signal to noise ratio
Selective averaging Stimulus and response locking
Techniques to estimate time function fMRI timing models EEG/MEG time function for fMRI signal extraction
Single trial analysis with individual modeling
What problems exist?
April 19, 2023 Hill Center
Case Study Observations
Diverse set of tools function and implementation separate tools (monolithic) and not integrated incompatibilities and limitations for interoperation
Complex analysis processes multiple processes applied (process pipeline) high-level, hierarchical process methodology scientific discovery through integrated techniques heterogeneous, flexible, extensible capabilities increasingly high computational demands
Multiple, interdisciplinary scientific domains
April 19, 2023 Hill Center
High-Performance Computational Environments
Integrated database, analysis, and visualization Distributed tool infrastructure
diverse tools across multiple platforms interoperation requirements user interaction requirements support portability, flexibility, extensibility
Scalable, high-performance parallel computing increase data resolution minimize solution time
High-level access to tools web-based access
April 19, 2023 Hill Center
Computational Systems: Models and Technology
Domain-specific, problem-specific environments (PSE) TIERRA
Scientific “workbench” SCIRun
Programming environments numerical frameworks
POOMA application coupling
PVM / MPI CUMULVS PAWS SILOON / PDT
Metacomputing / GRID Legion Globus
Heterogeneous distributed computing / coupling NetSolve INTERLACE HARNESS
Web-based environments ViNE PUNCH VNC
April 19, 2023 Hill Center
TIERRA (Computational Science Institute, UO)
Tomographic Imaging Environment for Ridge Research and Analysis
High-performance, domain-specific environment for seismis tomography parallelized tomography code runtime distributed array access computational steering via MatLab frontend full problem solving process for seismic tomography
Led to new discoveries for three-dimensional melt migration beneath the East Pacific Rise
April 19, 2023 Hill Center
TIERRA Architecture
KEY IDEAS
Domain specific
Support for the entire process
April 19, 2023 Hill Center
SCIRun (Johnson, University of Utah)
Scientific programming environment large-scale simulations “computational workbench” visual programming interface dataflow model of computing
modules: operation or algorithm with I/O ports network: set of modules and their interconnections widgets: 3D user interaction
data types: Mesh, Surface, Matrix, Field, Geometry extensible module library computational steering
April 19, 2023 Hill Center
SCIRun User Interface
Visual programming lets users select, arrange, and connect modules into a desired network
Interactive steering of design, computation, and visualization allows more rapid convergence
April 19, 2023 Hill Center
ICA for EEG Source Localization with SCIRun
PCA decomposition forEEG signal/noise subspaces
ICA activity map separationon signal subspace
Solution to a single dipolesource forward problem underlying model is shown
in the MRI planes dipole source is indicated by red and blue spheres electric field visualized by cropped scalp potential
map and wire-frame equipotential isosurface
KEY IDEAS
Integrated application development environment
“Component-based” application programming
High-level data objects
April 19, 2023 Hill Center
POOMA (Advanced Computing Lab, LANL)
Parallel Object-Oriented Methods and Applications Goals
use object-oriented programming to help manage complexity of modern scientific simulation codes
extract physics content of simulations from details of parallel, high-performance computing
framework approach: allows flexible code structure, object reuse across problem domains
build upon standards to maintain code portability
An object-oriented framework for scientific computing applications on parallel computers
April 19, 2023 Hill Center
POOMA Approach
C++ class library high-level, generally data-parallel API
Generic programming classes modeled after STL style heavy use of C++ templates
Parallelism encapsulated message-passing for distributed memory machines multi-threaded shared memory (POOMA II)
Cross platform code development and scalable parallelism
April 19, 2023 Hill Center
Compile-timePolymorphism
ComputerScience
Physics
ApplicationApplication
AlgorithmAlgorithm
LocalLocal
ParallelParallel
GlobalGlobal
STL ExpressionTemplates
DomainDecomposition
MessagePassing
LoadBalancing
Fields MeshesParticles
InterpolatorsFFTDifferentialOperators
MC++NTTPLINAC
POOMA Framework
KEY IDEAS
Numerical programming framework
Encapsulated parallelism
High-level API’s / data support
April 19, 2023 Hill Center
PDT (Malony, University of Oregon)
Program Database Toolkit Program analysis
multi-language(Fortran, C,C++, Java)
commercial-grade parsers
IL to programdatabase (PDB)
API for PDBaccess / query
Tools: instrumentation, code wrapping, documentation
April 19, 2023 Hill Center
SILOON (Advanced Computing Lab, LANL; UO)
Scripting Interface Language for OO Numerics Toolkit and run-time support for building easy-to-use
external interfaces to existing numerical codes Scripting language to “glue” components together
KEY IDEAS
Support for application interaction control
Support for application code wrapping
Application / tool coupling
Data exchange support
April 19, 2023 Hill Center
Metasystems and Metacomputing
Many resources accessible on the internet computers, data, devices, people
Extend single system model to internet domain wide-area (department, campus, region, country) scalable, transparent access to resources hides network complexity (“as if on your machine”)
Extend computing model to internet domain shared persistent space of objects (data, execution) heterogeneous distributed and parallel processing meta-applications (multi-component, hierarchical)
Deal with complex environment / primitive tools
April 19, 2023 Hill Center
“The GRID”
New applications based on high-speed coupling of people, computers, databases, instruments, ... computer-enhanced instruments collaborative engineering browsing of remote datasets use of remote software data-intensive computing very large-scale simulation large-scale parameter studies
April 19, 2023 Hill Center
GRID Architectural Picture
KEY IDEAS
Metasystems infrastructure / services
Metacomputing applications programming
GRID resources
April 19, 2023 Hill Center
NetSolve (Dongarra, University of Tennessee)
Client-server systemto access distributedcomputational / DBHW/SW resources
Distributed computing:resources, processes,data, users
Load-balancing policy for efficiency / performance Integration with arbitrary software components
C, Fortran, Java, MatLab, Mathematica, Excel BLAS, (Sca)LAPACK, MINPACK, FFTPACK
April 19, 2023 Hill Center
NetSolve Usage
“Blue collar” GRID-based computing users can set things up (without “su” privileges) no deep network programming knowledge required
Scenarios clients, servers, and agents anywhere on Internet clients, servers, and agents on an Intranet clients, servers, and agent on the same machine
Focus on MATLAB users OO-style language (objects are matrices) one of most popular desktop systems for numerical
computing (> 400K users)
April 19, 2023 Hill Center
NetSolve – The Client
NetSolve API hides complexity of numerical software Computation is location transparent Provides access to virtual libraries:
Component GRID-based framework Central management of library resources User not concerned with most up-to-date versions Automatic tie to Netlib repository
Synchronous or asynchronous calls User-level parallelism
April 19, 2023 Hill Center
Agent gateway to computational services performs load balancing and resource management
Server various software installed on various hardware configurable and extendable framework to easily add software many numerical libraries being integrated supports parallel computing
NetSolve – The Agent and Server
April 19, 2023 Hill Center
MCell (Bartol, Salk Institute; Salpeter, Cornell)
Monte Carlo simulator of cellular microphysiology Study how neurotransmitters diffuse and activate
receptors in synapses between different cells NetSolve distributes
processing workloadand allows access tocomputational resources
Simultaneous evaluationof large number ofdifferent parametercombinations
April 19, 2023 Hill Center
INTERLACE (Malony, University of Oregon)
INTERoperation and Linking Architecture for Computational Engines
Goals framework for building high-performance computing
environments from existing tools reusable components in heterogeneous environment abstract connection mechanisms for control/data flow resource management for dynamic operation use standard software technologies parallel and distributed computational environments
http://www.cs.uoregon.edu/research/paracomp/proj/interlace/
April 19, 2023 Hill Center
INTERLACE Components Computational engines: libraries or programs
providing specific functions Computational server: program interfacing multiple
engines with middleware Wrappers: server-engine interface for data/control Middleware: server-to-server interoperation software
KEY IDEAS
High-level numeric computational services
Access to metasystem resources
Wrapping/linking of computational engines
Dynamic, adaptable, extensible
High-level metasystems programming support
April 19, 2023 Hill Center
ViNE (Malony, University of Oregon)
Virtual Notebook Environment High-level, shared
notebooks, data, andtools in distributed,heterogenous system
Architecture leaves: notebook
functions and data stems: notebook
communication Web-based access
April 19, 2023 Hill Center
ViNE Experiment Builder
List of available, named data, tools, and experiments Visual dataflow model of experiment process Wrapped tools and databases
wrappedMATLAB
“tool”
April 19, 2023 Hill Center
Brain Electrophysiology Lab Notebook
Dense array EEG datasets
Commercial of the shelf statistical and numerical packages
Multiple machines types
Notebook content automatically generated from experiment results
April 19, 2023 Hill Center
PUNCH
Purdue University Network-Computing Hubs Educational and research computing “portals”
across the Purdue “enterprise” with affiliated institutions
Resource sharing by Purdue users computers, software, laboratory equipment educational materials
Distance education allows sharing of courses and instructors
Collaborative research
April 19, 2023 Hill Center
PUNCH – User’s and Developer’s View
Set of network-based laboratories that provide software tools for various fields
Specialized WWW-server interfaces WWW-browsers access software and download data run tools and view results
Tool specification Virtual laboratory
developmentenvironment
April 19, 2023 Hill Center
PUNCH Web Page
Hubs
April 19, 2023 Hill Center
PUNCH Tool Display Support via VNC
MATLABcommandwindow
X Windowsdisplay
MATLABinteractive
window
MATLABgraphicswindow
KEY IDEAS
Web-based access to tools
Web-based applications development
Web-based data, results, process management
April 19, 2023 Hill Center
Opportunities and the Neural Informatics Center
Integrated time-dynamic neuroimaging poses methodological, computational, and informatic challenges
Apply computer science technology to create problem solving environment for brain analysis neuroscientist defines methods and processes add value to environment through its use
Neural Informatics Center (NIC) within BBMI focus on single trial analysis problem advanced EEG/ERP analysis and integrated fMRI BEM/FEM brain models (EEG, CT, MRI)
April 19, 2023 Hill Center
Final Thoughts
Enable high-level problem solving environments Tools to enable scientists to compose solutions from
a set of building blocks Seamless access to local and remote resources Enabling infrastructure
framework standards and interfaces implementations of reusable components
Collaboration environments Future Neural Informatics Grid