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February 26, 2010

February 26, 2010. NEMO All-Hands Meeting: Overview of Day 1. http://nemo.nic.uoregon.edu. Overview Today’s Agenda. Introductions & review of NEMO project aims (GAF) Overview of data analysis workflow (RMF) Intro to EEGLAB & NEMO simERP test data (GF/RMF) LUNCH

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February 26, 2010

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  1. February 26, 2010 NEMO All-Hands Meeting: Overview of Day 1 http://nemo.nic.uoregon.edu

  2. Overview Today’s Agenda • Introductions & review of NEMO project aims (GAF) • Overview of data analysis workflow (RMF) • Intro to EEGLAB & NEMO simERP test data (GF/RMF) LUNCH • EEGLAB visualization tutorial • NEMO_Pattern_Decomposition tutorial #1 • NEMO_Pattern_Decomposition tutorial #2

  3. (Re)Introductions: Who we are • NEMO “Core” (PIs & go-to people) • Dejing Dou (lead PI, CIS — Oregon) • Gwen Frishkoff (co-PI, Psychology — GSU) • Allen Malony (co-I, CIS — Oregon) • Don Tucker (co-I, Psychology — Oregon) • Robert Frank (EEG/ERP Analysis Tools) • Paea LePendu (Ontology Development) • Snezana Nikolic (Ontology Curation) • Jason Sydes (Database & Web Portal) • Haishan Liu (Grad Student, CIS)

  4. (Re)Introductions: Who we are • NEMO Consortium • John Connolly & Alex Beaverstone (McMaster U) • Tim Curran & Chris Bird (U Colorado) • Kerry Kilborn & Stephanie Connell (Glasgow U) • Dennis Molfese (U Louisville) • Chuck Perfetti (U Pittsburgh)

  5. Overview of NEMO Project Aims • Design and test procedures for automated & robust ERP pattern analysis and classification • Capture rules, concepts in a formal ERP ontology • Develop ontology-based tools for ERP data markup • Apply ERP analysis tools to consortium datasets • Perform meta-analyses of consortium data • Build data storage & management system

  6. The three pillars of NEMO • ERP Ontologies • ERP Data • ERP Database & portal

  7. The three pillars of NEMO Focus of this All-Hands Meeting • ERP Ontologies • ERP Data • ERP Database & portal

  8. TUTORIAL #1:Viewing ERP Data in EEGLAB TUTORIAL #2:Decomposition with PCA TUTORIAL #3:Segmentation with Microstates TODAY

  9. TUTORIAL #4:Extracting ontology-based attributes And exporting to text or RDF TOMORROW

  10. Two classes of methods for NEMO_ERP_pattern_extractraction • Pattern decomposition • Temporal factor analysis (tPCA, tICA) • Spatial factor analysis (sPCA, sICA) • etc. • Pattern segmentation (i.e., windowing) • Microstate analysis (5 flavors – Bob will describe)

  11. Decomposition approach 100ms P100 PCA, ICA, dipoles etc. multiple methods for principled separation of patterns using factor-analytic approach 170ms N100 200ms fP2 P1r/ N3 280ms 400ms P1r/ MFN 600ms P300

  12. Windowing/segmentation approach • Advantages over factor-analytic/ decomposition methods: • Familiarity — Closer to what most ERP researchers do (manually) • Less (or at least different!) concerns regarding misallocation of variance • Robustness to latency diffs across subjects, conditions 100ms P100 170ms N100 200ms fP2 P1r/ N3 280ms 400ms P1r/ MFN 600ms P300 Michel, et al., 2004; Koenig, 1995; Lehmann & Skrandies, 1985

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