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Haishan Liu 1, Gwen Frishkoff 2, Robert Frank 1, Dejing Dou 1 1 University of Oregon 2 Georgia State University

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ERP (Event-Related Potentials): a direct measure of neuronal activity Lack of meta-analysis across experiment NEMO (Neural ElectroMagnetic Ontologies) for data sharing and integration Goal of the presented study Mapping alternative sets of ERP spatial and temporal measures

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Alternative sets of ERP metrics

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Semi-structured data

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Uninformative column headers

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Semi-structured data Uninformative column headers Numerical values

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Cluster labels Meaningful labels Point-sequence curve

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Process all point- sequence curves Calculate Euclidean distance between sequences in the Cartesian product set (Cross-spatial join) Metric Set1 Metric Set2

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the two datasets contain the same or similar ERP patterns

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1-to-1 mapping between metrics

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the two datasets contain the same or similar ERP patterns 1-to-1 mapping between metrics Minimum sum of distances 4.01 + 3.74 > 4.08 + 3.57

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Wrong Mappings. Precision = 9/13 Gold standard mapping falls along the diagonal cells

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3-Factor design of experiment data (Fully factorial: 2 x 2 x 2) 2 simulated subject groups (samples) SG1 = sample 1 SG2 = sample 2 2 data decompositions tPCA = temporal PCA decomposition sICA = spatial ICA decomposition 2 sets of alternative metrics m1 = metric set 1 m2 = metric set 2

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Overall Precision: 84.6%

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Use of an ontology to assign meaningful labels to ERP patterns Application of sequence similarity search in discovering mappings across alternative metrics Extension of the instance-level approach in schema matching Articulation of a global minimum heuristic

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Questions and comments? Please contact Haishan Liu (ahoyleo@cs.uoregon.edu)