Mapping ERP patterns from heterogeneous datasets: A simulation study

Haishan Liu, Gwen Frishkoff, Robert Frank & Dejing Dou Department of Computer and Information Science, University of Oregon, USA NeuroInformatics Center, University of Oregon, USA Language Imaging Laboratory, Medical College of Wisconsin, USA Introduction: We describe an ontology-based method for representation and integration of neuroscience data, with an application to event-related brain potentials (ERPs). ERP datasets from different labs are highly heterogeneous, in that they are acquired in different experiment contexts and may be analyzed and described using different methods. To address this issue, we use data mining to discover mappings across ERP patterns derived from alternative analysis methods and from datasets that are summarized using different spatial and temporal measures. We then use the discovered mappings to develop machine-readable descriptions of ERP patterns, or “ontologies” [1]. The resulting ontologies are being used to support data sharing and cross-laboratory analysis of ERP experiment results within our Neural Electromagnetic Ontologies consortium [2].