Modeling of activation data in the BrainMapTM database: Detection of outliers

Publication: Research - peer-reviewJournal article – Annual report year: 2002

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We describe a system for meta-analytical modeling of activation foci from functional neuroimaging studies. Our main vehicle is a set of density models in Talairach space capturing the distribution of activation foci in sets of experiments labeled by lobar anatomy. One important use of such density models is identification of novelty, i.e., low probability database events. We rank the novelty of the outliers and investigate the cause for 21 of the most novel, finding several outliers that are entry and transcription errors or infrequent or non-conforming terminology. We briefly discuss the use of atlases for outlier detection. Hum. Brain Mapping 15:146-156, 2002. © 2002 Wiley-Liss, Inc.
Original languageEnglish
JournalHuman Brain Mapping
Publication date2002
Volume15
Journal number3
Pages146-156
ISSN1065-9471
DOIs
StatePublished
CitationsWeb of Science® Times Cited: No match on DOI

Keywords

  • functional neuroimaging, BrainMap, Neuroinformatics, outliers, Parzen window, novelty
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