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

Finn Årup Nielsen, Lars Kai Hansen

AbstractWe 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.
KeywordsNeuroinformatics, functional neuroimaging, BrainMap, Parzen window, novelty, outliers
TypeJournal paper [With referee]
JournalHuman Brain Mapping
Year2002    Month March    Vol. 15    No. 3    pp. 146-156
ISBN / ISSN1065-9471
NoteWiley's web version of the article might be unavailable because of a strange recurring technical problem. Please email fn(at) for a copy if you cannot obtain it
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BibTeX data [bibtex]
IMM Group(s)Intelligent Signal Processing

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