Mining for associations between text and brain activation in a functional neuroimaging database

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    Abstract

    We describe a method for mining a neuroimaging database for associations between text and brain locations. The objective is to discover association rules between words indicative of cognitive function as described in abstracts of neuroscience papers and sets of reported stereotactic Talairach coordinates. We invoke a simple probabilistic framework in which kernel density estimates are used to model distributions of brain activation foci conditioned on words in a given abstract. The principal associations are found in the joint probability density between words and voxels. We show that the statistically motivated associations are well aligned with general neuroscientific knowledge.
    Original languageEnglish
    JournalNeuroinformatics
    Volume2
    Issue number4
    Pages (from-to)369-379
    ISSN1539-2791
    Publication statusPublished - 2004

    Keywords

    • data mining
    • meta-analysis
    • information storage and retrieval
    • databases
    • brain mapping
    • magnetic resonance imaging
    • data interpretation
    • neuroirnaging
    • positron-emission tomography
    • statistical

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