Testing for difference between two groups of functional neuroimaging experiments

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    Abstract

    We describe a meta-analytic method that tests for the difference between two groups of functional neuroimaging experiments. We use kernel density estimation in three-dimensional brain space to convert points representing focal brain activations into a voxel-based representation. We find the maximum in the subtraction between two probability densities and compare its value against a resampling distribution obtained by permuting the labels of the two groups. As such it appears as a general method for comparing the local intensity of two non-stationary spatial point processes. The method is applied on data from thermal pain studies where "hot pain" and "cold pain" form the two groups.
    Original languageEnglish
    Title of host publicationDen 13. Danske Konference i Mønstergenkendelse og Billedanalyse
    PublisherDepartment of Computer Science, University of Copenhagen (DIKU)
    Publication date2004
    Publication statusPublished - 2004

    Cite this

    Nielsen, F. Å., Chen, A. C. N., & Hansen, L. K. (2004). Testing for difference between two groups of functional neuroimaging experiments. In Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse Department of Computer Science, University of Copenhagen (DIKU).
    Nielsen, Finn Årup ; Chen, Andrew C. N. ; Hansen, Lars Kai. / Testing for difference between two groups of functional neuroimaging experiments. Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse. Department of Computer Science, University of Copenhagen (DIKU), 2004.
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    Nielsen, FÅ, Chen, ACN & Hansen, LK 2004, Testing for difference between two groups of functional neuroimaging experiments. in Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse. Department of Computer Science, University of Copenhagen (DIKU).

    Testing for difference between two groups of functional neuroimaging experiments. / Nielsen, Finn Årup; Chen, Andrew C. N.; Hansen, Lars Kai.

    Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse. Department of Computer Science, University of Copenhagen (DIKU), 2004.

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearch

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    N2 - We describe a meta-analytic method that tests for the difference between two groups of functional neuroimaging experiments. We use kernel density estimation in three-dimensional brain space to convert points representing focal brain activations into a voxel-based representation. We find the maximum in the subtraction between two probability densities and compare its value against a resampling distribution obtained by permuting the labels of the two groups. As such it appears as a general method for comparing the local intensity of two non-stationary spatial point processes. The method is applied on data from thermal pain studies where "hot pain" and "cold pain" form the two groups.

    AB - We describe a meta-analytic method that tests for the difference between two groups of functional neuroimaging experiments. We use kernel density estimation in three-dimensional brain space to convert points representing focal brain activations into a voxel-based representation. We find the maximum in the subtraction between two probability densities and compare its value against a resampling distribution obtained by permuting the labels of the two groups. As such it appears as a general method for comparing the local intensity of two non-stationary spatial point processes. The method is applied on data from thermal pain studies where "hot pain" and "cold pain" form the two groups.

    KW - Neuroinformatics

    KW - kernel density estimation

    M3 - Article in proceedings

    BT - Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse

    PB - Department of Computer Science, University of Copenhagen (DIKU)

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    Nielsen FÅ, Chen ACN, Hansen LK. Testing for difference between two groups of functional neuroimaging experiments. In Den 13. Danske Konference i Mønstergenkendelse og Billedanalyse. Department of Computer Science, University of Copenhagen (DIKU). 2004