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Exploratory fMRI Analysis without Spatial Normalization

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Information Processing in Medical Imaging (IPMI 2009)

Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 5636))

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Abstract

We present an exploratory method for simultaneous parcellation of multisubject fMRI data into functionally coherent areas. The method is based on a solely functional representation of the fMRI data and a hierarchical probabilistic model that accounts for both inter-subject and intra-subject forms of variability in fMRI response. We employ a Variational Bayes approximation to fit the model to the data. The resulting algorithm finds a functional parcellation of the individual brains along with a set of population-level clusters, establishing correspondence between these two levels. The model eliminates the need for spatial normalization while still enabling us to fuse data from several subjects. We demonstrate the application of our method on a visual fMRI study.

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Author information

Authors and Affiliations

  1. Computer Science and Artificial Intelligence Laboratory, MIT, USA

    Danial Lashkari & Polina Golland

Authors
  1. Danial Lashkari
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  2. Polina Golland
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Editor information

Editors and Affiliations

  1. Department of Electrical and Computer Engineering, Johns Hopkins University, 3400 North Charles Street, MD 21218, Baltimore, USA

    Jerry L. Prince

  2. Department of Radiology, Johns Hopkins University, 600 North Wolfe Street, MD 21287, Baltimore, USA

    Dzung L. Pham

  3. Division of Imaging and Applied Mathematics, OSEL, U.S. Food and Drug Administration, 10903 New Hampshire Avenue, MD 20993, Silver Spring, USA

    Kyle J. Myers

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© 2009 Springer-Verlag Berlin Heidelberg

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Lashkari, D., Golland, P. (2009). Exploratory fMRI Analysis without Spatial Normalization. In: Prince, J.L., Pham, D.L., Myers, K.J. (eds) Information Processing in Medical Imaging. IPMI 2009. Lecture Notes in Computer Science, vol 5636. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02498-6_33

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  • DOI: https://doi.org/10.1007/978-3-642-02498-6_33

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02497-9

  • Online ISBN: 978-3-642-02498-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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