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Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity

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Abstract

Analytic tools for addressing spontaneous brain activity, as acquired with fMRI during the “resting-state,” have grown dramatically over the past decade. Along with each new technique, novel hypotheses about the functional organization of the brain are also available to researchers. We review six prominent categories of resting-state fMRI data analysis: seed-based functional connectivity, independent component analysis, clustering, pattern classification, graph theory, and two “local” methods. In surveying these methods, we address their underlying assumptions, methodologies, and novel applications.

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Authors and Affiliations

  1. Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany

    Daniel S. Margulies, Xiangyu Long, Yating Lv, Alexander Schäfer, Dirk Goldhahn, Gabriele Lohmann & Arno Villringer

  2. Department of Neurosurgery, Charité—Universitätsmedizin, Berlin, Germany

    Joachim Böttger & Alexander Abbushi

  3. P. Green and R. Cōwen Institute for Pediatric Neuroscience, New York University School of Medicine, New York, USA

    Clare Kelly & Michael P. Milham

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  1. Daniel S. Margulies
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D. S. Margulies and J. Böttger contributed equally.

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Margulies, D.S., Böttger, J., Long, X. et al. Resting developments: a review of fMRI post-processing methodologies for spontaneous brain activity. Magn Reson Mater Phy 23, 289–307 (2010). https://doi.org/10.1007/s10334-010-0228-5

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