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An Unsupervised Group Average Cortical Parcellation Using Diffusion MRI to Probe Cytoarchitecture

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Computational Diffusion MRI (MICCAI 2016)

Part of the book series: Mathematics and Visualization ((MATHVISUAL))

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Abstract

Cortical parcellations provide valuable localisation resources for other neuroimaging modalities such as fMRI as well as insight into the structure-function relationship of the brain. The venerable but now dated ex vivo Brodmann map is currently being superseded by in vivo techniques that can better take into account intersubject variability. One popular in vivo method focusses on myeloarchitecture by measuring T1. This, however, probes only one aspect of cortical microstructure and is less useful in regions of low myelination. In contrast, diffusion MRI (dMRI) is sensitive to several additional microstructural features and can potentially provide a richer set of information regarding the architecture of grey matter microcircuitry. The following study used 3T HARDI data of multiple subjects to produce an entirely unsupervised, hemisphere-wide, group-average, parcellation. A qualitative assessment of the resulting cortical parcellation demonstrates several spatially coherent clusters in areas corresponding to well known functional anatomical areas. In addition, it exhibits some cluster boundaries that correlate with independently derived myelin mapping data for the same set of subjects, whilst also providing distinct clusters in areas (e.g., within MT+) where myelination is a less informative measurement.

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Author information

Authors and Affiliations

  1. Department of Cognitive, Perceptual and Brain Sciences, University College London, London, UK

    Tara Ganepola & Martin I. Sereno

  2. Department of Computer Science, Centre for Medical Image Computing, University College London, London, UK

    Tara Ganepola & Daniel C. Alexander

  3. Laboratory for Social and Neural Systems Research University of Zurich, Zurich, Switzerland

    Zoltan Nagy

  4. Wellcome Trust Centre for Neuroimaging, UCL Institute of Neurology, London, UK

    Zoltan Nagy

Authors
  1. Tara Ganepola
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  2. Zoltan Nagy
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  3. Daniel C. Alexander
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  4. Martin I. Sereno
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Corresponding author

Correspondence to Tara Ganepola .

Editor information

Editors and Affiliations

  1. Department of Mathematics and Computer Science, Eindhoven University of Technology, Eindhoven, The Netherlands

    Andrea Fuster

  2. Centre for Medical Image Computing, University College London, London, United Kingdom

    Aurobrata Ghosh

  3. Centre for Medical Image Computing, University College London, London, United Kingdom

    Enrico Kaden

  4. Department of Psychiatry, Brigham & Womens Hospital, Boston, Massachusetts, USA

    Yogesh Rathi

  5. Medical Physics, University Medical Center, Freiburg, Germany

    Marco Reisert

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Ganepola, T., Nagy, Z., Alexander, D.C., Sereno, M.I. (2017). An Unsupervised Group Average Cortical Parcellation Using Diffusion MRI to Probe Cytoarchitecture. In: Fuster, A., Ghosh, A., Kaden, E., Rathi, Y., Reisert, M. (eds) Computational Diffusion MRI. MICCAI 2016. Mathematics and Visualization. Springer, Cham. https://doi.org/10.1007/978-3-319-54130-3_12

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