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International Symposium on Visual Computing

ISVC 2015: Advances in Visual Computing pp 3–13Cite as

Graph-Based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling

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Part of the book series: Lecture Notes in Computer Science ((LNIP,volume 9474))

Abstract

Neuronal connectivity matrices contain information vital to the understanding of brain structure and function. In this work we present graph-based visualization techniques for macroscale connectivity matrices that retain anatomical context while reducing the clutter and occlusion problems that plague 2D and 3D node-link diagrams. By partitioning the connectivity matrix into blocks corresponding to brain hemispheres and bundling graph edges we are able to generate intuitive visualizations that permit investigation at multiple scales (hemisphere, lobe, anatomical region). We demonstrate our approach on connectivity matrices computed using tractography of high angular resolution diffusion images acquired as part of a Parkinson’s disease study.

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Author information

Authors and Affiliations

  1. Purdue University, West Lafayette, USA

    Tim McGraw

Authors
  1. Tim McGraw
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Corresponding author

Correspondence to Tim McGraw .

Editor information

Editors and Affiliations

  1. University of Nevada, Reno, Nevada, USA

    George Bebis

  2. NASA Ames Research Center, Moffett Field, California, USA

    Richard Boyle

  3. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Bahram Parvin

  4. Desert Research Institute, Reno, Nevada, USA

    Darko Koracin

  5. University of Houston, Houston, Texas, USA

    Ioannis Pavlidis

  6. IBM T.J. Watson Research Center, Yorktown Heights, New York, USA

    Rogerio Feris

  7. Purdue University, West Lafayette, Indiana, USA

    Tim McGraw

  8. Side Effects Software, Santa Monica, California, USA

    Mark Elendt

  9. The DiVE, Durham, North Carolina, USA

    Regis Kopper

  10. Texas A&M University, College Station, Texas, USA

    Eric Ragan

  11. Kent State University, Kent, Ohio, USA

    Zhao Ye

  12. Lawrence Berkeley National Laboratory, Berkeley, California, USA

    Gunther Weber

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© 2015 Springer International Publishing Switzerland

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McGraw, T. (2015). Graph-Based Visualization of Neuronal Connectivity Using Matrix Block Partitioning and Edge Bundling. In: Bebis, G., et al. Advances in Visual Computing. ISVC 2015. Lecture Notes in Computer Science(), vol 9474. Springer, Cham. https://doi.org/10.1007/978-3-319-27857-5_1

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  • DOI: https://doi.org/10.1007/978-3-319-27857-5_1

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-27856-8

  • Online ISBN: 978-3-319-27857-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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