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Towards a Multiscale, High-Resolution Model of the Human Brain

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Book cover Brain-Inspired Computing (BrainComp 2013)

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Abstract

To understand the microscopical organization including cellular and fiber architecture it is a necessary prerequisite to build models of the human brain on a sound biological basis. We have recently pushed the limits of current technology by creating the first ultra-high resolution 3D-model of the human brain at nearly cellular resolution of 20 microns, the BigBrain model. At the same time, 3D Polarized Light Imaging provides a window to analyze the fiber architecture, i.e., the way, how brain regions are inter-connected, with unprecedented spatial resolution at the micrometer level. Considering the complexity and the pure size of the human brain with its nearly 86 billion nerve cells, both approaches are most challenging with respect to data handling and analysis in the TeraByte to PetaByte range, and require supercomputers. Parallelization and automation of image processing steps open up new perspectives to speed up the generation of new, ultra-high resolution models of the human brain, to provide new insights into the three-dimensional micro architecture of the human brain.

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Acknowledgement

The authors thank Janine Klapper for help in preparing the manuscript, and Thomas Lippert for scientific discussion and support. Daniel Mallmann and André Giesler from the “Federated Systems and Data” group at the Jülich Supercomputing Centre generously assisted with the adaptation of UNICORE to the specific workflow requirements.

Author information

Authors and Affiliations

  1. Research Centre Juelich, Institute of Neuroscience and Medicine (INM-1), Juelich, Germany

    Katrin Amunts & Markus Axer

  2. Cecile and Oskar Vogt Institute for Brain Research, Heinrich Heine University Düsseldorf, Düsseldorf, Germany

    Katrin Amunts

  3. Juelich Supercomputing Centre (JSC), Research Centre Juelich, Juelich, Germany

    Oliver Bücker

Authors
  1. Katrin Amunts
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  2. Oliver Bücker
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  3. Markus Axer
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Corresponding author

Correspondence to Katrin Amunts .

Editor information

Editors and Affiliations

  1. Faculty of Engineering, University of Calabria, Arcavacada di Rende, Italy

    Lucio Grandinetti

  2. Jülich Supercomputing Centre, Jülich, Germany

    Thomas Lippert

  3. Computing Science, University of Groningen Institute for Mathematics &, Groningen, The Netherlands

    Nicolai Petkov

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Amunts, K., Bücker, O., Axer, M. (2014). Towards a Multiscale, High-Resolution Model of the Human Brain. In: Grandinetti, L., Lippert, T., Petkov, N. (eds) Brain-Inspired Computing. BrainComp 2013. Lecture Notes in Computer Science(), vol 8603. Springer, Cham. https://doi.org/10.1007/978-3-319-12084-3_1

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  • DOI: https://doi.org/10.1007/978-3-319-12084-3_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-12083-6

  • Online ISBN: 978-3-319-12084-3

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