Neuroinformatics

, Volume 12, Issue 2, pp 277–289

VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function

  • John Edwards
  • Eric Daniel
  • Justin Kinney
  • Tom Bartol
  • Terrence Sejnowski
  • Daniel Johnston
  • Kristen Harris
  • Chandrajit Bajaj
Software Original Article

DOI: 10.1007/s12021-013-9205-2

Cite this article as:
Edwards, J., Daniel, E., Kinney, J. et al. Neuroinform (2014) 12: 277. doi:10.1007/s12021-013-9205-2

Abstract

Establishing meaningful relationships between cellular structure and function requires accurate morphological reconstructions. In particular, there is an unmet need for high quality surface reconstructions to model subcellular and synaptic interactions among neurons and glia at nanometer resolution. We address this need with VolRoverN, a software package that produces accurate, efficient, and automated 3D surface reconstructions from stacked 2D contour tracings. While many techniques and tools have been developed in the past for 3D visualization of cellular structure, the reconstructions from VolRoverN meet specific quality criteria that are important for dynamical simulations. These criteria include manifoldness, water-tightness, lack of self- and object-object-intersections, and geometric accuracy. These enhanced surface reconstructions are readily extensible to any cell type and are used here on spiny dendrites with complex morphology and axons from mature rat hippocampal area CA1. Both spatially realistic surface reconstructions and reduced skeletonizations are produced and formatted by VolRoverN for easy input into analysis software packages for neurophysiological simulations at multiple spatial and temporal scales ranging from ion electro-diffusion to electrical cable models.

Keywords

Electron microscopy Serial sections 3-D reconstruction Neuropil Skeletonization Reduced model Electrophysiology 

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • John Edwards
    • 1
  • Eric Daniel
    • 1
  • Justin Kinney
    • 2
  • Tom Bartol
    • 3
    • 4
  • Terrence Sejnowski
    • 3
    • 4
    • 5
  • Daniel Johnston
    • 6
  • Kristen Harris
    • 6
  • Chandrajit Bajaj
    • 1
  1. 1.Department of Computer Science, ICESThe University of TexasAustinUSA
  2. 2.Massachussetts Institute of TechnologyCambridgeUSA
  3. 3.Howard Hughes Medical InstituteChevy ChaseUSA
  4. 4.Salk Institute for Biological StudiesLa JollaUSA
  5. 5.University of California at San DiegoSan DiegoUSA
  6. 6.Center for Learning and MemoryThe University of TexasAustinUSA

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