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

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....

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Main Authors: Edwards, John, Daniel, Eric, Bartol, Tom, Sejnowski, Terrence, Johnston, Daniel, Harris, Kristen, Bajaj, Chandrajit, Kinney, Justin
Other Authors: Massachusetts Institute of Technology. Media Laboratory
Format: Article
Language:English
Published: Springer US 2016
Online Access:http://hdl.handle.net/1721.1/105864
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author Edwards, John
Daniel, Eric
Bartol, Tom
Sejnowski, Terrence
Johnston, Daniel
Harris, Kristen
Bajaj, Chandrajit
Kinney, Justin
author2 Massachusetts Institute of Technology. Media Laboratory
author_facet Massachusetts Institute of Technology. Media Laboratory
Edwards, John
Daniel, Eric
Bartol, Tom
Sejnowski, Terrence
Johnston, Daniel
Harris, Kristen
Bajaj, Chandrajit
Kinney, Justin
author_sort Edwards, John
collection MIT
description 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.
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spelling mit-1721.1/1058642022-09-28T17:51:52Z VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function Edwards, John Daniel, Eric Bartol, Tom Sejnowski, Terrence Johnston, Daniel Harris, Kristen Bajaj, Chandrajit Kinney, Justin Massachusetts Institute of Technology. Media Laboratory Program in Media Arts and Sciences (Massachusetts Institute of Technology) Kinney, Justin 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. 2016-12-16T23:18:20Z 2016-12-16T23:18:20Z 2013-10 2016-08-18T15:45:46Z Article http://purl.org/eprint/type/JournalArticle 1539-2791 1559-0089 http://hdl.handle.net/1721.1/105864 Edwards, John, Eric Daniel, Justin Kinney, Tom Bartol, Terrence Sejnowski, Daniel Johnston, Kristen Harris, and Chandrajit Bajaj. “VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function.” Neuroinformatics 12, no. 2 (October 8, 2013): 277–289. en http://dx.doi.org/10.1007/s12021-013-9205-2 Neuroinformatics Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use. Springer Science+Business Media New York application/pdf Springer US Springer US
spellingShingle Edwards, John
Daniel, Eric
Bartol, Tom
Sejnowski, Terrence
Johnston, Daniel
Harris, Kristen
Bajaj, Chandrajit
Kinney, Justin
VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title_full VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title_fullStr VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title_full_unstemmed VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title_short VolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Function
title_sort volrovern enhancing surface and volumetric reconstruction for realistic dynamical simulation of cellular and subcellular function
url http://hdl.handle.net/1721.1/105864
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