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dc.contributor.authorEdwards, John
dc.contributor.authorDaniel, Eric
dc.contributor.authorBartol, Tom
dc.contributor.authorSejnowski, Terrence
dc.contributor.authorJohnston, Daniel
dc.contributor.authorHarris, Kristen
dc.contributor.authorBajaj, Chandrajit
dc.contributor.authorKinney, Justin
dc.date.accessioned2016-12-16T23:18:20Z
dc.date.available2016-12-16T23:18:20Z
dc.date.issued2013-10
dc.identifier.issn1539-2791
dc.identifier.issn1559-0089
dc.identifier.urihttp://hdl.handle.net/1721.1/105864
dc.description.abstractEstablishing 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.en_US
dc.publisherSpringer USen_US
dc.relation.isversionofhttp://dx.doi.org/10.1007/s12021-013-9205-2en_US
dc.rightsArticle 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.en_US
dc.sourceSpringer USen_US
dc.titleVolRoverN: Enhancing Surface and Volumetric Reconstruction for Realistic Dynamical Simulation of Cellular and Subcellular Functionen_US
dc.typeArticleen_US
dc.identifier.citationEdwards, 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_US
dc.contributor.departmentMassachusetts Institute of Technology. Media Laboratoryen_US
dc.contributor.departmentProgram in Media Arts and Sciences (Massachusetts Institute of Technology)en_US
dc.contributor.mitauthorKinney, Justin
dc.relation.journalNeuroinformaticsen_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/JournalArticleen_US
eprint.statushttp://purl.org/eprint/status/PeerRevieweden_US
dc.date.updated2016-08-18T15:45:46Z
dc.language.rfc3066en
dc.rights.holderSpringer Science+Business Media New York
dspace.orderedauthorsEdwards, John; Daniel, Eric; Kinney, Justin; Bartol, Tom; Sejnowski, Terrence; Johnston, Daniel; Harris, Kristen; Bajaj, Chandrajiten_US
dspace.embargo.termsNen
mit.licensePUBLISHER_POLICYen_US


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