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Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks

Large-scale models of neuronal structures are needed to explore emergent properties of mammalian brains. Because these models have trillions of synapses, a major problem in their creation is synapse placement. Here we present a novel method for exploiting consistent fiber orientation in a neural tis...

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Detalles Bibliográficos
Autores principales: Zito, Jack, Memelli, Heraldo, Horn, Kyle G., Solomon, Irene C., Wittie, Larry D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi Publishing Corporation 2012
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465897/
https://www.ncbi.nlm.nih.gov/pubmed/23056037
http://dx.doi.org/10.1155/2012/876357
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author Zito, Jack
Memelli, Heraldo
Horn, Kyle G.
Solomon, Irene C.
Wittie, Larry D.
author_facet Zito, Jack
Memelli, Heraldo
Horn, Kyle G.
Solomon, Irene C.
Wittie, Larry D.
author_sort Zito, Jack
collection PubMed
description Large-scale models of neuronal structures are needed to explore emergent properties of mammalian brains. Because these models have trillions of synapses, a major problem in their creation is synapse placement. Here we present a novel method for exploiting consistent fiber orientation in a neural tissue to perform a highly efficient modified plane-sweep algorithm, which identifies all regions of 3D overlaps between dendritic and axonal projection fields. The first step in placing synapses in physiological models is neurite-overlap detection, at large scales a computationally intensive task. We have developed an efficient “Staggered Walk” algorithm that can find all 3D overlaps of neurites where trillions of synapses connect billions of neurons.
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spelling pubmed-34658972012-10-10 Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks Zito, Jack Memelli, Heraldo Horn, Kyle G. Solomon, Irene C. Wittie, Larry D. Comput Intell Neurosci Research Article Large-scale models of neuronal structures are needed to explore emergent properties of mammalian brains. Because these models have trillions of synapses, a major problem in their creation is synapse placement. Here we present a novel method for exploiting consistent fiber orientation in a neural tissue to perform a highly efficient modified plane-sweep algorithm, which identifies all regions of 3D overlaps between dendritic and axonal projection fields. The first step in placing synapses in physiological models is neurite-overlap detection, at large scales a computationally intensive task. We have developed an efficient “Staggered Walk” algorithm that can find all 3D overlaps of neurites where trillions of synapses connect billions of neurons. Hindawi Publishing Corporation 2012 2012-09-30 /pmc/articles/PMC3465897/ /pubmed/23056037 http://dx.doi.org/10.1155/2012/876357 Text en Copyright © 2012 Jack Zito et al. https://creativecommons.org/licenses/by/3.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Zito, Jack
Memelli, Heraldo
Horn, Kyle G.
Solomon, Irene C.
Wittie, Larry D.
Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title_full Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title_fullStr Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title_full_unstemmed Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title_short Application of a “Staggered Walk” Algorithm for Generating Large-Scale Morphological Neuronal Networks
title_sort application of a “staggered walk” algorithm for generating large-scale morphological neuronal networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3465897/
https://www.ncbi.nlm.nih.gov/pubmed/23056037
http://dx.doi.org/10.1155/2012/876357
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