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A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds
We introduce a graphical method originating from the computer graphics domain that is used for the arbitrary placement of cells over a two-dimensional manifold. Using a bitmap image whose luminance provides cell density, this method guarantees a discrete distribution of the positions of the cells re...
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2018
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869184/ https://www.ncbi.nlm.nih.gov/pubmed/29615887 http://dx.doi.org/10.3389/fninf.2018.00012 |
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author | Rougier, Nicolas P. |
author_facet | Rougier, Nicolas P. |
author_sort | Rougier, Nicolas P. |
collection | PubMed |
description | We introduce a graphical method originating from the computer graphics domain that is used for the arbitrary placement of cells over a two-dimensional manifold. Using a bitmap image whose luminance provides cell density, this method guarantees a discrete distribution of the positions of the cells respecting the local density. This method scales to any number of cells, allows one to specify arbitrary enclosing shapes and provides a scalable and versatile alternative to the more classical assumption of a uniform spatial distribution. The method is illustrated on a discrete homogeneous neural field, on the distribution of cones and rods in the retina and on the neural density of a flattened piece of cortex. |
format | Online Article Text |
id | pubmed-5869184 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-58691842018-04-03 A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds Rougier, Nicolas P. Front Neuroinform Neuroscience We introduce a graphical method originating from the computer graphics domain that is used for the arbitrary placement of cells over a two-dimensional manifold. Using a bitmap image whose luminance provides cell density, this method guarantees a discrete distribution of the positions of the cells respecting the local density. This method scales to any number of cells, allows one to specify arbitrary enclosing shapes and provides a scalable and versatile alternative to the more classical assumption of a uniform spatial distribution. The method is illustrated on a discrete homogeneous neural field, on the distribution of cones and rods in the retina and on the neural density of a flattened piece of cortex. Frontiers Media S.A. 2018-03-20 /pmc/articles/PMC5869184/ /pubmed/29615887 http://dx.doi.org/10.3389/fninf.2018.00012 Text en Copyright © 2018 Rougier. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Rougier, Nicolas P. A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title | A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title_full | A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title_fullStr | A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title_full_unstemmed | A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title_short | A Density-Driven Method for the Placement of Biological Cells Over Two-Dimensional Manifolds |
title_sort | density-driven method for the placement of biological cells over two-dimensional manifolds |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5869184/ https://www.ncbi.nlm.nih.gov/pubmed/29615887 http://dx.doi.org/10.3389/fninf.2018.00012 |
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