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Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body
Synaptic boutons are highly plastic structures undergoing experience-dependent changes in their number, volume, and shape. Their plasticity has been intensively studied in the insect mushroom bodies by manually counting the number of boutons in small regions of interest and extrapolating this number...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920473/ https://www.ncbi.nlm.nih.gov/pubmed/31852957 http://dx.doi.org/10.1038/s41598-019-55974-2 |
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author | Cabirol, Amélie Haase, Albrecht |
author_facet | Cabirol, Amélie Haase, Albrecht |
author_sort | Cabirol, Amélie |
collection | PubMed |
description | Synaptic boutons are highly plastic structures undergoing experience-dependent changes in their number, volume, and shape. Their plasticity has been intensively studied in the insect mushroom bodies by manually counting the number of boutons in small regions of interest and extrapolating this number to the volume of the mushroom body neuropil. Here we extend this analysis to the synaptic bouton distribution within a larger subregion of the mushroom body olfactory neuropil of honey bees (Apis mellifera). This required the development of an automated method combining two-photon imaging with advanced image post-processing and multiple threshold segmentation. The method was first validated in subregions of the mushroom body olfactory and visual neuropils. Further analyses in the olfactory neuropil suggested that previous studies overestimated the number of synaptic boutons. As a reason for that, we identified boundaries effects in the small volume samples. The application of the automated analysis to larger volumes of the mushroom body olfactory neuropil revealed a corrected average density of synaptic boutons and, for the first time, their 3D spatial distribution. This distribution exhibited a considerable heterogeneity. This additional information on the synaptic bouton distribution provides the basis for future studies on brain development, symmetry, and plasticity. |
format | Online Article Text |
id | pubmed-6920473 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69204732019-12-20 Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body Cabirol, Amélie Haase, Albrecht Sci Rep Article Synaptic boutons are highly plastic structures undergoing experience-dependent changes in their number, volume, and shape. Their plasticity has been intensively studied in the insect mushroom bodies by manually counting the number of boutons in small regions of interest and extrapolating this number to the volume of the mushroom body neuropil. Here we extend this analysis to the synaptic bouton distribution within a larger subregion of the mushroom body olfactory neuropil of honey bees (Apis mellifera). This required the development of an automated method combining two-photon imaging with advanced image post-processing and multiple threshold segmentation. The method was first validated in subregions of the mushroom body olfactory and visual neuropils. Further analyses in the olfactory neuropil suggested that previous studies overestimated the number of synaptic boutons. As a reason for that, we identified boundaries effects in the small volume samples. The application of the automated analysis to larger volumes of the mushroom body olfactory neuropil revealed a corrected average density of synaptic boutons and, for the first time, their 3D spatial distribution. This distribution exhibited a considerable heterogeneity. This additional information on the synaptic bouton distribution provides the basis for future studies on brain development, symmetry, and plasticity. Nature Publishing Group UK 2019-12-18 /pmc/articles/PMC6920473/ /pubmed/31852957 http://dx.doi.org/10.1038/s41598-019-55974-2 Text en © The Author(s) 2019 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Cabirol, Amélie Haase, Albrecht Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title | Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title_full | Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title_fullStr | Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title_full_unstemmed | Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title_short | Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body |
title_sort | automated quantification of synaptic boutons reveals their 3d distribution in the honey bee mushroom body |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6920473/ https://www.ncbi.nlm.nih.gov/pubmed/31852957 http://dx.doi.org/10.1038/s41598-019-55974-2 |
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