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Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body

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Abstract 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.
Title: Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body
Description:
Abstract 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.

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