Skip to content
DraconiticResearch
Search Sources API
203,234 studies31 sourcesUpdated 12 min ago
Peer-reviewedCC BY 4.0Scientific Reports

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

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.

Related

  1. Semi-Automated CellProfiler Pipelines for Robust Quantification of Microglial Density, Distribution and Morphology
    B. C. Bobotis, A. Landwehr, V. Hadera +3
    bioRxivPreprintCC BY-NDFull text1 citedCell biologybioRxiv
  2. Breaking the bottleneck: semi-automated quantification of actin filament dynamics
    A. D. Nobles, D. M. Rutkowski, C. R. Belden +4
    bioRxivPreprintCC BY-NC-NDFull textCell biologybioRxiv
  3. BeatRatePy - Automated Hight-Throughput Python-Based Beat Rate Quantification and Generation of Speed and Contraction Traces
    M. Held, W. Partington, T. Waring +8
    bioRxivPreprintCC BYFull textCell biologybioRxiv
  4. Automated compartment-based quantification reveals distinct patterns of cutaneous innervation with aging and microbial colonization
    H. Le Chang, M. Lee, L. Schneider +4
    bioRxivPreprintCC BYFull textNeurosciencebioRxivEurope PMC
  5. Automated Cerebrospinal Fluid Flow Quantification in Hydrocephalus Using Phase‐Contrast Magnetic Resonance Imaging
    Eder Alejandro Rodríguez Martínez, Pan Liu, Kimi Owashi +2
    NMR in BiomedicinePeer-reviewedCC BY 4.0Full textNeuroscienceHALPMCEurope PMC
BibTeX
@article{cabirol2026automated,
  title = {{Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body}},
  author = {Amélie Cabirol and Albrecht Haase},
  journal = {Scientific Reports},
  year = {2026},
  month = sep,
  doi = {10.1038/s41598-019-55974-2},
  url = {https://hal.science/hal-05762972v1},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Automated quantification of synaptic boutons reveals their 3D distribution in the honey bee mushroom body
AU  - Amélie Cabirol
AU  - Albrecht Haase
PY  - 2026
DA  - 2026/09/24
JO  - Scientific Reports
DO  - 10.1038/s41598-019-55974-2
UR  - https://hal.science/hal-05762972v1
AB  - 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.
SN  - 2045-2322
ER  -