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SynBot is an open-source image analysis software for automated quantification of synapses

Output Details

Preprint June 26, 2024

Published September 9, 2024

The formation of precise numbers of neuronal connections, known as synapses, is crucial for brain function. Therefore, synaptogenesis mechanisms have been one of the main focuses of neuroscience. Immunohistochemistry is a common tool for visualizing synapses. Thus, quantifying the numbers of synapses from light microscopy images enables screening the impacts of experimental manipulations on synapse development. Despite its utility, this approach is paired with low throughput analysis methods that are challenging to learn and results are variable between experimenters, especially when analyzing noisy images of brain tissue. We developed an open-source ImageJ-based software, SynBot, to address these technical bottlenecks by automating the analysis. SynBot incorporates the advanced algorithms ilastik and SynQuant for accurate thresholding for synaptic puncta identification, and the code can easily be modified by users. The use of this software will allow for rapid and reproducible screening of synaptic phenotypes in healthy and diseased nervous systems.
Tags
  • Algorithms
  • Analysis
  • Imaging
  • Immunofluorescence
  • Machine learning
  • Original Research
  • Synapse

Meet the Authors

  • User avatar fallback logo

    Justin Savage, BSc

    Key Personnel: Team Calakos

    Duke University

  • User avatar fallback logo

    Juan Ramirez

    External Collaborator

  • User avatar fallback logo

    W. Christopher Risher

    External Collaborator

  • User avatar fallback logo

    Yihzi Wang

    External Collaborator

  • User avatar fallback logo

    Dolores Ilara

    External Collaborator

  • Cagla Eroglu, PhD

    Co-PI (Core Leadership): Team Calakos

    Duke University

Aligning Science Across Parkinson's
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