Cited by 13Cell Image Analysis TechniquesNeuroscience and Neuropharmacology ResearchNeural dynamics and brain function

ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology

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Jin, Dezhe Z., Zhao, Ting, Hunt, David L., Tillage, Rachel P., Hsu, Ching-Lung, Spruston, Nelson·2019·Frontiers in Neuroinformatics

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Abstract

Abstract Neurons perform computations by integrating inputs from thousands of synapses – mostly in the dendritic tree – to drive action potential firing in the axon. One fruitful approach to understanding this process is to record from neurons using patch-clamp electrodes, fill the recorded neuron with a substance that allows subsequent staining, reconstruct the three-dimensional architecture of the dendrites, and use the resulting functional and structural data to develop computer models of dendritic integration. Accurately producing quantitative reconstructions of dendrites is typically a tedious process taking many hours of manual inspection and measurement. Here we present ShuTu, a new software package that facilitates accurate and efficient reconstruction of dendrites imaged using bright-field microscopy. The program operates in two steps: (1) automated identification of dendritic process, and (2) manual correction of errors in the automated reconstruction. This approach allows neurons with complex dendritic morphologies to be reconstructed rapidly and efficiently, thus facilitating the use of computer models to study dendritic structure-function relationships and the computations performed by single neurons. Significance Statement We developed a software package – ShuTu – that integrates automated reconstruction of stained neurons with manual error correction. This package facilitates rapid reconstruction of the three-dimensional geometry of neuronal dendritic trees, often needed for computational simulations of the functional properties of these structures.

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  1. Jin D. Z. Zhao T. Hunt D. L. Pearcy R. Hsu C.-L. Spruston N. (2017). ShuTu: open-source software for efficient and accurate reconstruction of dendritic morphology. bioRxiv [preprint] 226548 10.1101/226548 PMC6834530 31736735 · DOI

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Authors
Jin, D. Z., Zhao, T., Hunt, D. L., Tillage, R. P., Hsu, C.-L., & Spruston, N.
Affiliations
  • Pennsylvania State University (US)
  • Howard Hughes Medical Institute (US)
Corresponding author
  • Jin, Dezhe Z.
  • Spruston, Nelson
Venue
Frontiers in Neuroinformatics
Published
2019-10-31
Volume
13
Pages
68-68
ISSN
1662-5196 (ISSN-L)
OpenAlex
W2982679883
Cited by
13
References
41
Citations by year
2025: 1 · 2024: 2 · 2023: 1 · 2022: 4 · 2021: 1 · 2020: 2 · 2019: 2
FWCI
1.09
Type
journal article
Language
en
Open access
Locations
  • Frontiers in Neuroinformatics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Pennsylvania State University
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Biophysics › Cell Image Analysis Techniques
  • Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Neural dynamics and brain function
Keywords
dendritic integration, dendritic trees, bright-field microscopy, neuronal morphology, dendritic computation, open source software

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