ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
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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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Morphologies were reconstructed using the semi-automated procedure provided by ShuTu, followed by manual curation.
“The morphologies were reconstructed using the semi-automated procedure provided by ShuTu (Jin et al., 2019), followed by manual curation.”
From Xenotransplanted human cortical neurons reveal species-specific development and functional integration into mouse visual circuits (2019) · cites this paper as Jin et al., 2019
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- 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
- Publisher
- Frontiers Media SA
- Published
- 2019-10-31
- Volume
- 13
- Pages
- 68-68
- ISSN
- 1662-5196 (ISSN-L)
- PMC
- PMC6834530
- 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
- gold
- doi.org
- Licence
- 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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