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

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 studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance t...

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Autores principales: Jin, Dezhe Z., Zhao, Ting, Hunt, David L., Tillage, Rachel P., Hsu, Ching-Lung, Spruston, Nelson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834530/
https://www.ncbi.nlm.nih.gov/pubmed/31736735
http://dx.doi.org/10.3389/fninf.2019.00068
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author Jin, Dezhe Z.
Zhao, Ting
Hunt, David L.
Tillage, Rachel P.
Hsu, Ching-Lung
Spruston, Nelson
author_facet Jin, Dezhe Z.
Zhao, Ting
Hunt, David L.
Tillage, Rachel P.
Hsu, Ching-Lung
Spruston, Nelson
author_sort Jin, Dezhe Z.
collection PubMed
description 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 studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures 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 processes, 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.
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spelling pubmed-68345302019-11-15 ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology Jin, Dezhe Z. Zhao, Ting Hunt, David L. Tillage, Rachel P. Hsu, Ching-Lung Spruston, Nelson Front Neuroinform Neuroscience 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 studying this process is to record from neurons using patch-clamp electrodes, fill the recorded neurons with a substance that allows subsequent staining, reconstruct the three-dimensional architectures 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 processes, 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. Frontiers Media S.A. 2019-10-31 /pmc/articles/PMC6834530/ /pubmed/31736735 http://dx.doi.org/10.3389/fninf.2019.00068 Text en Copyright © 2019 Jin, Zhao, Hunt, Tillage, Hsu and Spruston. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Jin, Dezhe Z.
Zhao, Ting
Hunt, David L.
Tillage, Rachel P.
Hsu, Ching-Lung
Spruston, Nelson
ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title_full ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title_fullStr ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title_full_unstemmed ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title_short ShuTu: Open-Source Software for Efficient and Accurate Reconstruction of Dendritic Morphology
title_sort shutu: open-source software for efficient and accurate reconstruction of dendritic morphology
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6834530/
https://www.ncbi.nlm.nih.gov/pubmed/31736735
http://dx.doi.org/10.3389/fninf.2019.00068
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