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Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain
Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy a...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group US
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636024/ https://www.ncbi.nlm.nih.gov/pubmed/36280717 http://dx.doi.org/10.1038/s41592-022-01621-0 |
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author | Svara, Fabian Förster, Dominique Kubo, Fumi Januszewski, Michał dal Maschio, Marco Schubert, Philipp J. Kornfeld, Jörgen Wanner, Adrian A. Laurell, Eva Denk, Winfried Baier, Herwig |
author_facet | Svara, Fabian Förster, Dominique Kubo, Fumi Januszewski, Michał dal Maschio, Marco Schubert, Philipp J. Kornfeld, Jörgen Wanner, Adrian A. Laurell, Eva Denk, Winfried Baier, Herwig |
author_sort | Svara, Fabian |
collection | PubMed |
description | Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14 × 14 × 25 nm(3). We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system. |
format | Online Article Text |
id | pubmed-9636024 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Nature Publishing Group US |
record_format | MEDLINE/PubMed |
spelling | pubmed-96360242022-11-06 Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain Svara, Fabian Förster, Dominique Kubo, Fumi Januszewski, Michał dal Maschio, Marco Schubert, Philipp J. Kornfeld, Jörgen Wanner, Adrian A. Laurell, Eva Denk, Winfried Baier, Herwig Nat Methods Resource Dense reconstruction of synaptic connectivity requires high-resolution electron microscopy images of entire brains and tools to efficiently trace neuronal wires across the volume. To generate such a resource, we sectioned and imaged a larval zebrafish brain by serial block-face electron microscopy at a voxel size of 14 × 14 × 25 nm(3). We segmented the resulting dataset with the flood-filling network algorithm, automated the detection of chemical synapses and validated the results by comparisons to transmission electron microscopic images and light-microscopic reconstructions. Neurons and their connections are stored in the form of a queryable and expandable digital address book. We reconstructed a network of 208 neurons involved in visual motion processing, most of them located in the pretectum, which had been functionally characterized in the same specimen by two-photon calcium imaging. Moreover, we mapped all 407 presynaptic and postsynaptic partners of two superficial interneurons in the tectum. The resource developed here serves as a foundation for synaptic-resolution circuit analyses in the zebrafish nervous system. Nature Publishing Group US 2022-10-24 2022 /pmc/articles/PMC9636024/ /pubmed/36280717 http://dx.doi.org/10.1038/s41592-022-01621-0 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Resource Svara, Fabian Förster, Dominique Kubo, Fumi Januszewski, Michał dal Maschio, Marco Schubert, Philipp J. Kornfeld, Jörgen Wanner, Adrian A. Laurell, Eva Denk, Winfried Baier, Herwig Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title | Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title_full | Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title_fullStr | Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title_full_unstemmed | Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title_short | Automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
title_sort | automated synapse-level reconstruction of neural circuits in the larval zebrafish brain |
topic | Resource |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9636024/ https://www.ncbi.nlm.nih.gov/pubmed/36280717 http://dx.doi.org/10.1038/s41592-022-01621-0 |
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