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A three-dimensional thalamocortical dataset for characterizing brain heterogeneity
Neural microarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to...
Autores principales: | , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576781/ https://www.ncbi.nlm.nih.gov/pubmed/33082340 http://dx.doi.org/10.1038/s41597-020-00692-y |
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author | Prasad, Judy A. Balwani, Aishwarya H. Johnson, Erik C. Miano, Joseph D. Sampathkumar, Vandana De Andrade, Vincent Fezzaa, Kamel Du, Ming Vescovi, Rafael Jacobsen, Chris Kording, Konrad P. Gürsoy, Doga Gray Roncal, William Kasthuri, Narayanan Dyer, Eva L. |
author_facet | Prasad, Judy A. Balwani, Aishwarya H. Johnson, Erik C. Miano, Joseph D. Sampathkumar, Vandana De Andrade, Vincent Fezzaa, Kamel Du, Ming Vescovi, Rafael Jacobsen, Chris Kording, Konrad P. Gürsoy, Doga Gray Roncal, William Kasthuri, Narayanan Dyer, Eva L. |
author_sort | Prasad, Judy A. |
collection | PubMed |
description | Neural microarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to continuous, three-dimensional volumes that span multiple brain areas not only provides richer context for identifying such landmarks, but also enables a deeper probing of the microstructures within. Here, we describe a three-dimensional X-ray microtomography imaging dataset of a well-known and validated thalamocortical sample, encompassing a range of cortical and subcortical structures from the mouse brain . In doing so, we provide the field with access to a micron-scale anatomical imaging dataset ideal for studying heterogeneity of neural structure. |
format | Online Article Text |
id | pubmed-7576781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-75767812020-10-23 A three-dimensional thalamocortical dataset for characterizing brain heterogeneity Prasad, Judy A. Balwani, Aishwarya H. Johnson, Erik C. Miano, Joseph D. Sampathkumar, Vandana De Andrade, Vincent Fezzaa, Kamel Du, Ming Vescovi, Rafael Jacobsen, Chris Kording, Konrad P. Gürsoy, Doga Gray Roncal, William Kasthuri, Narayanan Dyer, Eva L. Sci Data Data Descriptor Neural microarchitecture is heterogeneous, varying both across and within brain regions. The consistent identification of regions of interest is one of the most critical aspects in examining neurocircuitry, as these structures serve as the vital landmarks with which to map brain pathways. Access to continuous, three-dimensional volumes that span multiple brain areas not only provides richer context for identifying such landmarks, but also enables a deeper probing of the microstructures within. Here, we describe a three-dimensional X-ray microtomography imaging dataset of a well-known and validated thalamocortical sample, encompassing a range of cortical and subcortical structures from the mouse brain . In doing so, we provide the field with access to a micron-scale anatomical imaging dataset ideal for studying heterogeneity of neural structure. Nature Publishing Group UK 2020-10-20 /pmc/articles/PMC7576781/ /pubmed/33082340 http://dx.doi.org/10.1038/s41597-020-00692-y Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article. |
spellingShingle | Data Descriptor Prasad, Judy A. Balwani, Aishwarya H. Johnson, Erik C. Miano, Joseph D. Sampathkumar, Vandana De Andrade, Vincent Fezzaa, Kamel Du, Ming Vescovi, Rafael Jacobsen, Chris Kording, Konrad P. Gürsoy, Doga Gray Roncal, William Kasthuri, Narayanan Dyer, Eva L. A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title | A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title_full | A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title_fullStr | A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title_full_unstemmed | A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title_short | A three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
title_sort | three-dimensional thalamocortical dataset for characterizing brain heterogeneity |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7576781/ https://www.ncbi.nlm.nih.gov/pubmed/33082340 http://dx.doi.org/10.1038/s41597-020-00692-y |
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