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Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century
Obtaining precise and detailed parcellations of the human brain has been a major focus of neuroscience research. Here, we present a multimodal dataset, MYATLAS, based on histology-derived myeloarchitectonic parcellations for use with contemporary neuroimaging analyses software. The core of MYATLAS i...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015172/ https://www.ncbi.nlm.nih.gov/pubmed/36936633 http://dx.doi.org/10.1016/j.dib.2023.108999 |
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author | Foit, Niels Alexander Yung, Seles Lee, Hyo Min Bernasconi, Andrea Bernasconi, Neda Hong, Seok-Jun |
author_facet | Foit, Niels Alexander Yung, Seles Lee, Hyo Min Bernasconi, Andrea Bernasconi, Neda Hong, Seok-Jun |
author_sort | Foit, Niels Alexander |
collection | PubMed |
description | Obtaining precise and detailed parcellations of the human brain has been a major focus of neuroscience research. Here, we present a multimodal dataset, MYATLAS, based on histology-derived myeloarchitectonic parcellations for use with contemporary neuroimaging analyses software. The core of MYATLAS is a novel 3D neocortical, surface-based atlas derived from legacy myeloarchitectonic histology studies. Additionally, we provide digitized quantitative laminar profiles of intracortical myelin content derived from postmortem photometric data, cross-correlated with in vivo myeloarchitectonic features obtained by quantitative MRI mapping. Moreover, congregated, digitized and quality-improved Vogt-Vogt legacy histology data is made available. Finally, to allow for cross-modality correlations, maps of quantitative myelin estimates and corresponding von Economo-Koskinas’ cytoarchitectonic features are also included. We share all necessary surface and volume-based registration files as well as shell scripts to facilitate applications of MYATLAS to future in vivo MRI studies. |
format | Online Article Text |
id | pubmed-10015172 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-100151722023-03-16 Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century Foit, Niels Alexander Yung, Seles Lee, Hyo Min Bernasconi, Andrea Bernasconi, Neda Hong, Seok-Jun Data Brief Data Article Obtaining precise and detailed parcellations of the human brain has been a major focus of neuroscience research. Here, we present a multimodal dataset, MYATLAS, based on histology-derived myeloarchitectonic parcellations for use with contemporary neuroimaging analyses software. The core of MYATLAS is a novel 3D neocortical, surface-based atlas derived from legacy myeloarchitectonic histology studies. Additionally, we provide digitized quantitative laminar profiles of intracortical myelin content derived from postmortem photometric data, cross-correlated with in vivo myeloarchitectonic features obtained by quantitative MRI mapping. Moreover, congregated, digitized and quality-improved Vogt-Vogt legacy histology data is made available. Finally, to allow for cross-modality correlations, maps of quantitative myelin estimates and corresponding von Economo-Koskinas’ cytoarchitectonic features are also included. We share all necessary surface and volume-based registration files as well as shell scripts to facilitate applications of MYATLAS to future in vivo MRI studies. Elsevier 2023-02-20 /pmc/articles/PMC10015172/ /pubmed/36936633 http://dx.doi.org/10.1016/j.dib.2023.108999 Text en © 2023 The Authors. Published by Elsevier Inc. https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Data Article Foit, Niels Alexander Yung, Seles Lee, Hyo Min Bernasconi, Andrea Bernasconi, Neda Hong, Seok-Jun Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title | Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title_full | Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title_fullStr | Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title_full_unstemmed | Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title_short | Myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the Vogt-Vogt legacy in the 21st century |
title_sort | myeloarchitectonic cortical parcellation data for contemporary neuroimaging – the vogt-vogt legacy in the 21st century |
topic | Data Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10015172/ https://www.ncbi.nlm.nih.gov/pubmed/36936633 http://dx.doi.org/10.1016/j.dib.2023.108999 |
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