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TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus

Auditory cortex volume and shape differences have been observed in the context of phonetic learning, musicianship and dyslexia. Heschl’s gyrus, which includes primary auditory cortex, displays large anatomical variability across individuals and hemispheres. Given this variability, manual labelling i...

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Autores principales: Dalboni da Rocha, Josué Luiz, Schneider, Peter, Benner, Jan, Santoro, Roberta, Atanasova, Tanja, Van De Ville, Dimitri, Golestani, Narly
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054571/
https://www.ncbi.nlm.nih.gov/pubmed/32127593
http://dx.doi.org/10.1038/s41598-020-60609-y
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author Dalboni da Rocha, Josué Luiz
Schneider, Peter
Benner, Jan
Santoro, Roberta
Atanasova, Tanja
Van De Ville, Dimitri
Golestani, Narly
author_facet Dalboni da Rocha, Josué Luiz
Schneider, Peter
Benner, Jan
Santoro, Roberta
Atanasova, Tanja
Van De Ville, Dimitri
Golestani, Narly
author_sort Dalboni da Rocha, Josué Luiz
collection PubMed
description Auditory cortex volume and shape differences have been observed in the context of phonetic learning, musicianship and dyslexia. Heschl’s gyrus, which includes primary auditory cortex, displays large anatomical variability across individuals and hemispheres. Given this variability, manual labelling is the gold standard for segmenting HG, but is time consuming and error prone. Our novel toolbox, called ‘Toolbox for the Automated Segmentation of HG’ or TASH, automatically segments HG in brain structural MRI data, and extracts measures including its volume, surface area and cortical thickness. TASH builds upon FreeSurfer, which provides an initial segmentation of auditory regions, and implements further steps to perform finer auditory cortex delineation. We validate TASH by showing significant relationships between HG volumes obtained using manual labelling and using TASH, in three independent datasets acquired on different scanners and field strengths, and by showing good qualitative segmentation. We also present two applications of TASH, demonstrating replication and extension of previously published findings of relationships between HG volumes and (a) phonetic learning, and (b) musicianship. In sum, TASH effectively segments HG in a fully automated and reproducible manner, opening up a wide range of applications in the domains of expertise, disease, genetics and brain plasticity.
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spelling pubmed-70545712020-03-11 TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus Dalboni da Rocha, Josué Luiz Schneider, Peter Benner, Jan Santoro, Roberta Atanasova, Tanja Van De Ville, Dimitri Golestani, Narly Sci Rep Article Auditory cortex volume and shape differences have been observed in the context of phonetic learning, musicianship and dyslexia. Heschl’s gyrus, which includes primary auditory cortex, displays large anatomical variability across individuals and hemispheres. Given this variability, manual labelling is the gold standard for segmenting HG, but is time consuming and error prone. Our novel toolbox, called ‘Toolbox for the Automated Segmentation of HG’ or TASH, automatically segments HG in brain structural MRI data, and extracts measures including its volume, surface area and cortical thickness. TASH builds upon FreeSurfer, which provides an initial segmentation of auditory regions, and implements further steps to perform finer auditory cortex delineation. We validate TASH by showing significant relationships between HG volumes obtained using manual labelling and using TASH, in three independent datasets acquired on different scanners and field strengths, and by showing good qualitative segmentation. We also present two applications of TASH, demonstrating replication and extension of previously published findings of relationships between HG volumes and (a) phonetic learning, and (b) musicianship. In sum, TASH effectively segments HG in a fully automated and reproducible manner, opening up a wide range of applications in the domains of expertise, disease, genetics and brain plasticity. Nature Publishing Group UK 2020-03-03 /pmc/articles/PMC7054571/ /pubmed/32127593 http://dx.doi.org/10.1038/s41598-020-60609-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/.
spellingShingle Article
Dalboni da Rocha, Josué Luiz
Schneider, Peter
Benner, Jan
Santoro, Roberta
Atanasova, Tanja
Van De Ville, Dimitri
Golestani, Narly
TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title_full TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title_fullStr TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title_full_unstemmed TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title_short TASH: Toolbox for the Automated Segmentation of Heschl’s gyrus
title_sort tash: toolbox for the automated segmentation of heschl’s gyrus
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7054571/
https://www.ncbi.nlm.nih.gov/pubmed/32127593
http://dx.doi.org/10.1038/s41598-020-60609-y
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