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Transcranial brain atlas
We introduce here the concept of a transcranial brain atlas (TBA), a new kind of brain atlas specialized for transcranial techniques. A TBA is a probabilistic mapping from scalp space to atlas label space, relating scalp locations to anatomical, functional, network, genetic, or other labels. TBAs of...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6124906/ https://www.ncbi.nlm.nih.gov/pubmed/30191174 http://dx.doi.org/10.1126/sciadv.aar6904 |
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author | Xiao, Xiang Yu, Xiaoting Zhang, Zong Zhao, Yang Jiang, Yihan Li, Zheng Yang, Yihong Zhu, Chaozhe |
author_facet | Xiao, Xiang Yu, Xiaoting Zhang, Zong Zhao, Yang Jiang, Yihan Li, Zheng Yang, Yihong Zhu, Chaozhe |
author_sort | Xiao, Xiang |
collection | PubMed |
description | We introduce here the concept of a transcranial brain atlas (TBA), a new kind of brain atlas specialized for transcranial techniques. A TBA is a probabilistic mapping from scalp space to atlas label space, relating scalp locations to anatomical, functional, network, genetic, or other labels. TBAs offer a new way to integrate and present structural and functional organization of the brain and allow previously subsurface and invisible atlas labels visible on the scalp surface to accurately guide the placement of transcranial devices directly on the scalp surface in a straightforward, visual manner. We present here a framework for building TBAs that includes (i) a new, continuous proportional coordinate system devised for the scalp surface to allow standardized specification of scalp positions; (ii) a high-resolution, large sample–based (114-participant) mapping from scalp space to brain space to accurately and reliably describe human cranio-cortical correspondence; and (iii) a two-step Markov chain to combine the probabilistic scalp-brain mapping with a traditional brain atlas, bringing atlas labels to the scalp surface. We assessed the reproducibility (consistency of TBAs generated from different groups) and predictiveness (prediction accuracy of labels for individuals without brain images) of the TBAs built via our framework. Moreover, we present an application of TBAs to a functional near-infrared spectroscopy finger-tapping experiment, illustrating the utility and benefits of TBAs in transcranial studies. Our results demonstrate that TBAs can support ongoing efforts to map the human brain using transcranial techniques, just as traditional brain atlases have supported magnetic resonance imaging and positron emission tomography studies. |
format | Online Article Text |
id | pubmed-6124906 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-61249062018-09-06 Transcranial brain atlas Xiao, Xiang Yu, Xiaoting Zhang, Zong Zhao, Yang Jiang, Yihan Li, Zheng Yang, Yihong Zhu, Chaozhe Sci Adv Research Articles We introduce here the concept of a transcranial brain atlas (TBA), a new kind of brain atlas specialized for transcranial techniques. A TBA is a probabilistic mapping from scalp space to atlas label space, relating scalp locations to anatomical, functional, network, genetic, or other labels. TBAs offer a new way to integrate and present structural and functional organization of the brain and allow previously subsurface and invisible atlas labels visible on the scalp surface to accurately guide the placement of transcranial devices directly on the scalp surface in a straightforward, visual manner. We present here a framework for building TBAs that includes (i) a new, continuous proportional coordinate system devised for the scalp surface to allow standardized specification of scalp positions; (ii) a high-resolution, large sample–based (114-participant) mapping from scalp space to brain space to accurately and reliably describe human cranio-cortical correspondence; and (iii) a two-step Markov chain to combine the probabilistic scalp-brain mapping with a traditional brain atlas, bringing atlas labels to the scalp surface. We assessed the reproducibility (consistency of TBAs generated from different groups) and predictiveness (prediction accuracy of labels for individuals without brain images) of the TBAs built via our framework. Moreover, we present an application of TBAs to a functional near-infrared spectroscopy finger-tapping experiment, illustrating the utility and benefits of TBAs in transcranial studies. Our results demonstrate that TBAs can support ongoing efforts to map the human brain using transcranial techniques, just as traditional brain atlases have supported magnetic resonance imaging and positron emission tomography studies. American Association for the Advancement of Science 2018-09-05 /pmc/articles/PMC6124906/ /pubmed/30191174 http://dx.doi.org/10.1126/sciadv.aar6904 Text en Copyright © 2018 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). http://creativecommons.org/licenses/by-nc/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (http://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Xiao, Xiang Yu, Xiaoting Zhang, Zong Zhao, Yang Jiang, Yihan Li, Zheng Yang, Yihong Zhu, Chaozhe Transcranial brain atlas |
title | Transcranial brain atlas |
title_full | Transcranial brain atlas |
title_fullStr | Transcranial brain atlas |
title_full_unstemmed | Transcranial brain atlas |
title_short | Transcranial brain atlas |
title_sort | transcranial brain atlas |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6124906/ https://www.ncbi.nlm.nih.gov/pubmed/30191174 http://dx.doi.org/10.1126/sciadv.aar6904 |
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