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A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain
TheVirtualBrain, an open-source platform for large-scale network modeling, can be personalized to an individual using a wide range of neuroimaging modalities. With the growing number and scale of neuroimaging data sharing initiatives of both healthy and clinical populations comes an opportunity to c...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239912/ https://www.ncbi.nlm.nih.gov/pubmed/35784190 http://dx.doi.org/10.3389/fninf.2022.883223 |
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author | Frazier-Logue, Noah Wang, Justin Wang, Zheng Sodums, Devin Khosla, Anisha Samson, Alexandria D. McIntosh, Anthony R. Shen, Kelly |
author_facet | Frazier-Logue, Noah Wang, Justin Wang, Zheng Sodums, Devin Khosla, Anisha Samson, Alexandria D. McIntosh, Anthony R. Shen, Kelly |
author_sort | Frazier-Logue, Noah |
collection | PubMed |
description | TheVirtualBrain, an open-source platform for large-scale network modeling, can be personalized to an individual using a wide range of neuroimaging modalities. With the growing number and scale of neuroimaging data sharing initiatives of both healthy and clinical populations comes an opportunity to create large and heterogeneous sets of dynamic network models to better understand individual differences in network dynamics and their impact on brain health. Here we present TheVirtualBrain-UK Biobank pipeline, a robust, automated and open-source brain image processing solution to address the expanding scope of TheVirtualBrain project. Our pipeline generates connectome-based modeling inputs compatible for use with TheVirtualBrain. We leverage the existing multimodal MRI processing pipeline from the UK Biobank made for use with a variety of brain imaging modalities. We add various features and changes to the original UK Biobank implementation specifically for informing large-scale network models, including user-defined parcellations for the construction of matching whole-brain functional and structural connectomes. Changes also include detailed reports for quality control of all modalities, a streamlined installation process, modular software packaging, updated software versions, and support for various publicly available datasets. The pipeline has been tested on various datasets from both healthy and clinical populations and is robust to the morphological changes observed in aging and dementia. In this paper, we describe these and other pipeline additions and modifications in detail, as well as how this pipeline fits into the TheVirtualBrain ecosystem. |
format | Online Article Text |
id | pubmed-9239912 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-92399122022-06-30 A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain Frazier-Logue, Noah Wang, Justin Wang, Zheng Sodums, Devin Khosla, Anisha Samson, Alexandria D. McIntosh, Anthony R. Shen, Kelly Front Neuroinform Neuroscience TheVirtualBrain, an open-source platform for large-scale network modeling, can be personalized to an individual using a wide range of neuroimaging modalities. With the growing number and scale of neuroimaging data sharing initiatives of both healthy and clinical populations comes an opportunity to create large and heterogeneous sets of dynamic network models to better understand individual differences in network dynamics and their impact on brain health. Here we present TheVirtualBrain-UK Biobank pipeline, a robust, automated and open-source brain image processing solution to address the expanding scope of TheVirtualBrain project. Our pipeline generates connectome-based modeling inputs compatible for use with TheVirtualBrain. We leverage the existing multimodal MRI processing pipeline from the UK Biobank made for use with a variety of brain imaging modalities. We add various features and changes to the original UK Biobank implementation specifically for informing large-scale network models, including user-defined parcellations for the construction of matching whole-brain functional and structural connectomes. Changes also include detailed reports for quality control of all modalities, a streamlined installation process, modular software packaging, updated software versions, and support for various publicly available datasets. The pipeline has been tested on various datasets from both healthy and clinical populations and is robust to the morphological changes observed in aging and dementia. In this paper, we describe these and other pipeline additions and modifications in detail, as well as how this pipeline fits into the TheVirtualBrain ecosystem. Frontiers Media S.A. 2022-06-14 /pmc/articles/PMC9239912/ /pubmed/35784190 http://dx.doi.org/10.3389/fninf.2022.883223 Text en Copyright © 2022 Frazier-Logue, Wang, Wang, Sodums, Khosla, Samson, McIntosh and Shen. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neuroscience Frazier-Logue, Noah Wang, Justin Wang, Zheng Sodums, Devin Khosla, Anisha Samson, Alexandria D. McIntosh, Anthony R. Shen, Kelly A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title | A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title_full | A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title_fullStr | A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title_full_unstemmed | A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title_short | A Robust Modular Automated Neuroimaging Pipeline for Model Inputs to TheVirtualBrain |
title_sort | robust modular automated neuroimaging pipeline for model inputs to thevirtualbrain |
topic | Neuroscience |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9239912/ https://www.ncbi.nlm.nih.gov/pubmed/35784190 http://dx.doi.org/10.3389/fninf.2022.883223 |
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