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Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities”
We thank the editors for organizing the discussions and the discussants for insightful comments. Our rejoinder provides results and comments to address the questions raised in the discussions. Specifically, we present results showing DICA largely demonstrates better or comparable stability as compar...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
John Wiley and Sons Inc.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107522/ https://www.ncbi.nlm.nih.gov/pubmed/34780668 http://dx.doi.org/10.1111/biom.13588 |
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author | Wu, Ben Pal, Subhadip Kang, Jian Guo, Ying |
author_facet | Wu, Ben Pal, Subhadip Kang, Jian Guo, Ying |
author_sort | Wu, Ben |
collection | PubMed |
description | We thank the editors for organizing the discussions and the discussants for insightful comments. Our rejoinder provides results and comments to address the questions raised in the discussions. Specifically, we present results showing DICA largely demonstrates better or comparable stability as compared with standard ICA. We also validate the DICA in real fMRI application by showing DICA generally shows higher reliability in reproducibly recovering major brain functional networks as compared with the standard ICA. We provide details on the computational complexity of the method. The computational cost of DICA is very reasonable with the analysis of the fMRI and DTI data easily implementable on a PC or laptop. Finally, we include discussions on several directions for extending the DICA framework in the future. |
format | Online Article Text |
id | pubmed-9107522 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | John Wiley and Sons Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-91075222022-12-28 Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” Wu, Ben Pal, Subhadip Kang, Jian Guo, Ying Biometrics Biometric Methodology We thank the editors for organizing the discussions and the discussants for insightful comments. Our rejoinder provides results and comments to address the questions raised in the discussions. Specifically, we present results showing DICA largely demonstrates better or comparable stability as compared with standard ICA. We also validate the DICA in real fMRI application by showing DICA generally shows higher reliability in reproducibly recovering major brain functional networks as compared with the standard ICA. We provide details on the computational complexity of the method. The computational cost of DICA is very reasonable with the analysis of the fMRI and DTI data easily implementable on a PC or laptop. Finally, we include discussions on several directions for extending the DICA framework in the future. John Wiley and Sons Inc. 2021-11-15 2022-09 /pmc/articles/PMC9107522/ /pubmed/34780668 http://dx.doi.org/10.1111/biom.13588 Text en © 2021 The Authors. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made. |
spellingShingle | Biometric Methodology Wu, Ben Pal, Subhadip Kang, Jian Guo, Ying Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title | Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title_full | Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title_fullStr | Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title_full_unstemmed | Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title_short | Rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
title_sort | rejoinder to discussions of “distributional independent component analysis for diverse neuroimaging modalities” |
topic | Biometric Methodology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9107522/ https://www.ncbi.nlm.nih.gov/pubmed/34780668 http://dx.doi.org/10.1111/biom.13588 |
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