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Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study
AD is a common chronic progressive neurodegenerative disorder. However, the understanding of the dynamic longitudinal change of the brain in the progression of AD is still rough and sometimes conflicting. This paper analyzed the brain networks of healthy people and patients at different stages (EMCI...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Hindawi
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341396/ https://www.ncbi.nlm.nih.gov/pubmed/32684923 http://dx.doi.org/10.1155/2020/7839536 |
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author | Li, Wei Wen, Wen Chen, Xi Ni, BingJie Lin, Xuefeng Fan, Wenliang The Alzheimer's Disease Neuroimaging Initiative, |
author_facet | Li, Wei Wen, Wen Chen, Xi Ni, BingJie Lin, Xuefeng Fan, Wenliang The Alzheimer's Disease Neuroimaging Initiative, |
author_sort | Li, Wei |
collection | PubMed |
description | AD is a common chronic progressive neurodegenerative disorder. However, the understanding of the dynamic longitudinal change of the brain in the progression of AD is still rough and sometimes conflicting. This paper analyzed the brain networks of healthy people and patients at different stages (EMCI, LMCI, and AD). The results showed that in global network properties, most differences only existed between healthy people and patients, and few were discovered between patients at different stages. However, nearly all subnetwork properties showed significant differences between patients at different stages. Moreover, the most interesting result was that we found two different functional evolving patterns of cortical networks in progression of AD, named ‘temperature inversion' and “monotonous decline,” but not the same monotonous decline trend as the external functional assessment observed in the course of disease progression. We suppose that those subnetworks, showing the same functional evolving pattern in AD progression, may have something the same in work mechanism in nature. And the subnetworks with ‘temperature inversion' evolving pattern may play a special role in the development of AD. |
format | Online Article Text |
id | pubmed-7341396 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Hindawi |
record_format | MEDLINE/PubMed |
spelling | pubmed-73413962020-07-16 Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study Li, Wei Wen, Wen Chen, Xi Ni, BingJie Lin, Xuefeng Fan, Wenliang The Alzheimer's Disease Neuroimaging Initiative, Neural Plast Research Article AD is a common chronic progressive neurodegenerative disorder. However, the understanding of the dynamic longitudinal change of the brain in the progression of AD is still rough and sometimes conflicting. This paper analyzed the brain networks of healthy people and patients at different stages (EMCI, LMCI, and AD). The results showed that in global network properties, most differences only existed between healthy people and patients, and few were discovered between patients at different stages. However, nearly all subnetwork properties showed significant differences between patients at different stages. Moreover, the most interesting result was that we found two different functional evolving patterns of cortical networks in progression of AD, named ‘temperature inversion' and “monotonous decline,” but not the same monotonous decline trend as the external functional assessment observed in the course of disease progression. We suppose that those subnetworks, showing the same functional evolving pattern in AD progression, may have something the same in work mechanism in nature. And the subnetworks with ‘temperature inversion' evolving pattern may play a special role in the development of AD. Hindawi 2020-06-29 /pmc/articles/PMC7341396/ /pubmed/32684923 http://dx.doi.org/10.1155/2020/7839536 Text en Copyright © 2020 Wei Li et al. http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Research Article Li, Wei Wen, Wen Chen, Xi Ni, BingJie Lin, Xuefeng Fan, Wenliang The Alzheimer's Disease Neuroimaging Initiative, Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title | Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title_full | Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title_fullStr | Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title_full_unstemmed | Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title_short | Functional Evolving Patterns of Cortical Networks in Progression of Alzheimer's Disease: A Graph-Based Resting-State fMRI Study |
title_sort | functional evolving patterns of cortical networks in progression of alzheimer's disease: a graph-based resting-state fmri study |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7341396/ https://www.ncbi.nlm.nih.gov/pubmed/32684923 http://dx.doi.org/10.1155/2020/7839536 |
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