Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10400.14/40183 |
Resumo: | Background: Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer’s disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques. Methods: In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer’s disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer’s disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson’s correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed. Results: Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition. Conclusion: The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings. |
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Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI studyAlzheimer’s diseaseDynamic functional connectivityFunctional connectivityMild cognitive impairmentPoint process analysisResting state fMRIBackground: Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer’s disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques. Methods: In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer’s disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer’s disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson’s correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed. Results: Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition. Conclusion: The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.Veritati - Repositório Institucional da Universidade Católica PortuguesaPenalba-Sánchez, LucíaOliveira-Silva, PatríciaSumich, Alexander LukeCifre, Ignacio2023-02-08T16:17:09Z2023-01-092023-01-09T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.14/40183eng1663-436510.3389/fnagi.2022.103734785146837038PMC986906836698861000916833500001info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-07-12T17:45:43Zoai:repositorio.ucp.pt:10400.14/40183Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T18:32:55.255806Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
title |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
spellingShingle |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study Penalba-Sánchez, Lucía Alzheimer’s disease Dynamic functional connectivity Functional connectivity Mild cognitive impairment Point process analysis Resting state fMRI |
title_short |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
title_full |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
title_fullStr |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
title_full_unstemmed |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
title_sort |
Increased functional connectivity patterns in mild Alzheimer’s disease: a rsfMRI study |
author |
Penalba-Sánchez, Lucía |
author_facet |
Penalba-Sánchez, Lucía Oliveira-Silva, Patrícia Sumich, Alexander Luke Cifre, Ignacio |
author_role |
author |
author2 |
Oliveira-Silva, Patrícia Sumich, Alexander Luke Cifre, Ignacio |
author2_role |
author author author |
dc.contributor.none.fl_str_mv |
Veritati - Repositório Institucional da Universidade Católica Portuguesa |
dc.contributor.author.fl_str_mv |
Penalba-Sánchez, Lucía Oliveira-Silva, Patrícia Sumich, Alexander Luke Cifre, Ignacio |
dc.subject.por.fl_str_mv |
Alzheimer’s disease Dynamic functional connectivity Functional connectivity Mild cognitive impairment Point process analysis Resting state fMRI |
topic |
Alzheimer’s disease Dynamic functional connectivity Functional connectivity Mild cognitive impairment Point process analysis Resting state fMRI |
description |
Background: Alzheimer’s disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer’s disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques. Methods: In the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer’s disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer’s disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson’s correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed. Results: Our results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition. Conclusion: The increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-02-08T16:17:09Z 2023-01-09 2023-01-09T00:00:00Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.14/40183 |
url |
http://hdl.handle.net/10400.14/40183 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
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1663-4365 10.3389/fnagi.2022.1037347 85146837038 PMC9869068 36698861 000916833500001 |
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info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
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application/pdf |
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reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799132055093641216 |