Alzheimer's Disease Progressively Reduces Visual Functional Network Connectivity

被引:19
|
作者
Huang, Jie [1 ]
Beach, Paul [2 ]
Bozoki, Andrea [1 ,3 ,4 ]
Zhu, David C. [1 ,5 ]
机构
[1] Michigan State Univ, Dept Radiol, 846 Serv Rd, E Lansing, MI 48824 USA
[2] Emory Univ, Sch Med, Dept Neurol, Atlanta, GA 30322 USA
[3] Michigan State Univ, Dept Neurol, E Lansing, MI 48824 USA
[4] Univ N Carolina, Dept Neurol, Chapel Hill, NC 27515 USA
[5] Michigan State Univ, Cognit Imaging Res Ctr, E Lansing, MI 48824 USA
关键词
Alzheimer's disease; face-evoked visual-processing network; FAUPA; functional areas of unitary pooled activity; resting-state visual functional connectivity network; NEUROFIBRILLARY TANGLES; AMYLOID-BETA; NEURITIC PLAQUES; CEREBRAL-CORTEX; PATHOLOGY; STATE; TAU; COGNITION;
D O I
10.3233/ADR-210017
中图分类号
Q189 [神经科学];
学科分类号
071006 ;
摘要
Background: Postmortem studies of brains with Alzheimer's disease (AD) not only find amyloid-beta (A beta) and neurofibrillary tangles (NFT) in the visual cortex, but also reveal temporally sequential changes in AD pathology from higher-order association areas to lower-order areas and then primary visual area (V1) with disease progression. Objective: This study investigated the effect of AD severity on visual functional network. Methods: Eight severe AD (SAD) patients, 11 mild/moderate AD (MAD), and 26 healthy senior (HS) controls undertook a resting-state fMRI (rs-fMRI) and a task fMRI of viewing face photos. A resting-state visual functional connectivity (FC) network and a face-evoked visual-processing network were identified for each group. Results: For the HS, the identified group-mean face-evoked visual-processing network in the ventral pathway started from V1 and ended within the fusiform gyrus. In contrast, the resting-state visual FC network was mainly confined within the visual cortex. AD disrupted these two functional networks in a similar severity dependent manner: the more severe the cognitive impairment, the greater reduction in network connectivity. For the face-evoked visual-processing network, MAD disrupted and reduced activation mainly in the higher-order visual association areas, with SAD further disrupting and reducing activation in the lower-order areas. Conclusion: These findings provide a functional corollary to the canonical view of the temporally sequential advancement of AD pathology through visual cortical areas. The association of the disruption of functional networks, especially the face-evoked visual-processing network, with AD severity suggests a potential predictor or biomarker of AD progression.
引用
收藏
页码:549 / 562
页数:14
相关论文
共 50 条
  • [21] Disturbed Default Mode Network Connectivity Patterns in Alzheimer's Disease Associated with Visual Processing
    Krajcovicova, Lenka
    Mikl, Michal
    Marecek, Radek
    Rektorova, Irena
    JOURNAL OF ALZHEIMERS DISEASE, 2014, 41 (04) : 1229 - 1238
  • [22] Altered within- and between-network functional connectivity in atypical Alzheimer's disease
    Singh, Neha Atulkumar
    Martin, Peter R.
    Graff-Radford, Jonathan
    Sintini, Irene
    Machulda, Mary M.
    Duffy, Joseph R.
    Gunter, Jeffrey L.
    Botha, Hugo
    Jones, David T.
    Lowe, Val J.
    JackJr, Clifford R.
    Josephs, Keith A.
    Whitwell, Jennifer L.
    BRAIN COMMUNICATIONS, 2023, 5 (04)
  • [23] Classification of Schizophrenia and Alzheimer's Disease using Resting-State Functional Network Connectivity
    Hassanzadeh, Reihaneh
    Abrol, Anees
    Calhoun, Vince
    2022 IEEE-EMBS INTERNATIONAL CONFERENCE ON BIOMEDICAL AND HEALTH INFORMATICS (BHI) JOINTLY ORGANISED WITH THE IEEE-EMBS INTERNATIONAL CONFERENCE ON WEARABLE AND IMPLANTABLE BODY SENSOR NETWORKS (BSN'22), 2022,
  • [24] Functional Connectivity between the Resting-State Olfactory Network and the Hippocampus in Alzheimer's Disease
    Lu, Jiaming
    Testa, Nicole
    Jordan, Rebecca
    Elyan, Rommy
    Kanekar, Sangam
    Wang, Jianli
    Eslinger, Paul
    Yang, Qing X.
    Zhang, Bing
    Karunanayaka, Prasanna R.
    BRAIN SCIENCES, 2019, 9 (12)
  • [25] Structure Feature Learning: Constructing Functional Connectivity Network for Alzheimer's Disease Identification and Analysis
    Zhao, Qinghua
    Ali, Zakir
    Lu, Jianfeng
    Metmer, Hichem
    BIOMETRIC RECOGNITION (CCBR 2019), 2019, 11818 : 107 - 115
  • [26] Impaired default network functional connectivity in autosomal dominant Alzheimer disease
    Chhatwal, Jasmeer P.
    Schultz, Aaron P.
    Johnson, Keith
    Benzinger, Tammie L. S.
    Jack, Clifford, Jr.
    Ances, Beau M.
    Sullivan, Caroline A.
    Salloway, Stephen P.
    Ringman, John M.
    Koeppe, Robert A.
    Marcus, Daniel S.
    Thompson, Paul
    Saykin, Andrew J.
    Correia, Stephen
    Schofield, Peter R.
    Rowe, Christopher C.
    Fox, Nick C.
    Brickman, Adam M.
    Mayeux, Richard
    McDade, Eric
    Bateman, Randall
    Fagan, Anne M.
    Goate, Allison M.
    Xiong, Chengjie
    Buckles, Virginia D.
    Morris, John C.
    Sperling, Reisa A.
    NEUROLOGY, 2013, 81 (08) : 736 - 744
  • [27] Sleep functional connectivity, hyperexcitability, and cognition in Alzheimer's disease
    Moguilner, Sebastian G.
    Berezuk, Courtney
    Bender, Alex C.
    Pellerin, Kyle R.
    Gomperts, Stephen N.
    Cash, Sydney S.
    Sarkis, Rani A.
    Lam, Alice D.
    ALZHEIMERS & DEMENTIA, 2024, 20 (06) : 4234 - 4249
  • [28] Altered Functional Connectivity of Insular Subregions in Alzheimer's Disease
    Liu, Xingyun
    Chen, Xiaodan
    Zheng, Weimin
    Xia, Mingrui
    Han, Ying
    Song, Haiqing
    Li, Kuncheng
    He, Yong
    Wang, Zhiqun
    FRONTIERS IN AGING NEUROSCIENCE, 2018, 10
  • [29] Functional connectivity tracks clinical deterioration in Alzheimer's disease
    Damoiseaux, Jessica S.
    Prater, Katherine E.
    Miller, Bruce L.
    Greicius, Michael D.
    NEUROBIOLOGY OF AGING, 2012, 33 (04)
  • [30] Dynamic functional connectivity MEG features of Alzheimer's disease
    Jin, Huaqing
    Ranasinghe, Kamalini G.
    Prabhu, Pooja
    Dale, Corby
    Gao, Yijing
    Kudo, Kiwamu
    Vossel, Keith
    Raj, Ashish
    Nagarajan, Srikantan S.
    Jiang, Fei
    NEUROIMAGE, 2023, 281