Literature DB >> 30553155

Disrupted structural and functional brain networks in Alzheimer's disease.

Zhengjia Dai1, Qixiang Lin2, Tao Li3, Xiao Wang3, Huishu Yuan4, Xin Yu3, Yong He5, Huali Wang6.   

Abstract

Studies have demonstrated that the clinical manifestations of Alzheimer's disease (AD) are associated with abnormal connections in either functional connectivity networks (FCNs) or structural connectivity networks (SCNs). However, the FCN and SCN of AD have usually been examined separately, and the results were inconsistent. In this multimodal study, we collected resting-state functional magnetic resonance imaging and diffusion magnetic resonance imaging data from 46 patients with AD and 39 matched healthy controls (HCs). Graph-theory analysis was used to investigate the topological organization of the FCN and SCN simultaneously. Compared with HCs, both the FCN and SCN of patients with AD showed disrupted network integration (i.e., increased characteristic path length) and segregation (i.e., decreased intramodular connections in the default mode network). Moreover, the FCN, but not the SCN, exhibited a reduced clustering coefficient and reduced rich club connections in AD. The coupling (i.e., correlation) of the FCN and SCN in AD was increased in connections of the default mode network and the rich club. These findings demonstrated overlapping and distinct network disruptions in the FCN and SCN and a strengthened correlation between FCNs and SCNs in AD, which provides a novel perspective for understanding the pathophysiological mechanisms underlying AD.
Copyright © 2018 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Connectome; Functional connectivity; Graph theory; Small-world; Structural connectivity

Mesh:

Year:  2018        PMID: 30553155     DOI: 10.1016/j.neurobiolaging.2018.11.005

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  32 in total

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4.  Integrated and segregated frequency architecture of the human brain network.

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5.  Predicting MCI to AD Conversation Using Integrated sMRI and rs-fMRI: Machine Learning and Graph Theory Approach.

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Journal:  Neurobiol Aging       Date:  2019-12-14       Impact factor: 4.673

7.  [Changes of brain structural network properties in patients with rapid eye movement sleep behavior disorder].

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8.  Disrupted Brain Network Topology in Drug-naïve Essential Tremor Patients with and Without Depression : A Resting State Functional Magnetic Resonance Imaging Study.

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Journal:  Clin Neuroradiol       Date:  2021-03-09       Impact factor: 3.649

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Journal:  Front Aging Neurosci       Date:  2021-06-10       Impact factor: 5.750

10.  A Graph Theory Approach to Clarifying Aging and Disease Related Changes in Cognitive Networks.

Authors:  Laura M Wright; Matteo De Marco; Annalena Venneri
Journal:  Front Aging Neurosci       Date:  2021-07-12       Impact factor: 5.750

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