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  Functional disorganization of small-world brain networks in mild Alzheimer's disease and amnestic mild cognitive impairment: An EEG study using relative wavelet entropy (RWE)

Frantzidis, C. A., Vivas, A. B., Tsolaki, A., Klados, M., Tsolaki, M., & Bamidis, P. D. (2014). Functional disorganization of small-world brain networks in mild Alzheimer's disease and amnestic mild cognitive impairment: An EEG study using relative wavelet entropy (RWE). Frontiers in Aging Neuroscience, 6: 224. doi:10.3389/fnagi.2014.00224.

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 Creators:
Frantzidis, Christos A.1, Author
Vivas, Ana B.2, Author
Tsolaki, Anthoula1, 3, Author
Klados, Manousos1, Author           
Tsolaki, Magda4, Author
Bamidis, Panagiotis D.1, Author
Affiliations:
1Laboratory of Medical Physics, School of Medicine, Faculty of Health Sciences, Aristotle University of Thessaloniki, Greece, ou_persistent22              
2Psychology Department, The University of Sheffield International Faculty, Thessaloniki, Greece, ou_persistent22              
3Greek Association of Alzheimer's Disease and Related Disorders, Thessaloniki, Greece, ou_persistent22              
4Department of Neurology, Aristotle University of Thessaloniki, Greece, ou_persistent22              

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Free keywords: Alzheimer disease; Amnestic mild cognitive impairment; Electroencephalography; Graph analysis; Relative wavelet entropy
 Abstract: Previous neuroscientific findings have linked Alzheimer's Disease (AD) with less efficient information processing and brain network disorganization. However, pathological alterations of the brain networks during the preclinical phase of amnestic Mild Cognitive Impairment (aMCI) remain largely unknown. The present study aimed at comparing patterns of the detection of functional disorganization in MCI relative to Mild Dementia (MD). Participants consisted of 23 cognitively healthy adults, 17 aMCI and 24 mild AD patients who underwent electroencephalographic (EEG) data acquisition during a resting-state condition. Synchronization analysis through the Orthogonal Discrete Wavelet Transform (ODWT), and directional brain network analysis were applied on the EEG data. This computational model was performed for networks that have the same number of edges (N = 500, 600, 700, 800 edges) across all participants and groups (fixed density values). All groups exhibited a small-world (SW) brain architecture. However, we found a significant reduction in the SW brain architecture in both aMCI and MD patients relative to the group of Healthy controls. This functional disorganization was also correlated with the participant's generic cognitive status. The deterioration of the network's organization was caused mainly by deficient local information processing as quantified by the mean cluster coefficient value. Functional hubs were identified through the normalized betweenness centrality metric. Analysis of the local characteristics showed relative hub preservation even with statistically significant reduced strength. Compensatory phenomena were also evident through the formation of additional hubs on left frontal and parietal regions. Our results indicate a declined functional network organization even during the prodromal phase. Degeneration is evident even in the preclinical phase and coexists with transient network reorganization due to compensation.

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Language(s): eng - English
 Dates: 2014-04-162014-08-042014-08-26
 Publication Status: Published online
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3389/fnagi.2014.00224
PMID: 25206333
PMC: PMC4144118
Other: eCollection 2014
 Degree: -

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Title: Frontiers in Aging Neuroscience
  Abbreviation : Front Aging Neurosci
Source Genre: Journal
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Publ. Info: Lausanne : Frontiers Research Foundation
Pages: - Volume / Issue: 6 Sequence Number: 224 Start / End Page: - Identifier: ISSN: 1663-4365
CoNE: https://pure.mpg.de/cone/journals/resource/1663-4365