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Lookup NU author(s): Ramtin Mehraram, Professor Marcus Kaiser, Dr Ruth Cromarty, Dr Sara Graziadio, Professor John O'Brien, Dr Alison Killen, Professor John-Paul TaylorORCiD, Dr Luis Peraza RodriguezORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc.The diagnosis of dementia with Lewy bodies (DLB) versus Alzheimer's disease (AD) can be difficult especially early in the disease process. However, one inexpensive and non-invasive biomarker which could help is electroencephalography (EEG). Previous studies have shown that the brain network architecture assessed by EEG is altered in AD patients compared with age-matched healthy control people (HC). However, similar studies in Lewy body diseases, that is, DLB and Parkinson's disease dementia (PDD) are still lacking. In this work, we (a) compared brain network connectivity patterns across conditions, AD, DLB and PDD, in order to infer EEG network biomarkers that differentiate between these conditions, and (b) tested whether opting for weighted matrices led to more reliable results by better preserving the topology of the network. Our results indicate that dementia groups present with reduced connectivity in the EEG α band, whereas DLB shows weaker posterior–anterior patterns within the β-band and greater network segregation within the θ-band compared with AD. Weighted network measures were more consistent across global thresholding levels, and the network properties reflected reduction in connectivity strength in the dementia groups. In conclusion, β- and θ-band network measures may be suitable as biomarkers for discriminating DLB from AD, whereas the α-band network is similarly affected in DLB and PDD compared with HC. These variations may reflect the impairment of attentional networks in Parkinsonian diseases such as DLB and PDD.
Author(s): Mehraram R, Kaiser M, Cromarty R, Graziadio S, O'Brien JT, Killen A, Taylor J-P, Peraza LR
Publication type: Article
Publication status: Published
Journal: Human Brain Mapping
Year: 2019
Volume: 41
Issue: 6
Pages: 1573-1590
Print publication date: 15/04/2020
Online publication date: 09/12/2019
Acceptance date: 29/11/2019
Date deposited: 02/01/2020
ISSN (print): 1065-9471
ISSN (electronic): 1097-0193
Publisher: John Wiley and Sons Inc.
URL: https://doi.org/10.1002/hbm.24896
DOI: 10.1002/hbm.24896
PubMed id: 31816147
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