Cargando…

Weighted network measures reveal differences between dementia types: An EEG study

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 arc...

Descripción completa

Detalles Bibliográficos
Autores principales: Mehraram, Ramtin, Kaiser, Marcus, Cromarty, Ruth, Graziadio, Sara, O'Brien, John T., Killen, Alison, Taylor, John‐Paul, Peraza, Luis R.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267959/
https://www.ncbi.nlm.nih.gov/pubmed/31816147
http://dx.doi.org/10.1002/hbm.24896
_version_ 1783541513672720384
author Mehraram, Ramtin
Kaiser, Marcus
Cromarty, Ruth
Graziadio, Sara
O'Brien, John T.
Killen, Alison
Taylor, John‐Paul
Peraza, Luis R.
author_facet Mehraram, Ramtin
Kaiser, Marcus
Cromarty, Ruth
Graziadio, Sara
O'Brien, John T.
Killen, Alison
Taylor, John‐Paul
Peraza, Luis R.
author_sort Mehraram, Ramtin
collection PubMed
description 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.
format Online
Article
Text
id pubmed-7267959
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher John Wiley & Sons, Inc.
record_format MEDLINE/PubMed
spelling pubmed-72679592020-06-12 Weighted network measures reveal differences between dementia types: An EEG study Mehraram, Ramtin Kaiser, Marcus Cromarty, Ruth Graziadio, Sara O'Brien, John T. Killen, Alison Taylor, John‐Paul Peraza, Luis R. Hum Brain Mapp Research Articles 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. John Wiley & Sons, Inc. 2019-12-09 /pmc/articles/PMC7267959/ /pubmed/31816147 http://dx.doi.org/10.1002/hbm.24896 Text en © 2019 The Authors. Human Brain Mapping published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Mehraram, Ramtin
Kaiser, Marcus
Cromarty, Ruth
Graziadio, Sara
O'Brien, John T.
Killen, Alison
Taylor, John‐Paul
Peraza, Luis R.
Weighted network measures reveal differences between dementia types: An EEG study
title Weighted network measures reveal differences between dementia types: An EEG study
title_full Weighted network measures reveal differences between dementia types: An EEG study
title_fullStr Weighted network measures reveal differences between dementia types: An EEG study
title_full_unstemmed Weighted network measures reveal differences between dementia types: An EEG study
title_short Weighted network measures reveal differences between dementia types: An EEG study
title_sort weighted network measures reveal differences between dementia types: an eeg study
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7267959/
https://www.ncbi.nlm.nih.gov/pubmed/31816147
http://dx.doi.org/10.1002/hbm.24896
work_keys_str_mv AT mehraramramtin weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT kaisermarcus weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT cromartyruth weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT graziadiosara weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT obrienjohnt weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT killenalison weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT taylorjohnpaul weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy
AT perazaluisr weightednetworkmeasuresrevealdifferencesbetweendementiatypesaneegstudy