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Microstate connectivity alterations in patients with early Alzheimer’s disease
INTRODUCTION: Electroencephalography (EEG) microstates and brain network are altered in patients with Alzheimer’s disease (AD) and discussed as potential biomarkers for AD. Microstates correspond to defined states of brain activity, and their connectivity patterns may change accordingly. Little is k...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4697314/ https://www.ncbi.nlm.nih.gov/pubmed/26718102 http://dx.doi.org/10.1186/s13195-015-0163-9 |
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author | Hatz, Florian Hardmeier, Martin Benz, Nina Ehrensperger, Michael Gschwandtner, Ute Rüegg, Stephan Schindler, Christian Monsch, Andreas U. Fuhr, Peter |
author_facet | Hatz, Florian Hardmeier, Martin Benz, Nina Ehrensperger, Michael Gschwandtner, Ute Rüegg, Stephan Schindler, Christian Monsch, Andreas U. Fuhr, Peter |
author_sort | Hatz, Florian |
collection | PubMed |
description | INTRODUCTION: Electroencephalography (EEG) microstates and brain network are altered in patients with Alzheimer’s disease (AD) and discussed as potential biomarkers for AD. Microstates correspond to defined states of brain activity, and their connectivity patterns may change accordingly. Little is known about alteration of connectivity in microstates, especially in patients with amnestic mild cognitive impairment with stable or improving cognition within 30 months (aMCI). METHODS: Thirty-five outpatients with aMCI or mild dementia (mean age 77 ± 7 years, 47 % male, Mini Mental State Examination score ≥24) had comprehensive neuropsychological and clinical examinations. Subjects with cognitive decline over 30 months were allocated to the AD group, subjects with stable or improving cognition to the MCI-stable group. Results of neuropsychological testing at baseline were summarized in six domain scores. Resting state EEG was recorded with 256 electrodes and analyzed using TAPEEG. Five microstates were defined and individual data fitted. After phase transformation, the phase lag index (PLI) was calculated for the five microstates in every subject. Networks were reduced to 22 nodes for statistical analysis. RESULTS: The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups. In the present sample, they separated in a logistic regression model with a 100 % positive predictive value, 60 % negative predictive value, 100 % specificity and 77 % sensitivity between AD and MCI-stable. CONCLUSIONS: Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-015-0163-9) contains supplementary material, which is available to authorized users. |
format | Online Article Text |
id | pubmed-4697314 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-46973142016-01-01 Microstate connectivity alterations in patients with early Alzheimer’s disease Hatz, Florian Hardmeier, Martin Benz, Nina Ehrensperger, Michael Gschwandtner, Ute Rüegg, Stephan Schindler, Christian Monsch, Andreas U. Fuhr, Peter Alzheimers Res Ther Research INTRODUCTION: Electroencephalography (EEG) microstates and brain network are altered in patients with Alzheimer’s disease (AD) and discussed as potential biomarkers for AD. Microstates correspond to defined states of brain activity, and their connectivity patterns may change accordingly. Little is known about alteration of connectivity in microstates, especially in patients with amnestic mild cognitive impairment with stable or improving cognition within 30 months (aMCI). METHODS: Thirty-five outpatients with aMCI or mild dementia (mean age 77 ± 7 years, 47 % male, Mini Mental State Examination score ≥24) had comprehensive neuropsychological and clinical examinations. Subjects with cognitive decline over 30 months were allocated to the AD group, subjects with stable or improving cognition to the MCI-stable group. Results of neuropsychological testing at baseline were summarized in six domain scores. Resting state EEG was recorded with 256 electrodes and analyzed using TAPEEG. Five microstates were defined and individual data fitted. After phase transformation, the phase lag index (PLI) was calculated for the five microstates in every subject. Networks were reduced to 22 nodes for statistical analysis. RESULTS: The domain score for verbal learning and memory and the microstate segmented PLI between the left centro-lateral and parieto-occipital regions in the theta band at baseline differentiated significantly between the groups. In the present sample, they separated in a logistic regression model with a 100 % positive predictive value, 60 % negative predictive value, 100 % specificity and 77 % sensitivity between AD and MCI-stable. CONCLUSIONS: Combining neuropsychological and quantitative EEG test results allows differentiation between subjects with aMCI remaining stable and subjects with aMCI deteriorating over 30 months. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s13195-015-0163-9) contains supplementary material, which is available to authorized users. BioMed Central 2015-12-31 /pmc/articles/PMC4697314/ /pubmed/26718102 http://dx.doi.org/10.1186/s13195-015-0163-9 Text en © Hatz et al. 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. |
spellingShingle | Research Hatz, Florian Hardmeier, Martin Benz, Nina Ehrensperger, Michael Gschwandtner, Ute Rüegg, Stephan Schindler, Christian Monsch, Andreas U. Fuhr, Peter Microstate connectivity alterations in patients with early Alzheimer’s disease |
title | Microstate connectivity alterations in patients with early Alzheimer’s disease |
title_full | Microstate connectivity alterations in patients with early Alzheimer’s disease |
title_fullStr | Microstate connectivity alterations in patients with early Alzheimer’s disease |
title_full_unstemmed | Microstate connectivity alterations in patients with early Alzheimer’s disease |
title_short | Microstate connectivity alterations in patients with early Alzheimer’s disease |
title_sort | microstate connectivity alterations in patients with early alzheimer’s disease |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4697314/ https://www.ncbi.nlm.nih.gov/pubmed/26718102 http://dx.doi.org/10.1186/s13195-015-0163-9 |
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