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EEG time signature in Alzheimer´s disease: Functional brain networks falling apart

Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uni...

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Autores principales: Smailovic, Una, Koenig, Thomas, Laukka, Erika J, Kalpouzos, Grégoria, Andersson, Thomas, Winblad, Bengt, Jelic, Vesna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909352/
https://www.ncbi.nlm.nih.gov/pubmed/31795039
http://dx.doi.org/10.1016/j.nicl.2019.102046
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author Smailovic, Una
Koenig, Thomas
Laukka, Erika J
Kalpouzos, Grégoria
Andersson, Thomas
Winblad, Bengt
Jelic, Vesna
author_facet Smailovic, Una
Koenig, Thomas
Laukka, Erika J
Kalpouzos, Grégoria
Andersson, Thomas
Winblad, Bengt
Jelic, Vesna
author_sort Smailovic, Una
collection PubMed
description Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uniquely high temporal resolution, necessary for investigation of brain network dynamics. Since synaptic dysfunction is an early event and best correlate of cognitive status and decline in patients along Alzheimer's disease (AD) continuum, EEG microstates might serve as valuable early markers of AD. The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n = 308) and memory clinic patients: subjective cognitive decline (SCD, n = 210); mild cognitive impairment (MCI, n = 230) and AD (n = 197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD. Four most representative microstate maps assigned as classes A, B (asymmetrical), C and D (symmetrical) were computed from the resting state EEGs since it has been shown previously that this is sufficient to explain most of the resting state EEG data. Statistically different topography of microstate maps were found between the controls and the patient groups for microstate classes A, C and D. Changes in the topography of microstate class C were associated with the CSF Aβ42 levels, whereas changes in the topography of class B were linked with the CSF p-tau levels. Gradient-like increase in the contribution of asymmetrical (A and B) and gradient-like decrease in the contribution of symmetrical (C and D) maps were observed with the more severe stage of cognitive impairment. Our study demonstrated extensive relationship of resting state EEG microstates topographies and parameters with the stage of cognitive impairment and AD biomarkers. Resting state EEG microstates might therefore serve as functional markers of early disruption of neurocognitive networks in patients along AD continuum.
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spelling pubmed-69093522019-12-23 EEG time signature in Alzheimer´s disease: Functional brain networks falling apart Smailovic, Una Koenig, Thomas Laukka, Erika J Kalpouzos, Grégoria Andersson, Thomas Winblad, Bengt Jelic, Vesna Neuroimage Clin Regular Article Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uniquely high temporal resolution, necessary for investigation of brain network dynamics. Since synaptic dysfunction is an early event and best correlate of cognitive status and decline in patients along Alzheimer's disease (AD) continuum, EEG microstates might serve as valuable early markers of AD. The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n = 308) and memory clinic patients: subjective cognitive decline (SCD, n = 210); mild cognitive impairment (MCI, n = 230) and AD (n = 197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD. Four most representative microstate maps assigned as classes A, B (asymmetrical), C and D (symmetrical) were computed from the resting state EEGs since it has been shown previously that this is sufficient to explain most of the resting state EEG data. Statistically different topography of microstate maps were found between the controls and the patient groups for microstate classes A, C and D. Changes in the topography of microstate class C were associated with the CSF Aβ42 levels, whereas changes in the topography of class B were linked with the CSF p-tau levels. Gradient-like increase in the contribution of asymmetrical (A and B) and gradient-like decrease in the contribution of symmetrical (C and D) maps were observed with the more severe stage of cognitive impairment. Our study demonstrated extensive relationship of resting state EEG microstates topographies and parameters with the stage of cognitive impairment and AD biomarkers. Resting state EEG microstates might therefore serve as functional markers of early disruption of neurocognitive networks in patients along AD continuum. Elsevier 2019-10-18 /pmc/articles/PMC6909352/ /pubmed/31795039 http://dx.doi.org/10.1016/j.nicl.2019.102046 Text en © 2019 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Regular Article
Smailovic, Una
Koenig, Thomas
Laukka, Erika J
Kalpouzos, Grégoria
Andersson, Thomas
Winblad, Bengt
Jelic, Vesna
EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title_full EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title_fullStr EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title_full_unstemmed EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title_short EEG time signature in Alzheimer´s disease: Functional brain networks falling apart
title_sort eeg time signature in alzheimer´s disease: functional brain networks falling apart
topic Regular Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6909352/
https://www.ncbi.nlm.nih.gov/pubmed/31795039
http://dx.doi.org/10.1016/j.nicl.2019.102046
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