Microstates as disease and progression markers in patients with mild cognitive impairment

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Microstates as disease and progression markers in patients with mild cognitive impairment. / Musaeus, Christian Sandøe; Nielsen, Malene Schjønning; Høgh, Peter.

I: Frontiers in Neuroscience, Bind 13, 563, 2019.

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningfagfællebedømt

Harvard

Musaeus, CS, Nielsen, MS & Høgh, P 2019, 'Microstates as disease and progression markers in patients with mild cognitive impairment', Frontiers in Neuroscience, bind 13, 563. https://doi.org/10.3389/fnins.2019.00563

APA

Musaeus, C. S., Nielsen, M. S., & Høgh, P. (2019). Microstates as disease and progression markers in patients with mild cognitive impairment. Frontiers in Neuroscience, 13, [563]. https://doi.org/10.3389/fnins.2019.00563

Vancouver

Musaeus CS, Nielsen MS, Høgh P. Microstates as disease and progression markers in patients with mild cognitive impairment. Frontiers in Neuroscience. 2019;13. 563. https://doi.org/10.3389/fnins.2019.00563

Author

Musaeus, Christian Sandøe ; Nielsen, Malene Schjønning ; Høgh, Peter. / Microstates as disease and progression markers in patients with mild cognitive impairment. I: Frontiers in Neuroscience. 2019 ; Bind 13.

Bibtex

@article{3cfb948509e24a778f6387cc84080136,
title = "Microstates as disease and progression markers in patients with mild cognitive impairment",
abstract = "Network dysfunction is well established in patients with Alzheimer's disease (AD) and has been shown to be present early in the disease. This is especially interesting in patients with mild cognitive impairment (MCI) since they are more likely to develop AD. In EEG, one type of network analysis is microstates where the EEG is divided into quasi-stable states and these microstates have been linked to networks found with resting state functional MRI. In the current exploratory study, we therefore wanted to explore the changes in microstates in MCI, and AD compared to healthy controls (HC) and whether microstates were able to separate patients with MCI who progressed (pMCI) and those who remained stable (sMCI). EEGs were recorded at baseline for 17 patients with AD, 27 patients with MCI, and 38 older HC and the patients were followed for 3 years. To investigate whole-brain dynamics we extracted different microstate parameters. We found that patients with MCI, and AD had significantly higher occurrence (p-value = 0.028), and coverage (p-value = 0.010) for microstate A compared to HC. However, we did not find any significant systematic deviation of the transition probabilities from randomness for any of the groups. No significant differences were found between pMCI and sMCI but the largest difference in duration was found for microstate D. Microstate A has been linked to the temporal lobes in studies combining EEG and fMRI and the temporal lobes are the most affected by AD pathology in the early stages of the disease. This supports our idea that microstate A may be the first affected microstate in early AD. Even though not significant between pMCI and sMCI, Microstate D has previously been shown to be associated with both frontal and parietal areas as measured with fMRI and may correspond to underlying pathological changes in the progression of MCI to AD. However, larger studies are needed to confirm these findings.",
keywords = "Alzheimer, Alzheimer's disease, EEG, Mci, Microstate, Mild cognitive impairment, Progression, Stable",
author = "Musaeus, {Christian Sand{\o}e} and Nielsen, {Malene Schj{\o}nning} and Peter H{\o}gh",
year = "2019",
doi = "10.3389/fnins.2019.00563",
language = "English",
volume = "13",
journal = "Frontiers in Neuroscience",
issn = "1662-4548",
publisher = "Frontiers Research Foundation",

}

RIS

TY - JOUR

T1 - Microstates as disease and progression markers in patients with mild cognitive impairment

AU - Musaeus, Christian Sandøe

AU - Nielsen, Malene Schjønning

AU - Høgh, Peter

PY - 2019

Y1 - 2019

N2 - Network dysfunction is well established in patients with Alzheimer's disease (AD) and has been shown to be present early in the disease. This is especially interesting in patients with mild cognitive impairment (MCI) since they are more likely to develop AD. In EEG, one type of network analysis is microstates where the EEG is divided into quasi-stable states and these microstates have been linked to networks found with resting state functional MRI. In the current exploratory study, we therefore wanted to explore the changes in microstates in MCI, and AD compared to healthy controls (HC) and whether microstates were able to separate patients with MCI who progressed (pMCI) and those who remained stable (sMCI). EEGs were recorded at baseline for 17 patients with AD, 27 patients with MCI, and 38 older HC and the patients were followed for 3 years. To investigate whole-brain dynamics we extracted different microstate parameters. We found that patients with MCI, and AD had significantly higher occurrence (p-value = 0.028), and coverage (p-value = 0.010) for microstate A compared to HC. However, we did not find any significant systematic deviation of the transition probabilities from randomness for any of the groups. No significant differences were found between pMCI and sMCI but the largest difference in duration was found for microstate D. Microstate A has been linked to the temporal lobes in studies combining EEG and fMRI and the temporal lobes are the most affected by AD pathology in the early stages of the disease. This supports our idea that microstate A may be the first affected microstate in early AD. Even though not significant between pMCI and sMCI, Microstate D has previously been shown to be associated with both frontal and parietal areas as measured with fMRI and may correspond to underlying pathological changes in the progression of MCI to AD. However, larger studies are needed to confirm these findings.

AB - Network dysfunction is well established in patients with Alzheimer's disease (AD) and has been shown to be present early in the disease. This is especially interesting in patients with mild cognitive impairment (MCI) since they are more likely to develop AD. In EEG, one type of network analysis is microstates where the EEG is divided into quasi-stable states and these microstates have been linked to networks found with resting state functional MRI. In the current exploratory study, we therefore wanted to explore the changes in microstates in MCI, and AD compared to healthy controls (HC) and whether microstates were able to separate patients with MCI who progressed (pMCI) and those who remained stable (sMCI). EEGs were recorded at baseline for 17 patients with AD, 27 patients with MCI, and 38 older HC and the patients were followed for 3 years. To investigate whole-brain dynamics we extracted different microstate parameters. We found that patients with MCI, and AD had significantly higher occurrence (p-value = 0.028), and coverage (p-value = 0.010) for microstate A compared to HC. However, we did not find any significant systematic deviation of the transition probabilities from randomness for any of the groups. No significant differences were found between pMCI and sMCI but the largest difference in duration was found for microstate D. Microstate A has been linked to the temporal lobes in studies combining EEG and fMRI and the temporal lobes are the most affected by AD pathology in the early stages of the disease. This supports our idea that microstate A may be the first affected microstate in early AD. Even though not significant between pMCI and sMCI, Microstate D has previously been shown to be associated with both frontal and parietal areas as measured with fMRI and may correspond to underlying pathological changes in the progression of MCI to AD. However, larger studies are needed to confirm these findings.

KW - Alzheimer

KW - Alzheimer's disease

KW - EEG

KW - Mci

KW - Microstate

KW - Mild cognitive impairment

KW - Progression

KW - Stable

U2 - 10.3389/fnins.2019.00563

DO - 10.3389/fnins.2019.00563

M3 - Journal article

C2 - 31263397

AN - SCOPUS:85068497879

VL - 13

JO - Frontiers in Neuroscience

JF - Frontiers in Neuroscience

SN - 1662-4548

M1 - 563

ER -

ID: 232099400