Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2021 Sep 13:13:714220.
doi: 10.3389/fnagi.2021.714220. eCollection 2021.

Cortical Frontoparietal Network Dysfunction in CHMP2B-Frontotemporal Dementia

Collaborators, Affiliations

Cortical Frontoparietal Network Dysfunction in CHMP2B-Frontotemporal Dementia

Christian Sandøe Musaeus et al. Front Aging Neurosci. .

Abstract

A rare cause of inherited frontotemporal dementia (FTD) is a mutation in the CHMP2B gene on chromosome 3 leading to the autosomal dominantly inherited FTD (CHMP2B-FTD). Since CHMP2B-FTD is clinically well-characterized, and patients show a distinct pattern of executive dysfunction, the condition offers possible insight in the early electroencephalographic (EEG) changes in the cortical networks. Specifically, EEG microstate analysis parses the EEG signals into topographies believed to represent discrete network activations. We investigated the EEG dynamics in patients with symptomatic CHMP2B-FTD (n = 5) as well as pre-symptomatic mutation carriers (n = 5) compared to non-carrier family members (n = 6). The data was parsed into four archetypal microstates and global power was calculated. A trend was found for lower occurrence in microstate D in CHMP2B-FTD (p-value = 0.177, F-value = 2.036). Patients with recent symptom onset (<1 year) showed an increased duration of microstate D, whereas patients who had been symptomatic for longer periods (>2 years) showed decreased duration. Patients with CHMP2B-FTD present with executive dysfunction, and microstate D has previously been shown to be associated with the fronto-parietal network. The biphasic pattern may represent the pathophysiological changes in brain dynamics during neurodegeneration, which may apply to other neurodegenerative diseases.

Keywords: CHMP2B; EEG; FTD; Frontotemporal dementia; microstates; microstates analysis; spectral power.

PubMed Disclaimer

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Figures

FIGURE 1
FIGURE 1
Bar graphs showing the mean and standard deviation of duration, occurrence, and coverage for microstate D and the mean of the other microstates (A, B, and C) for the controls (n = 6), pre-symptomatic carriers (n = 5), patients with CHMP2B-FTD with recent (<1 year) onset of symptoms (n = 2), and patients who had been symptomatic for a longer (>2 years) period (n = 3).
FIGURE 2
FIGURE 2
Proposed model of cortical network dysfunction as seen in neurodegenerative diseases. When the neurodegenerative disease starts to affect a cortical network, (I) the compensation phase shows increased activity in the affected network (microstate D). This continues until the network can no longer compensate and then the patient starts to present symptoms in (II) the symptomatic phase (time of referral). In (III) the decompensation phase, the network can no longer compensate for the damages, and the activity falls below the previous level.

References

    1. Benedek M., Schickel R. J., Jauk E., Fink A., Neubauer A. C. (2014). Alpha power increases in right parietal cortex reflects focused internal attention. Neuropsychologia 56 393–400. 10.1016/j.neuropsychologia.2014.02.010 - DOI - PMC - PubMed
    1. Besthorn C., Sattel H., Hentschel F., Daniel S., Zerfass R., Forstl H. (1996). Quantitative EEG in frontal lobe dementia. J. Neural Transm. Suppl. 47 169–181. 10.1007/978-3-7091-6892-9_11 - DOI - PubMed
    1. Britz J., Van De Ville D., Michel C. M. (2010). BOLD correlates of EEG topography reveal rapid resting-state network dynamics. Neuroimage 52 1162–1170. 10.1016/j.neuroimage.2010.02.052 - DOI - PubMed
    1. Custo A., Van De Ville D., Wells W. M., Tomescu M. I., Brunet D., Michel C. M. (2017). Electroencephalographic resting-state networks: source localization of microstates. Brain Connect. 7 671–682. 10.1089/brain.2016.0476 - DOI - PMC - PubMed
    1. Delorme A., Makeig S. (2004). EEGLAB: an open source toolbox for analysis of single-trial EEG dynamics including independent component analysis. J. Neurosci. Methods 134 9–21. 10.1016/j.jneumeth.2003.10.009 - DOI - PubMed

LinkOut - more resources