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. 2019 Nov 15:10:826.
doi: 10.3389/fpsyt.2019.00826. eCollection 2019.

Altered Electroencephalographic Resting-State Large-Scale Brain Network Dynamics in Euthymic Bipolar Disorder Patients

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Altered Electroencephalographic Resting-State Large-Scale Brain Network Dynamics in Euthymic Bipolar Disorder Patients

Alena Damborská et al. Front Psychiatry. .

Abstract

Background: Neuroimaging studies provided evidence for disrupted resting-state functional brain network activity in bipolar disorder (BD). Electroencephalographic (EEG) studies found altered temporal characteristics of functional EEG microstates during depressive episode within different affective disorders. Here we investigated whether euthymic patients with BD show deviant resting-state large-scale brain network dynamics as reflected by altered temporal characteristics of EEG microstates. Methods: We used high-density EEG to explore between-group differences in duration, coverage, and occurrence of the resting-state functional EEG microstates in 17 euthymic adults with BD in on-medication state and 17 age- and gender-matched healthy controls. Two types of anxiety, state and trait, were assessed separately with scores ranging from 20 to 80. Results: Microstate analysis revealed five microstates (A-E) in global clustering across all subjects. In patients compared to controls, we found increased occurrence and coverage of microstate A that did not significantly correlate with anxiety scores. Conclusion: Our results provide neurophysiological evidence for altered large-scale brain network dynamics in BD patients and suggest the increased presence of A microstate to be an electrophysiological trait characteristic of BD.

Keywords: bipolar disorder; dynamic brain activity; electroencephalographic microstate; high-density electroencephalography; large-scale brain networks; resting state.

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Figures

Figure 1
Figure 1
The five microstate topographies (AE) identified in the group clusterings across patients (BD) and healthy controls (HC) and in the global clustering across all subjects (BD+HC). Note that similar five dominant microstate topographies were identified in all three clusterings.
Figure 2
Figure 2
Temporal dynamics of electroencephalographic microstates in patients with bipolar disorder (BD) and in healthy controls (HC). In each subplot, the raw data are plotted on top of the boxplot showing the mean (▪), 95% confidence interval (box plot area), 1 standard deviation (whiskers), and significant differences (*). In all plots, x-axes represent the subject group; y-axes represent the occurrence (upper plots) or coverage (lower plots). Note significantly increased occurrence and coverage of the microstate A and B in the BD compared to HC group (FDR corrected p < 0.05).
Figure 3
Figure 3
The alpha power in patients with bipolar disorder (BD) and healthy controls (HC). Raw data are plotted on top of each boxplot showing the mean (▪), 95% confidence interval (box plot area), and non-outlier range (whiskers). The x-axis represents the subject group; the y-axis represents the average alpha (8–14 Hz) power across 204 channels. Note significantly decreased alpha power in the BD compared to HC group (p < 0.03, Z value 2.7).

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