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The Functional Aspects of Resting EEG Microstates: A Systematic Review

Authors:
Povilas Tarailis at University of Geneva
Povilas Tarailis
Thomas Koenig at Universität Bern
Thomas Koenig
Christoph M. Michel at University of Geneva
Christoph M. Michel
Inga Griskova-Bulanova at Vilnius University
Inga Griskova-Bulanova
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Abstract and Figures

A growing body of clinical and cognitive neuroscience studies have adapted a broadband EEG microstate approach to evaluate the electrical activity of large-scale cortical networks. However, the functional aspects of these microstates have not yet been systematically reviewed. Here, we present an overview of the existing literature and systematize the results to provide hints on the functional role of electrical brain microstates. Studies that evaluated and manipulated the temporal properties of resting-state microstates and utilized questionnaires, task-initiated thoughts, specific tasks before or between EEG session(s), pharmacological interventions, neuromodulation approaches, or localized sources of the extracted microstates were selected. Fifty studies that met the inclusion criteria were included. A new microstate labeling system has been proposed for a comprehensible comparison between the studies, where four classical microstates are referred to as A-D, and the others are labeled by the frequency of their appearance. Microstate A was associated with both auditory and visual processing and links to subjects’ arousal/arousability. Microstate B showed associations with visual processing related to self, self-visualization, and autobiographical memory. Microstate C was related to processing personally significant information, self-reflection, and self-referential internal mentation rather than autonomic information processing. In contrast, microstate E was related to processing interoceptive and emotional information and to the salience network. Microstate D was associated with executive functioning. Microstate F is suggested to be a part of the Default Mode Network and plays a role in personally significant information processing, mental simulations, and theory of mind. Microstate G is potentially linked to the somatosensory network.
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Brain Topography (2024) 37:181–217
https://doi.org/10.1007/s10548-023-00958-9
REVIEW
The Functional Aspects ofResting EEG Microstates: ASystematic
Review
PovilasTarailis1· ThomasKoenig2· ChristophM.Michel3,4· IngaGriškova‑Bulanova1
Received: 14 January 2023 / Accepted: 11 April 2023 / Published online: 10 May 2023
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023
Abstract
A growing body of clinical and cognitive neuroscience studies have adapted a broadband EEG microstate approach to
evaluate the electrical activity of large-scale cortical networks. However, the functional aspects of these microstates have
not yet been systematically reviewed. Here, we present an overview of the existing literature and systematize the results
to provide hints on the functional role of electrical brain microstates. Studies that evaluated and manipulated the temporal
properties of resting-state microstates and utilized questionnaires, task-initiated thoughts, specific tasks before or between
EEG session(s), pharmacological interventions, neuromodulation approaches, or localized sources of the extracted micro-
states were selected. Fifty studies that met the inclusion criteria were included. A new microstate labeling system has been
proposed for a comprehensible comparison between the studies, where four classical microstates are referred to as A-D,
and the others are labeled by the frequency of their appearance. Microstate A was associated with both auditory and visual
processing and links to subjects’ arousal/arousability. Microstate B showed associations with visual processing related to
self, self-visualization, and autobiographical memory. Microstate C was related to processing personally significant infor-
mation, self-reflection, and self-referential internal mentation rather than autonomic information processing. In contrast,
microstate E was related to processing interoceptive and emotional information and to the salience network. Microstate D
was associated with executive functioning. Microstate F is suggested to be a part of the Default Mode Network and plays a
role in personally significant information processing, mental simulations, and theory of mind. Microstate G is potentially
linked to the somatosensory network.
Keywords EEG microstates· Resting state· Functions· Neuronal sources
Introduction
An increasing number of clinical and cognitive neuroscience
studies have been applying a broadband electroencephalog-
raphy (EEG) microstate approach to evaluate the electri-
cal activity of large-scale cortical networks (Fig.1). With
the microstate approach, the recorded electrical signal is
defined by non-overlapping distinct topographies (Khanna
etal. 2015; Koenig etal. 2002), which, through competi-
tive fitting based on spatial correlation, are fitted back to
the original signal. The obtained topographies are reliable
and comparable between the studies and independent of the
number of electrodes used to record the signal (Zhang etal.
2021), eyes open/closed instruction (Zanesco etal. 2020b),
analysis frequency range (Férat etal. 2022b) and algorithms
used to cluster thedata (Khanna etal., 2014; von Wegner
etal. 2018). Based on physical laws, distinct topographies
are generated by spatially distinct neuronal sources (Michel
Handling Editor: Micah Murray.
This is one of several papers published together in Brain
Topography on the "Special Issue: Microstates in EEG/MEG and
ERP Research”.
* Inga Griškova-Bulanova
i.griskova@gmail.com; inga.griskova-bulanova@gf.vu.lt
1 Life Sciences Centre, Institute ofBiosciences, Vilnius
University, Vilnius, Lithuania
2 Translational Research Center, University Hospital
ofPsychiatry, University ofBern, Bern, Switzerland
3 Functional Brain Mapping Laboratory, Department
ofFundamental Neuroscience, University ofGeneva,
Geneva, Switzerland
4 Center forBiomedical Imaging (CIBM), Lausanne,
Switzerland
Content courtesy of Springer Nature, terms of use apply. Rights reserved.
... In other words, the EEG microstate reveals the fast-changing temporal dynamics of resting state networks with high temporal resolution (Lehmann et al., 1987;Michel and Koenig, 2018). Notably, empirical studies increasingly demonstrate systematic links between variations in EEG microstates and fluctuations in mental states, supporting the utility of microstate analysis in probing brain dynamics and mental health (Khanna et al., 2015;Michel and Koenig, 2018;Chivu et al., 2023;Schiller et al., 2023;Tarailis et al., 2023). EEG microstate dynamics discriminate between different cognitive states like mental calculation, visualization, verbalization, and autobiographical memory, and socio-affective states and traits (Milz et al., 2016;Seitzman et al., 2017;Bréchet et al., 2019;Schiller et al., 2023;Tarailis et al., 2023). ...
... Notably, empirical studies increasingly demonstrate systematic links between variations in EEG microstates and fluctuations in mental states, supporting the utility of microstate analysis in probing brain dynamics and mental health (Khanna et al., 2015;Michel and Koenig, 2018;Chivu et al., 2023;Schiller et al., 2023;Tarailis et al., 2023). EEG microstate dynamics discriminate between different cognitive states like mental calculation, visualization, verbalization, and autobiographical memory, and socio-affective states and traits (Milz et al., 2016;Seitzman et al., 2017;Bréchet et al., 2019;Schiller et al., 2023;Tarailis et al., 2023). Moreover, EEG microstate temporal dynamics are differentiating between pathological brain states (Tomescu et al., 2014(Tomescu et al., , 2015Rieger et al., 2016;Michel and Koenig, 2018;Damborská et al., 2019;Chivu et al., 2023). ...
... Accumulating evidence suggests that EEG microstates represent the electrical fingerprints of resting-state networks; however, their one-to-one correspondence is still debated (Britz et al., 2010;Musso et al., 2010;Yuan et al., 2012;Custo et al., 2017;Michel and Koenig, 2018). Generally, A-B microstates are related to bottom-up visual and auditory/language-related. Microstate A initially recognized for its right frontal-to-left posterior pattern, is associated with auditory and visual processing, although its exact role remains unclear due to its interaction with arousal states (Milz et al., 2016;Seitzman et al., 2017;Michel and Koenig, 2018;Antonova et al., 2022;Tarailis et al., 2023). Microstate B consistently links to visual processing, including tasks involving self-related processes and scene imagery, with implications extending beyond visual stimuli and interacting with other microstates, notably microstate C (Milz et al., 2016;Seitzman et al., 2017;Michel and Koenig, 2018;Bréchet et al., 2019;Antonova et al., 2022;Tarailis et al., 2023). ...
Valence-specific EEG microstate modulations during self-generated affective states
Article
Full-text available
  • May 2024
Introduction This study aims to explore the temporal dynamics of brain networks involved in self-generated affective states, specifically focusing on modulating these states in both positive and negative valences. The overarching goal is to contribute to a deeper understanding of the neurodynamic patterns associated with affective regulation, potentially informing the development of biomarkers for therapeutic interventions in mood and anxiety disorders. Methods Utilizing EEG microstate analysis during self-generated affective states, we investigated the temporal dynamics of five distinct microstates across different conditions, including baseline resting state and self-generated states of positive valence (e.g., awe, contentment) and negative valence (e.g., anger, fear). Results The study revealed noteworthy modulations in microstate dynamics during affective states. Additionally, valence-specific mechanisms of spontaneous affective regulation were identified. Negative valence affective states were characterized by the heightened presence of attention-associated microstates and reduced occurrence of salience-related microstates during negative valence states. In contrast, positive valence affective states manifested a prevalence of microstates related to visual/autobiographical memory and a reduced presence of auditory/language-associated microstates compared to both baseline and negative valence states. Discussion This study contributes to the field by employing EEG microstate analysis to discern the temporal dynamics of brain networks involved in self-generated affective states. Insights from this research carry significant implications for understanding neurodynamic patterns in affective regulation. The identification of valence-specific modulations and mechanisms has potential applications in developing biomarkers for mood and anxiety disorders, offering novel avenues for therapeutic interventions.
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... A growing number of studies have employed microstates to investigate the neural correlates of cognitive processes and clinical disorders, e.g. schizophrenia, psychosis, Alzheimer's disease, epilepsy, bipolar disorder, autism spectrum disorder and many others (reviewed in Michel and Koenig (2018); Tarailis et al. (2023)). Expanding the microstate methodology to dyads of interacting participants (two-brain microstates) enables us to investigate quasi-stable moments of inter-brain synchronized activity, while not constraining the quantification of inter-brain synchronization to symmetric brain states. ...
... plementary Figure S1A and Supplementary Figure S2A respectively. The topographies of the determined microstates estimated in the alpha, beta and broadband frequency range were very similar with each other, and also remarkably similar to the conventionally found resting-state EEG microstates in the literature (Michel and Koenig, 2018;Tarailis et al., 2023;Koenig et al., 2023). Thus we sorted and labeled the microstates in line with the prototypes from literature with microstate A showing a left-right orientation, B with a right-left orientation, C with an anterior-posterior orientation, D with a fronto-central maximum, and E with an occipito-central maximum (Férat et al., 2022;Tarailis et al., 2023;Koenig et al., 2023). ...
... The topographies of the determined microstates estimated in the alpha, beta and broadband frequency range were very similar with each other, and also remarkably similar to the conventionally found resting-state EEG microstates in the literature (Michel and Koenig, 2018;Tarailis et al., 2023;Koenig et al., 2023). Thus we sorted and labeled the microstates in line with the prototypes from literature with microstate A showing a left-right orientation, B with a right-left orientation, C with an anterior-posterior orientation, D with a fronto-central maximum, and E with an occipito-central maximum (Férat et al., 2022;Tarailis et al., 2023;Koenig et al., 2023). ...
Two-brain microstates: A novel method for quantifying task-driven inter-brain asymmetry
Preprint
Full-text available
  • May 2024
Joint action and interpersonal coordination between individuals are integral parts of daily life, and various behavioral tasks have been designed to study their emergence and maintenance. One example is the mirror-game paradigm, which examines the dynamics of two people improvising motion together. However, the underlying neural mechanisms remain poorly understood, and inter-brain methods underdeveloped. Previously, we reported unique individual behavioral and neural signatures of performing actions when observed by others using a mirror-game paradigm. Here, we explored inter-brain synchronization during the mirror-game paradigm using a novel approach employing two-brain EEG microstates. Microstates are quasi-stable configurations of brain activity that have been reliably replicated across studies, and proposed to be basic buildings blocks for mental processing. Expanding the microstate methodology to dyads of interacting participants (two-brain microstates) enables us to investigate quasi-stable moments of inter-brain synchronous and asymmetric activity. Interestingly, we found that conventional microstates fitted to individuals were not related to the different task conditions; however, the dynamics of the two-brain microstates were changed for the observed actor-observer condition, compared to all other conditions where participants had more symmetric task demands (rest, individual, joint). These results suggest that two-brain microstates might serve as a method for identifying inter-brain states during asymmetric real-time social interaction.
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... The length of the included EEG data for analysis was at least 75 epochs. 35 Microstate Analysis MATLAB R2021a was used to conducted microstate analysis. The data underwent average referencing and were bandpass filtered in the range of 2-20Hz. ...
Abnormalities in Electroencephalographic Microstates in Patients with Late-Life Depression
Article
Full-text available
  • Jun 2024
Background Late-life depression (LLD) is characterized by disrupted brain networks. Resting-state networks in the brain are composed of both stable and transient topological structures known as microstates, which reflect the dynamics of the neural activities. However, the specific pattern of EEG microstate in LLD remains unclear. Methods Resting-state EEG were recorded for 31 patients with episodic LLD (eLLD), 20 patients with remitted LLD (rLLD) and 32 healthy controls (HCs) using a 64-channel cap. The clinical data of the patients were collected and the 17-Item Hamilton Rating Scale for Depression (HAMD) was used for symptom assessment. Duration, occurrence, time coverage and syntax of the four microstate classes (A-D) were calculated. Group differences in EEG microstates and the relationship between microstates parameters and clinical features were analyzed. Results Compared with NC and patients with rLLD, patients with eLLD showed increased duration and time coverage of microstate class D. Besides, a decrease in occurrence of microstate C and transition probability between microstate B and C was observed. In addition, the time coverage of microstate D was positively correlated with the total score of HAMD, core symptoms, and miscellaneous items. Conclusion These findings suggest that disrupted EEG microstates may be associated with the pathophysiology of LLD and may serve as potential state markers for the monitoring of the disease.
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... lower GEVs, occurrences, and transitions from one state to microstates C and C' (noting that 107 their C' can be relabeled to E; cf., Tarailis et al., 2024). 108 ...
Topographical polarity reveals continuous EEG microstate transitions and electric field direction in healthy aging
Preprint
  • Mar 2024
EEG microstate sequences, representing whole-brain spatial potential distribution patterns of the EEG, offer valuable insights for capturing spatiotemporally continuous and fluctuating neural dynamics with high temporal resolution through appropriate discretization. Recent studies suggest that EEG microstate transitions are gradual and continuous phenomena, contrary to the classical view of binary transitions. This study aimed to update conventional microstate analysis to reflect continuous EEG dynamics and examine differences in age-related electrophysiological state transitions. We considered the relative positions of EEG microstates on the neural manifold and their topographical polarity. Transition probability results showed fewer transitions on the microstate D-C-E axis in older adults. In contrast, transitions among microstates A, D, and B increased in the older group and were mainly observed within polarity. Furthermore, the 100 microstate transitions, which are variations of the shortest transitions between 10 microstates, could be reduced to 8 principal components based on the co-occurrence of each transition, including hubs C and E, planar transitions through msA/B and D, and unidirectional transition components. Several transition components were potentially significant predictors of age group. These features were nearly replicated in independent data, indicating their robustness in characterizing age-related electrophysiological spatiotemporal dynamics.
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Dynamic Resting-State EEG Alpha Connectivity: Quantifying Brain Network State Evolution in Individuals with Psychosis
Preprint
  • Jun 2024
This study introduces a novel pipeline for investigating brain activity in psychosis using dynamic connectivity from resting-state EEG. Seventy-eight individuals with psychosis and sixty control subjects were analyzed. Source estimation was performed using eLORETA, and connectivity in the alpha band was assessed with wPLI. A modified k-means algorithm was employed to cluster connectivity matrices into distinct brain network states (BNS), from which several metrics were extracted. The segmentation revealed five distinct BNS. The control group exhibited significantly higher connectivity power, while the psychosis group showed greater duration dispersion. In the control group, correlations were found between BNS metrics and cognitive scales. Negative correlations were identified between BNS metrics and the SANS scales in the psychosis group. These results underscore the variability of neural dynamics in individuals with psychosis, as demonstrated by this novel methodology.
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Fatigue in Multiple Sclerosis: A Resting-State EEG Microstate Study
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  • BRAIN TOPOGR
Fatigue affects approximately 80% of people with Multiple Sclerosis (PwMS) and can impact several domains of daily life. However, the neural underpinnings of fatigue in MS are still not completely clear. The aim of our study was to investigate the spontaneous large-scale networks functioning associated with fatigue in PwMS using the EEG microstate approach with a spectral decomposition. Forty-three relapsing–remitting MS patients and twenty-four healthy controls (HCs) were recruited. All participants underwent an administration of Modified Fatigue Impact scale (MFIS) and a 15-min resting-state high-density EEG recording. We compared the microstates of healthy subjects, fatigued (F-MS) and non-fatigued (nF-MS) patients with MS; correlations with clinical and behavioral fatigue scores were also analyzed. Microstates analysis showed six templates across groups and frequencies. We found that in the F-MS emerged a significant decrease of microstate F, associated to the salience network, in the broadband and in the beta band. Moreover, the microstate B, associated to the visual network, showed a significant increase in fatigued patients than healthy subjects in broadband and beta bands. The multiple linear regression showed that the high cognitive fatigue was predicted by both an increase and decrease, respectively, in delta band microstate B and beta band microstate F. On the other hand, higher physical fatigue was predicted with lower occurrence microstate F in beta band. The current findings suggest that in MS the higher level of fatigue might be related to a maladaptive functioning of the salience and visual network.
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Social functioning predicts individual changes in EEG microstates following intranasal oxytocin administration: A double-blind, cross-over randomized clinical trial
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Oxytocin (OXT) modulates social behaviors. However, the administration of exogenous OXT in humans produces inconsistent behavioral changes, affecting future consideration of OXT as a treatment for autism and other disorders with social symptoms. Inter-individual variability in social functioning traits might play a key role in how OXT changes brain activity and, therefore, behavior. Here, we investigated if inter-individual variability might dictate how single-dose intranasal OXT administration (IN-OXT) changes spontaneous neural activity during the eyes-open resting state. We used a double-blinded, randomized, placebo-controlled, cross-over design on 30 typically developing young adult men to investigate the dynamics of EEG microstates corresponding to activity in defined neural networks. We confirmed previous reports that, at the group level, IN-OXT increases the representation of the attention and salience microstates. Furthermore, we identified a decreased representation of microstates associated with the default mode network. Using multivariate partial least square statistical analysis, we found that social functioning traits associated with IN-OXT-induced changes in microstate dynamics in specific spectral bands. Correlation analysis further revealed that the higher the social functioning, the more IN-OXT increased the appearance of the visual network-associated microstate, and suppressed the appearance of a default mode network-related microstate. The lower the social functioning, the more IN-OXT increases the appearance of the salience microstate. The effects we report on the salience microstate support the hypothesis that OXT regulates behavior by enhancing social salience. Moreover, our findings indicate that social functioning traits modulate responses to IN-OXT and could partially explain the inconsistent reports on IN-OXT effects.
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EEG Microstate Associated with Trait Nostalgia
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Nostalgia, a self-related emotion characterized by its bittersweet yet predominantly positive nature, plays a vital role in shaping individual psychology and behavior. This includes impacts on mental and physical health, behavioral patterns, and cognitive functions. However, higher levels of trait nostalgia may be linked to potential adverse outcomes, such as increased loneliness, heightened neuroticism, and more intense experiences of grief. The specific electroencephalography (EEG) feature associated with individuals exhibiting trait nostalgia, and how it differs from others, remains an area of uncertainty. To address this, our study employs microstate analysis to investigate the differences in resting-state EEG between individuals with varying levels of trait nostalgia. We assessed trait nostalgia in 63 participants using the Personal Inventory of Nostalgia and collected their resting-state EEG signals with eyes closed. The results of the regression analysis indicate a significant correlation between trait nostalgia and the temporal characteristics of microstates A, B, and C. Further, the occurrence of microstate B was significantly more frequent in the high trait nostalgia group than in the low trait nostalgia group. Independent samples t-test results showed that the transition probability between microstates A and B was significantly higher in the high trait nostalgia group. These results support the hypothesis that trait nostalgia is reflected in the resting state brain activity. Furthermore, they reveal a deeper sensory immersion in nostalgia experiences among individuals with high levels of trait nostalgia, and highlight the critical role of self-referential and autobiographical memory processes in nostalgia.
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Spectral decomposition of EEG microstates in post-traumatic stress disorder
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  • Jul 2022
Microstates offer a promising framework to study fast-scale brain dynamics in the resting-state electroencephalogram (EEG). However, microstate dynamics have yet to be investigated in post-traumatic stress disorder (PTSD), despite research demonstrating resting-state alterations in PTSD. We performed microstate-based segmentation of resting-state EEG in a clinical population of participants with PTSD (N = 61) and a non-traumatized, healthy control group (N = 61). Microstate-based measures (i.e., occurrence, mean duration, time coverage) were compared group-wise using broadband (1-30 Hz) and frequency-specific (i.e., delta, theta, alpha, beta bands) decompositions. In the broadband comparisons, the centro-posterior maximum microstate (map E) occurred significantly less frequently (d = -0.64, pFWE = 0.03) and had a significantly shorter mean duration in participants with PTSD as compared to controls (d = -0.71, pFWE < 0.01). These differences were reflected in the narrow frequency bands as well, with lower frequency bands like delta (d = -0.78, pFWE < 0.01), theta (d = -0.74, pFWE = 0.01), and alpha (d = -0.65, pFWE = 0.02) repeating these group-level trends, only with larger effect sizes. Interestingly, a support vector machine classification analysis comparing broadband and frequency-specific measures revealed that models containing only alpha band features significantly out-perform broadband models. When classifying PTSD, the classification accuracy was 76% and 65% for the alpha band and the broadband model, respectively (p = 0.03). Taken together, we provide original evidence supporting the clinical utility of microstates as diagnostic markers of PTSD and demonstrate that filtering EEG into distinct frequency bands significantly improves microstate-based classification of a psychiatric disorder.
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+microstate: A MATLAB toolbox for brain microstate analysis in sensor and cortical EEG/MEG
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  • May 2022
  • NEUROIMAGE
+microstate is a MATLAB toolbox for brain functional microstate analysis. It builds upon previous EEG microstate literature and toolboxes by including algorithms for source-space microstate analysis. +microstate includes codes for performing individual- and group-level brain microstate analysis in resting-state and task-based data including event-related potentials/fields. Functions are included to visualise and perform statistical analysis of microstate sequences, including novel advanced statistical approaches such as statistical testing for associated functional connectivity patterns, cluster-permutation topographic ANOVAs, and χ2 analysis of microstate probabilities in response to stimuli. Additionally, codes for simulating microstate sequences and their associated M/EEG data are included in the toolbox, which can be used to generate artificial data with ground truth microstates and to validate the methodology. +microstate integrates with widely used toolboxes for M/EEG processing including Fieldtrip, SPM, LORETA/sLORETA, EEGLAB, and Brainstorm to aid with accessibility, and includes wrappers for pre-existing toolboxes for brain-state estimation such as Hidden Markov modelling (HMM-MAR) and independent component analysis (FastICA) to aid with direct comparison with these techniques. In this paper, we first introduce +microstate before subsequently performing example analyses using open access datasets to demonstrate and validate the methodology. MATLAB live scripts for each of these analyses are included in +microstate, to act as a tutorial and to aid with reproduction of the results presented in this manuscript.
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Within and Between Subject Spectral Fingerprints of EEG-Microstate Parameters
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Early reports have claimed that EEG microstate features (e.g. their mean duration or percent of time covered) are largely independent from EEG spectra. This has meanwhile been questioned for conceptual and empirical reasons, but so far, EEG spectral power map correlates of microstate features have not been reported. We present the results of such analyses, conducted both within and between subjects, and report patterns of systematic changes in local EEG spectral amplitude associated with the mean duration, frequency of occurrence and relative contribution of particular microstate classes. The combination of EEG microstate analysis with spectral analysis may therefore be helpful to come to a deeper understanding of local patterns of activation and inhibition associated with particular microstate classes.
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Abnormalities in resting-state EEG microstates are a vulnerability marker of migraine
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Background Resting-state EEG microstates are thought to reflect brief activations of several interacting components of resting-state brain networks. Surprisingly, we still know little about the role of these microstates in migraine. In the present study, we attempted to address this issue by examining EEG microstates in patients with migraine without aura (MwoA) during the interictal period and comparing them with those of a group of healthy controls (HC). Methods Resting-state EEG was recorded in 61 MwoA patients (50 females) and 66 HC (50 females). Microstate parameters were compared between the two groups. We computed four widely identified canonical microstate classes A-D. Results Microstate classes B and D displayed higher time coverage and occurrence in the MwoA patient group than in the HC group, while microstate class C exhibited significantly lower time coverage and occurrence in the MwoA patient group. Meanwhile, the mean duration of microstate class C was significantly shorter in the MwoA patient group than in the HC group. Moreover, among the MwoA patient group, the duration of microstate class C correlated negatively with clinical measures of headache-related disability as assessed by the six-item Headache Impact Test (HIT-6). Finally, microstate syntax analysis showed significant differences in transition probabilities between the two groups, primarily involving microstate classes B, C, and D. Conclusions By exploring EEG microstate characteristics at baseline we were able to explore the neurobiological mechanisms underlying altered cortical excitability and aberrant sensory, affective, and cognitive processing, thus deepening our understanding of migraine pathophysiology.
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EEG microstate dynamics indicate a U-shaped path to propofol-induced loss of consciousness
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  • NEUROIMAGE
Evidence suggests that the stream of consciousness is parsed into transient brain states manifesting themselves as discrete spatiotemporal patterns of global neuronal activity. Electroencephalographical (EEG) microstates are proposed as the neurophysiological correlates of these transiently stable brain states that last for fractions of seconds. To further understand the link between EEG microstate dynamics and consciousness, we continuously recorded high-density EEG in 23 surgical patients from their awake state to unconsciousness, induced by step-wise increasing concentrations of the intravenous anesthetic propofol. Besides the conventional parameters of microstate dynamics, we introduce a new implementation of a method to estimate the complexity of microstate sequences. The brain activity under the surgical anesthesia showed a decreased sequence complexity of the stereotypical microstates, which became sparser and longer-lasting. However, we observed an initial increase in microstates’ temporal dynamics and complexity with increasing depth of sedation leading to a distinctive "U-shape" that may be linked to the paradoxical excitation induced by moderate levels of propofol. Our results support the idea that the brain is in a metastable state under normal conditions, balancing between order and chaos in order to flexibly switch from one state to another. The temporal dynamics of EEG microstates indicate changes of this critical balance between stability and transition that lead to altered states of consciousness.
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Beyond broadband: Towards a spectral decomposition of electroencephalography microstates
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Originally applied to alpha oscillations in the 1970s, microstate (MS) analysis has since been used to decompose mainly broadband electroencephalogram (EEG) signals (e.g., 1-40 Hz). We hypothesised that MS decomposition within separate, narrow frequency bands could provide more fine-grained information for capturing the spatio-temporal complexity of multichannel EEG. In this study, using a large open-access dataset (n = 203), we first filtered EEG recordings into four classical frequency bands (delta, theta, alpha and beta) and thereafter compared their individual MS segmentations using mutual information as well as traditional MS measures (e.g., mean duration and time coverage). Firstly, we confirmed that MS topographies were spatially equivalent across all frequencies, matching the canonical broadband maps (A, B, C, D and C'). Interestingly, however, we observed strong informational independence of MS temporal sequences between spectral bands, together with significant divergence in traditional MS measures. For example, relative to broadband, alpha/beta band dynamics displayed greater time coverage of maps A and B, while map D was more prevalent in delta/theta bands. Moreover, using a frequency-specific MS taxonomy (e.g., ϴA and αC), we were able to predict the eyes-open versus eyes-closed behavioural state significantly better using alpha-band MS features compared with broadband ones (80 vs. 73% accuracy). Overall, our findings demonstrate the value and validity of spectrally specific MS analyses, which may prove useful for identifying new neural mechanisms in fundamental research and/or for biomarker discovery in clinical populations.
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EEG microstates: Functional significance and short-term test-retest reliability
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  • Jun 2022
EEG microstates, reflecting discrete topographical organization of the EEG signal power, may have clinical relevance; however, their functional significance and test-retest reliability remain unclear. To investigate the functional significance of the canonical EEG microstate classes and their pairwise transitions, and to establish their within-session test-retest reliability, we recorded 36-channel EEGs in 20 healthy volunteers during three eyes-closed conditions: mind-wandering, verbalization (silently repeating the word ‘square’ every 2 s), and visualization (visualizing a square every 2 s). Each condition lasted 3 min and the sequence of three conditions was repeated four times (two runs of two sequence repetitions). The participants' alertness and their sense of effort during the experiment were rated using visual-analogue scales. The EEG data were 2–20 Hz bandpass-filtered and analysed into the four canonical microstate classes: A, B, C, and D. EEG microstate classes C and D were persistently more dominant than classes A and B in all conditions. Of the first-order microstate parameters, average microstate duration was most reliable. The duration of class D microstate was longer during mind-wandering (106.8 ms) than verbalization (102.2 ms) or visualization (99.8 ms), with a concomitantly higher coverage (36.4% vs. 34.7% and 35.2%), but otherwise there was no clear association of the four microstate classes to particular mental states. The test-retest reliability was higher at the beginning of each run, together with higher average alpha power and subjective ratings of alertness. Only the transitions between classes C and D (from C to D in particular) were significantly higher than what would be expected from the respective microstates' occurrences. The transition probabilities, however, did not distinguish between conditions, and their test-retest reliability was overall lower than that of the first-order parameters such as duration and coverage. Further studies are needed to establish the functional significance of the canonical EEG microstate classes. This might be more fruitfully achieved by looking at their complex syntax beyond pairwise transitions. To ensure greater test-retest reliability of microstate parameters, study designs should allow for shorter experimental runs with regular breaks, particularly when using EEG microstates as clinical biomarkers.
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Alterations in spontaneous electrical brain activity after an extreme mountain ultramarathon
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  • May 2022
  • BIOL PSYCHOL
This study aimed to investigate the impact of an extreme mountain ultramarathon (MUM) on spontaneous electrical brain activity in a group of 16 finishers. By using 4-minute high-density electroencephalographic (EEG) recordings with eyes closed before and after a 330-km race (mean duration: 125±17 hours; sleep duration: 7.7±2.9 hours), spectral power, source localization and microstate analyses were conducted. After the race, power analyses revealed a centrally localized increase in power in the delta (0.5-3.5 Hz) and theta (4.0-7.5 Hz) frequency bands and a decrease in alpha (8.0-12.0 Hz) power at the parieto-occipital sites. Higher brain activation in the alpha frequency band was observed within the left posterior cingulate cortex, left angular gyrus and visual association areas. Microstate analyses indicated a significant decrease in map C predominance and an increase in the global field power (GFP) for map D at the end of the race. These changes in power patterns and microstate parameters contrast with previously reported findings following short bouts of endurance exercises. We discuss the potential factors that explain lower alpha activity within the parieto-occipital regions and microstate changes after MUMs. In conclusion, high-density EEG resting-state analyses can be recommended to investigate brain adaptations in extreme sporting activities.
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Effect of Trait Anxiety on Cognitive Flexibility: Evidence from Event-related Potentials and Resting-state EEG
Article
  • Mar 2022
  • BIOL PSYCHOL
Individuals with anxiety often exhibit cognitive flexibility impairment; however, the neural underpinnings of this cognitive impairment remain unclear. In this study, 45 participants were instructed to complete a task-switching assessment of shifting function by EEG technology, and 200 participants were included in microstate analysis to study why cognitive flexibility is impaired and the neuromechanism. Behaviorally, a positive correlation between trait anxiety scores and set shifting cost was found. At the EEG level, there was a positive correlation between trait anxiety scores and frontal P2 peaks under the shifting condition, which was related to the activation of the stimulus–response associations by attention. Furthermore, microstate analysis was used to analyze EEG functional networks, and TA scores had significant positive correlations with the occurrence of class D and the contribution of class D, which was related to the dorsal attention network. These results provided direct neuroelectrophysiological evidence that trait anxiety impairs cognitive flexibility when shifting is required.
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