EEG-Meta-Microstates: Towards a More Objective Use of Resting-State EEG Microstate Findings Across Studies.

Over the last decade, EEG resting-state microstate analysis has evolved from a niche existence to a widely used and well-accepted methodology. The rapidly increasing body of empirical findings started to yield overarching patterns of associations of biological and psychological states and traits with specific microstate classes. However, currently, this cross-referencing among apparently similar microstate classes of different studies is typically done by "eyeballing" of printed template maps by the individual authors, lacking a systematic procedure. To improve the reliability and validity of future findings, we present a tool to systematically collect the actual data of template maps from as many published studies as possible and present them in their entirety as a matrix of spatial similarity. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps from ongoing or published studies. The tool also allows importing novel template maps and systematically extracting the findings associated with specific microstate maps in the literature. The analysis of 40 included sets of template maps indicated that: (i) there is a high degree of similarity of template maps across studies, (ii) similar template maps were associated with converging empirical findings, and (iii) representative meta-microstates can be extracted from the individual studies. We hope that this tool will be useful in coming to a more comprehensive, objective, and overarching representation of microstate findings

Smegenų ramybės būsenos įvertinimas: ryšys su subjektyviais potyriais

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. However, the relationship between the ongoing experience of mind wandering and the individual biological signal is still unclear. To quantify subjects' subjective experiences at rest, the Amsterdam Resting-State Questionnaire (ARSQ) was introduced covering several dimensions of mind wandering. The aim of this work was to estimate associations between subjective experiences during the resting state session and electrical brain’s signal, focusing on EEG power, phase synchronization and topographical aspects. As it was showed in this work, different aspects of the same signal are related to both - different and the same - domains of ARSQ. Power aspect of EEG signal as evaluated with frequency principal component analysis showed that activity in theta frequency range was related to scores for Sleepiness, but not the phase, as evaluated with global field synchronization. On the other hand, phase synchronization of of beta frequency range, but not the power aspect correlated with domain of Comfort. And both, power and phase parameters of alpha band activity correlated with ARSQ domain of Comfort. Three different microstates – C, E and G – displayed associations with domain of Comfort, while microstate B and D correlated with domain of Self and microstate F correlated with Somatic Awareness

Relationship between Spatiotemporal Dynamics of the Brain at Rest and Self-Reported Spontaneous Thoughts: An EEG Microstate Approach.

RATIONALE The resting-state paradigm is frequently applied in electroencephalography (EEG) research; however, it is associated with the inability to control participants' thoughts. To quantify subjects' subjective experiences at rest, the Amsterdam Resting-State Questionnaire (ARSQ) was introduced covering ten dimensions of mind wandering. We aimed to estimate associations between subjective experiences and resting-state microstates of EEG. METHODS 5 min resting-state EEG data of 197 subjects was used to evaluate temporal properties of seven microstate classes. Bayesian correlation approach was implemented to assess associations between ARSQ domains assessed after resting and parameters of microstates. RESULTS Several associations between Comfort, Self and Somatic Awareness domains and temporal properties of neuroelectric microstates were revealed. The positive correlation between Comfort and duration of microstates E showed the strongest evidence (BF10 > 10); remaining correlations showed substantial evidence (10 > BF10 > 3). CONCLUSION Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the intrinsic brain activity reflected in microstates

The functional aspects of resting EEG microstates: A Systematic Review

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

Internet Usage Habits and Experienced Levels of Psychopathology: A Pilot Study on Association with Spontaneous Eye Blinking Rate

Increasing availability of the internet has resulted in the increased prevalence of problematic online behaviors. Reliable and affordable neurobiological and psychological biomarkers that distinguish problematic internet use (PIU) from functional online activities are of utmost importance. Previous studies have shown a relationship between spontaneous eye blinking rate (sEBR) and changes in dopamine regulation in neurological and psychiatric disorders, including substance use disorders. In this study, we utilized sEBR to examine the potential link between individual differences in dopaminergic neurotransmission and PIU. In sum, 62 subjects participated in this study (median age 25, IQR 6 years, 34 females). The Problematic Internet Use Questionnaire (PIUQ-9), Beck Depression Inventory (BDI-II), Beck Anxiety Inventory (BAI), Clark–Beck Obsessive–Compulsive Inventory (CBOCI) and Barratt Impulsiveness Scale (BIS-11) were used for psychological assessment. The sEBRs were assessed with an electrooculogram recorded from above and below the left eye and from the right and left outer canthi. The group with PIU (PIUQ-9 > 20) expressed higher levels of impulsivity and compulsive behavior symptoms than the control group. In the group with PIU, impulsivity levels were inversely related to sEBR, and a trend of negative association of sEBR with compulsive behavior was observed. Future research should enroll subjects with high levels of PIU and strongly expressed psychopathology levels to further address the utility of sEBR as a potential biomarker

Data-Driven EEG Theta and Alpha Components Are Associated with Subjective Experience during Resting State

The resting-state paradigm is frequently applied to study spontaneous activity of the brain in normal and clinical conditions. However, the relationship between the ongoing experience of mind wandering and the individual biological signal is still unclear. We aim to estimate associations between subjective experiences measured with the Amsterdam Resting-State Questionnaire and data-driven components of an electroencephalogram extracted by frequency principal component analysis (f-PCA). Five minutes of resting multichannel EEG was recorded in 226 participants and six EEG data-driven components were extracted—three components in the alpha range (peaking at 9, 10.5, and 11.5 Hz) and one each in the delta (peaking at 0.5 Hz), theta (peaking at 5.5 Hz) and beta (peaking at 17 Hz) ranges. Bayesian Pearson’s correlation revealed a positive association between the individual loadings of the theta component and ratings for Sleepiness (r = 0.200, BF10 = 7.676), while the individual loadings on one of the alpha components correlated positively with scores for Comfort (r = 0.198, BF10 = 7.115). Our study indicates the relevance of assessments of spontaneous thought occurring during the resting-state for the understanding of the individual intrinsic electrical brain activity

40-Hz auditory steady-state responses and the complex information processing: an exploratory study in healthy young males

Electroencephalographic (EEG) activity in the gamma (30–80 Hz) range is related to a variety of sensory and cognitive processes which are frequently impaired in schizophrenia. Auditory steady-state response at 40-Hz (40-Hz ASSR) is utilized as an index of gamma activity and is proposed as a biomarker of schizophrenia. Nevertheless, the link between ASSRs and cognitive functions is not clear. This study explores a possible relationship between the performance on cognitive tasks and the 40-Hz ASSRs in a controlled uniform sample of young healthy males, as age and sex may have complex influence on ASSRs. Twenty-eight young healthy male volunteers participated (mean age ± SD 25.8±3.3) in the study. The 40-Hz click trains (500 ms) were presented 150 times with an inter-stimulus interval set at 700–1000 ms. The phase-locking index (PLI) and event-related power perturbation (ERSP) of the ASSR were calculated in the 200–500 ms latency range, which corresponds to the steady part of the response. The Psychology Experiment Building Language (PEBL) task battery was used to assess five cognitive subdomains: the Choice response time task, the Stroop test, the Tower of London test, the Lexical decision task and the Semantic categorisation task. Pearson‘s correlation coefficients were calculated to access the relationships; no multiple-test correction was applied as the tests were explorative in nature. A significant positive correlation was observed for the late-latency gamma and the mean number of steps in the Tower of London task reflecting planning and problem-solving abilities. These findings support the concept that 40-Hz ASSR might highlight top-down mechanisms which are related to cognitive functioning. Therefore, 40-Hz ASSRs can be used to explore the relationship between cognitive functioning and neurophysiological indices of brain activity

EEG connectivity during active emotional musical performance

The neural correlates of intentional emotion transfer by the music performer are not well investigated as the present-day research mainly focuses on the assessment of emotions evoked by music. In this study, we aim to determine whether EEG connectivity patterns can reflect differences in information exchange during emotional playing. The EEG data were recorded while subjects were performing a simple piano score with contrasting emotional intentions and evaluated the subjectively experienced success of emotion transfer. The brain connectivity patterns were assessed from the EEG data using the Granger Causality approach. The effective connectivity was analyzed in different frequency bands—delta, theta, alpha, beta, and gamma. The features that (1) were able to discriminate between the neutral baseline and the emotional playing and (2) were shared across conditions, were used for further comparison. The low frequency bands—delta, theta, alpha—showed a limited number of connections (4 to 6) contributing to the discrimination between the emotional playing conditions. In contrast, a dense pattern of connections between regions that was able to discriminate between conditions (30 to 38) was observed in beta and gamma frequency ranges. The current study demonstrates that EEG-based connectivity in beta and gamma frequency ranges can effectively reflect the state of the networks involved in the emotional transfer through musical performance, whereas utility of the low frequency bands (delta, theta, alpha) remains questionable