Normative Temporal Dynamics of Resting EEG Microstates.

The large-scale electrophysiological events known as electroencephalographic microstates provide an important window into the intrinsic activity of whole-brain neuronal networks. The spontaneous activity of coordinated brain networks, including the ongoing temporal dynamics expressed by microstates, are thought to reflect individuals' neurocognitive functioning, and predict development, disease progression, and psychological differences among varied populations. A comprehensive understanding of human brain function therefore requires characterizing typical and atypical patterns in the temporal dynamics of microstates. But population-level estimates of normative microstate temporal dynamics are still unknown. To address this gap, I conducted a systematic search of the literature and accompanying meta-analysis of the average dynamics of microstates obtained from studies investigating spontaneous brain activity in individuals during periods of eyes-closed and eyes-open rest. Meta-analyses provided estimates of the average temporal dynamics of microstates across 93 studies totaling 6583 unique individual participants drawn from diverse populations. Results quantified the expected range of plausible estimates of average microstate dynamics across study samples, as well as characterized heterogeneity resulting from sampling variability and systematic differences in development, clinical diagnoses, or other study methodological factors. Specifically, microstate dynamics significantly differed for samples with specific developmental differences or clinical diagnoses, relative to healthy, typically developing samples. This research supports the notion that microstates and their dynamics reflect functionally relevant properties of large-scale brain networks, encoding typical and atypical neurocognitive functioning.

EEG Microstates as Markers for Cognitive Impairments in Fragile X Syndrome.

Fragile X syndrome (FXS) is one of the most common inherited causes of intellectual disabilities. While there is currently no cure for FXS, EEG is considered an important method to investigate the pathophysiology and evaluate behavioral and cognitive treatments. We conducted EEG microstate analysis to investigate resting brain dynamics in FXS participants. Resting-state recordings from 70 FXS participants and 71 chronological age-matched typically developing control (TDC) participants were used to derive microstates via modified k-means clustering. The occurrence, mean global field power (GFP), and global explained variance (GEV) of microstate C were significantly higher in the FXS group compared to the TDC group. The mean GFP was significantly negatively correlated with non-verbal IQ (NVIQ) in the FXS group, where lower NVIQ scores were associated with greater GFP. In addition, the occurrence, mean duration, mean GFP, and GEV of microstate D were significantly greater in the FXS group than the TDC group. The mean GFP and occurrence of microstate D were also correlated with individual alpha frequencies in the FXS group, where lower IAF frequencies accompanied greater microstate GFP and occurrence. Alterations in microstates C and D may be related to the two well-established cognitive characteristics of FXS, intellectual disabilities and attention impairments, suggesting that microstate parameters could serve as markers to study cognitive impairments and evaluate treatment outcomes in this population. Slowing of the alpha peak frequency and its correlation to microstate D parameters may suggest changes in thalamocortical dynamics in FXS, which could be specifically related to attention control. (250 words).

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.

Online mindfulness training for older adults during the COVID-19 pandemic: a randomized controlled trial using a multi-method assessment approach.

OBJECTIVES: The COVID-19 pandemic drastically accelerated the need for studies examining the effectiveness of programs to bolster psychological well-being, particularly for at-risk groups, such as older adults (OAs). Mindfulness Training (MT) has been suggested as a well-suited program for this purpose. The present study examined the impact of a 4-week online, trainer-led MT course tailored for OAs during the early months of the COVID-19 pandemic. METHODS: Fifty-three OAs were randomly assigned to either Group A or Group B. Group A received the online MT course during the 4-week interval between the first (T1) and second (T2) testing sessions, while Group B received the same MT course during the interval between T2 and the third testing session (T3). The testing sessions included measures of mindfulness, emotional well-being, psychological health, and cognitive performance. In addition, a very brief survey was sent every week during the T1-T2 and T2-T3 intervals to assess weekly emotional well-being. RESULTS: The findings revealed that MT may improve some, albeit not all, aspects of mindfulness and well-being, while no significant results were noted for outcomes measuring psychological health and cognitive performance. CONCLUSIONS: These findings are discussed in the context of the evolving COVID-19 situation.

The role of affective interference and mnemonic load in the dynamic adjustment in working memory.

The amount of cognitive control required during a task may fluctuate over the course of performing a task. The dynamic upregulation of cognitive control has been proposed to occur in response to conflict or in response to the need for additional control during demanding cognitive tasks. Specifically, upregulation in cognitive control results in improved performance on trials that follow more demanding trials. Recent work has demonstrated that upregulation occurs during following trials with high (vs. low) mnemonic load and negative (vs. neutral) affective interference during working memory tasks. Although dynamic upregulation appears to be a robust phenomenon, less is known about individual difference factors that may alter the likelihood to engage in upregulation as a result of a signal to increase cognitive control. The current study attempted to replicate prior findings that suggest upregulation may occur following higher load trials or affective interference during a working memory task. Further, the study examined anxiety, depressive symptomatology, working memory capacity, mood, and dispositional mindfulness and possible moderators for upregulation of cognitive control. Participants (N = 150) completed a delayed recognition working memory task with mnemonic load (High vs. Low) and affective interference (Negative vs. Neutral) parametrically manipulated. Participants completed measures of the individual difference factors. The current findings replicate prior work demonstrating an upregulation of cognitive control following high load trials and negative affective interference. Individual difference factors did not moderate the upregulation findings, suggesting that upregulation is a robust phenomenon that can be triggered by both affective interference and mnemonic load.

EEG microstates suggest atypical resting-state network activity in high-functioning children and adolescents with autism spectrum development.

EEG microstates represent transient electrocortical events that reflect synchronized activities of large-scale networks, which allows investigations of brain dynamics with sub-second resolution. We recorded resting EEG from 38 children and adolescents with Autism Spectrum Development (ASD) and 48 age, IQ, sex, and handedness-matched typically developing (TD) participants. The EEG was segmented into a time series of microstates using modified k-means clustering of scalp voltage topographies. The frequency and global explained variance (GEV) of a specific microstate (type C) were significantly lower in the ASD group compared to the TD group while the duration of the same microstate was correlated with the presence of ASD-related behaviors. The duration of this microstate was also positively correlated with participant age in the TD group, but not in the ASD group. Further, the frequency and duration of the microstate were significantly correlated with the overall alpha power only in the TD group. The signal strength and GEV for another microstate (type G) was greater in the ASD group than the TD group, and the associated topographical pattern differed between groups with greater variations in the ASD group. While more work is needed to clarify the underlying neural sources, the existing literature supports associations between the two microstates and the default mode and salience networks. The current study suggests specific alterations of temporal dynamics of the resting cortical network activities as well as their developmental trajectories and relationships to alpha power, which has been proposed to reflect reduced neural inhibition in ASD.

Self-reported Mind Wandering and Response Time Variability Differentiate Prestimulus Electroencephalogram Microstate Dynamics during a Sustained Attention Task.

Brain activity continuously and spontaneously fluctuates during tasks of sustained attention. This spontaneous activity reflects the intrinsic dynamics of neurocognitive networks, which have been suggested to differentiate moments of externally directed task focus from episodes of mind wandering. However, the contribution of specific electrophysiological brain states and their millisecond dynamics to the experience of mind wandering is still unclear. In this study, we investigated the association between electroencephalogram microstate temporal dynamics and self-reported mind wandering. Thirty-six participants completed a sustained attention to response task in which they were asked to respond to frequently occurring upright faces (nontargets) and withhold responses to rare inverted faces (targets). Intermittently, experience sampling probes assessed whether participants were focused on the task or whether they were mind wandering (i.e., off-task). Broadband electroencephalography was recorded and segmented into a time series of brain electric microstates based on data-driven clustering of topographic voltage patterns. The strength, prevalence, and rate of occurrence of specific microstates differentiated on- versus off-task moments in the prestimulus epochs of trials preceding probes. Similar associations were also evident between microstates and variability in response times. Together, these findings demonstrate that distinct microstates and their millisecond dynamics are sensitive to the experience of mind wandering.

Meditation training modulates brain electric microstates and felt states of awareness.

Meditation practice is believed to foster states of mindful awareness and mental quiescence in everyday life. If so, then the cultivation of these qualities with training ought to leave its imprint on the activity of intrinsic functional brain networks. In an intensive longitudinal study, we investigated associations between meditation practitioners' experiences of felt mindful awareness and changes in the spontaneous electrophysiological dynamics of functional brain networks. Experienced meditators were randomly assigned to complete 3 months of full-time training in focused-attention meditation (during an initial intervention) or to serve as waiting-list controls and receive training second (during a later intervention). We collected broadband electroencephalogram (EEG) during rest at the beginning, middle, and end of the two training periods. Using a data-driven approach, we segmented the EEG into a time series of transient microstate intervals based on clustering of topographic voltage patterns. Participants also provided daily reports of felt mindful awareness and mental quiescence, and reported daily on four experiential qualities of their meditation practice during training. We found that meditation training led to increases in mindful qualities of awareness, which corroborate contemplative accounts of deepening mental calm and attentional focus. We also observed reductions in the strength and duration of EEG microstates across both interventions. Importantly, changes in the dynamic sequencing of microstates were associated with daily increases in felt attentiveness and serenity during training. Our results connect shifts in subjective qualities of meditative experience with the large-scale dynamics of whole brain functional EEG networks at rest.

Associations between self-reported spontaneous thought and temporal sequences of EEG microstates.

Thought dynamically evolves from one moment to the next even in the absence of external stimulation. The extent to which patterns of spontaneous thought covary with time-varying fluctuations in intrinsic brain activity is of great interest but remains unknown. We conducted novel analyses of data originally reported by Portnova et al. (2019) to examine associations between the intrinsic dynamics of EEG microstates and self-reported thought measured using the Amsterdam Resting-State Questionnaire (ARSQ). Accordingly, the millisecond fluctuations of microstates were associated with specific dimensions of thought. We evaluated the reliability of these findings by combining our results with those of another study using meta-analysis. Importantly, we extended this investigation using multivariate methods to evaluate multidimensional thought profiles of individuals and their links to sequences of successive microstates. Thought profiles were identified based on hierarchical clustering of ARSQ ratings and were distinguished in terms of the temporal ordering of successive microstates based on sequence analytic methods. These findings demonstrate the relevance of assessing spontaneous thought for understanding intrinsic brain activity and the novel use of sequence analysis for characterizing microstate dynamics. Integrating the phenomenological view from within remains crucial for understanding the functional significance of intrinsic large-scale neurodynamics.

Within and between-person correlates of the temporal dynamics of resting EEG microstates.

Microstates reflect transient brain states resulting from the synchronous activity of brain networks that predominate in the broadband EEG. There has been increasing interest in how the functional organization of the brain varies across individuals, or the extent to which its spatiotemporal dynamics are state dependent. However, little research has examined within and between-person correlates of microstate temporal parameters in healthy populations. In the present study, neuroelectric activity recorded during eyes-closed rest and during simple visual fixation was segmented into a time series of transient microstate intervals. It was found that five data-driven microstate configurations explained the preponderance of topographic variance in the EEG time series of the 374 recordings (from 187 participants) included in the study. We observed that the temporal dynamics of microstates varied within individuals to a greater degree than they differed between persons, with within-person factors explaining a large portion of the variance in mean microstate duration and occurrence rate. Nevertheless, several individual differences were found to predict the temporal dynamics of microstates. Of these, age and gender were the most reliable. These findings not only suggest that the rich temporal dynamics of whole-brain neuronal networks vary considerably within individuals, but that microstates appear to differentiate persons based on trait individual differences. Rather than focusing exclusively on between-person differences in microstates as measures of brain function, researchers should turn their attention towards understanding the factors contributing to within-person variation.

Deconstructing the effects of concentration meditation practice on interference control: The roles of controlled attention and inflammatory activity.

Prior work has linked meditation practice to improvements in interference control. However, the mechanisms underlying these improvements are relatively unknown. In the context of meditation training, improvements in interference control could result eitherfrom increases in controlled attention to goal-relevant stimuli, or from reductions in automatic capture by goal-irrelevant stimuli. Moreover, few studies have linked training-related changes in attention to physiological processes, such as inflammatory activity, that are thought to influence cognitive function. This study addresses these gaps by examining associations between cognitive performance and cytokines in the context of an intensive meditation retreat. Participants were randomly assigned to complete 3 months of meditation training first, or to serve as waitlist controls. The waitlist-control participants then later completed a separate 3-month training intervention. We assessed participants' interference control with a flanker task and used computational modeling to derive component processes of controlled and automatic attention. We also collected blood samples at the beginning, middle, and end of training to quantify changes in cytokine activity. Participants who completed training evidenced better controlled attention than waitlist controls during the first retreat intervention, and controls showed significant improvements in controlled attention when they completed their own, second retreat. Importantly, inflammatory activity was inversely associated with controlled attention during both interventions. Our results suggest that practice of concentration meditation influences interference control by enhancing controlled attention to goal-relevant task elements, and that inflammatory activity relates to individual differences in controlled attention.

EEG Electric Field Topography is Stable During Moments of High Field Strength.

Spontaneous broadband electroencephalography (EEG) demonstrates short moments of stability in the spatial distribution of the head-surface voltage topography. This phenomenon underlies the premise behind segmenting multichannel EEG into topographically defined brain states, known as EEG microstates. Microstate segmentation methods commonly identify representative topographical configurations based on clustering applied to a subset of voltage maps selected at the time series points of greatest strength in the neuroelectric field. These moments are well-reasoned to best represent periods of momentary stability in the voltage topography, and consequently, points of greatest signal relative to noise. Yet, more direct empirical evidence for these assumptions is warranted, and the consistency of this phenomenon across individuals has not been characterized. In the present investigation, the association between electric field strength and topographic dissimilarity of temporally adjacent samples of EEG were characterized in a large sample of healthy adults engaged in quiet rest. Samples of individuals' EEG time series high in electric field strength were found to be topographically similar relative to adjacent time series samples. The strong phase-synchronized actvity of neuronal populations therefore coincides with momentary stability in the topographic voltage configuration, providing robust empirical support for the basic premise underlying segmentation of broadband EEG into microstates.

Quantifying streams of thought during cognitive task performance using sequence analysis.

Streams of thought vary in content from one moment to the next, and these temporal patterns have been argued to be critical to understanding the wandering mind. But few analytic methods have been proposed that can account for both the content and temporal ordering of categorical experience sampling thought probes over time. In the present study, I apply sequence analytic methods to quantify the dynamics of thought from time series sequences of categorical experience sampling thought probes delivered across five different cognitive tasks in the same individuals (N = 545). Analyses revealed some patterns of consistency in streams of thought within individuals, but also demonstrated considerable variability within and between task sessions. Hierarchical clustering of sequence dissimilarities further revealed common typologies of mind wandering across individuals. These findings demonstrate the application of sequence analytic methods for quantifying the dynamics of thought over the course of task performance and show that contextual task constraints are associated with how streams of thought unfold over time. More broadly, sequence analysis provides a valuable framework for investigation of time ordered cognitive and behavioral processes across psychological domains.

Modulation of Event-related Potentials of Visual Discrimination by Meditation Training and Sustained Attention.

The ability to discriminate among goal-relevant stimuli tends to diminish when detections must be made continuously over time. Previously, we reported that intensive training in shamatha (focused-attention) meditation can improve perceptual discrimination of difficult-to-detect visual stimuli [MacLean, K. A., Ferrer, E., Aichele, S. R., Bridwell, D. A., Zanesco, A. P., Jacobs, T. L., et al. Intensive meditation training improves perceptual discrimination and sustained attention. Psychological Science, 21, 829-839, 2010]. Here we extend these findings to examine how discrimination difficulty and meditation training interact to modulate event-related potentials of attention and perceptual processing during vigilance. Training and wait-list participants completed a continuous performance task at the beginning, middle, and end of two 3-month meditation interventions. In the first intervention (Retreat 1), the continuous performance task target was adjusted across assessments to match training-related changes in participants' perceptual capacity. In the second intervention (Retreat 2), the target was held constant across training, irrespective of changes in discrimination capacity. No training effects were observed in Retreat 1, whereas Retreat 2 was associated with changes in the onset of early sensory signals and an attenuation of within-task decrements at early latencies. In addition, changes at later stimulus processing stages were directly correlated with improvements in perceptual threshold across the second intervention. Overall, these findings demonstrate that improvements in perceptual discrimination can modulate electrophysiological markers of perceptual processing and attentional control during sustained attention, but likely only under conditions where an individual's discrimination capacity is allowed to exceed the demand imposed by the difficulty of a visual target. These results contribute to basic understanding of the dependence of perceptual processing and attentional control to contextual demands and their susceptibility to directed mental training.

Insight meditation and telomere biology: The effects of intensive retreat and the moderating role of personality.

A growing body of evidence suggests that meditation training may have a range of salubrious effects, including improved telomere regulation. Telomeres and the enzyme telomerase interact with a variety of molecular components to regulate cell-cycle signaling cascades, and are implicated in pathways linking psychological stress to disease. We investigated the effects of intensive meditation practice on these biomarkers by measuring changes in telomere length (TL), telomerase activity (TA), and telomere-related gene (TRG) expression during a 1-month residential Insight meditation retreat. Multilevel analyses revealed an apparent TL increase in the retreat group, compared to a group of experienced meditators, similarly comprised in age and gender, who were not on retreat. Moreover, personality traits predicted changes in TL, such that retreat participants highest in neuroticism and lowest in agreeableness demonstrated the greatest increases in TL. Changes observed in TRGs further suggest retreat-related improvements in telomere maintenance, including increases in Gar1 and HnRNPA1, which encode proteins that bind telomerase RNA and telomeric DNA. Although no group-level changes were observed in TA, retreat participants' TA levels at post-assessment were inversely related to several indices of retreat engagement and prior meditation experience. Neuroticism also predicted variation in TA across retreat. These findings suggest that meditation training in a retreat setting may have positive effects on telomere regulation, which are moderated by individual differences in personality and meditation experience. (ClinicalTrials.gov #NCT03056105).

The effect of movement-focused and breath-focused yoga practice on stress parameters and sustained attention: A randomized controlled pilot study.

Yoga-based practices (YBP) typically involve a combination of movement sequences, conscious regulation of the breath, and techniques to engage attention. However, little is known about whether effects of YBP result from the synergistic combination of these components, or whether a subset may yield similar effects. In this study we compared the effect of a movement-focused practice and a breath-focused practice on stress parameters (perceived stress and salivary cortisol) and sustained attention (response inhibition) in yoga naïve university students. While participants of both programs showed a reduction in perceived stress and salivary cortisol, only the breath-focused group showed improvements in sustained attention. In addition, improvement in sustained attention was correlated with reduction in perceived stress but not with reduction in salivary cortisol. We discuss these findings in the context of a theoretical framework outlining bottom-up neurophysiological and top-down neurocognitive mechanisms hypothesized to be engaged by YBP.

Mean-field thalamocortical modeling of longitudinal EEG acquired during intensive meditation training.

Meditation training has been shown to enhance attention and improve emotion regulation. However, the brain processes associated with such training are poorly understood and a computational modeling framework is lacking. Modeling approaches that can realistically simulate neurophysiological data while conforming to basic anatomical and physiological constraints can provide a unique opportunity to generate concrete and testable hypotheses about the mechanisms supporting complex cognitive tasks such as meditation. Here we applied the mean-field computational modeling approach using the scalp-recorded electroencephalogram (EEG) collected at three assessment points from meditating participants during two separate 3-month-long shamatha meditation retreats. We modeled cortical, corticothalamic, and intrathalamic interactions to generate a simulation of EEG signals recorded across the scalp. We also present two novel extensions to the mean-field approach that allow for: (a) non-parametric analysis of changes in model parameter values across all channels and assessments; and (b) examination of variation in modeled thalamic reticular nucleus (TRN) connectivity over the retreat period. After successfully fitting whole-brain EEG data across three assessment points within each retreat, two model parameters were found to replicably change across both meditation retreats. First, after training, we observed an increased temporal delay between modeled cortical and thalamic cells. This increase provides a putative neural mechanism for a previously observed reduction in individual alpha frequency in these same participants. Second, we found decreased inhibitory connection strength between the TRN and secondary relay nuclei (SRN) of the modeled thalamus after training. This reduction in inhibitory strength was found to be associated with increased dynamical stability of the model. Altogether, this paper presents the first computational approach, taking core aspects of physiology and anatomy into account, to formally model brain processes associated with intensive meditation training. The observed changes in model parameters inform theoretical accounts of attention training through meditation, and may motivate future study on the use of meditation in a variety of clinical populations.

Mind-wandering increases in frequency over time during task performance: An individual-participant meta-analytic review.

Attention has a seemingly inevitable tendency to turn inward toward our thoughts. Mind-wandering refers to moments when this inward focus diverts attention away from the current task-at-hand. Mind-wandering is thought to be ubiquitous, having been estimated to occur between 30% and 50% of our waking moments. Yet, it is unclear whether this frequency is similar within-task performance contexts and unknown whether mind-wandering systematically increases with time-on-task for a broad range of tasks. We conducted a systematic literature search and individual participant data meta-analysis of rates of occurrence of mind-wandering during task performance. Our search located 68 research reports providing almost a half-million total responses to experience sampling mind-wandering probes from more than 10,000 unique individuals. Latent growth curve models estimated the initial occurrence of mind-wandering and linear change in mind-wandering over sequential probes for each study sample, and effects were summarized using multivariate meta-analysis. Our results confirm that mind-wandering increases in frequency over time during task performance, implicating mind-wandering in characteristic within-task psychological changes, such as increasing boredom and patterns of worsening behavioral performance with time-on-task. The systematic search and meta-analysis provide the most comprehensive assessment of normative rates of mind-wandering during task performance reported to date. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Changes in peripheral oxytocin and vasopressin during a silent month-long Insight meditation retreat.

Background: Given its putative roles in mediating prosocial behavior, attachment bonds, and stress physiology, oxytocin modulation has been hypothesized to be a biological correlate of the salubrious effects of meditation practice. Here we investigated the effects of a month-long silent meditation retreat on changes in oxytocin, and the related hormone and vasopressin, in relation to psychosocial changes in attachment style, anxiety, personality measures, and feelings of social connectedness with fellow meditators. Methods: Plasma oxytocin and vasopressin and self-report questionnaires were measured in retreat participants (n = 28) at the beginning of, and 3 weeks into, a residential meditation retreat. Control participants (n = 34), who were similar in age, gender, and meditation experience, were also assessed across a 3-week interval. Linear mixed effects models were used to assess outcomes. Results: The retreat group showed a small but significant decrease in oxytocin compared to controls who showed no change. In the retreat group, higher openness to experience at Time 1 predicted greater reductions in oxytocin during the retreat, and lower oxytocin at Time 2 was related to stronger feelings of personal connection with fellow meditators. The changes in oxytocin were not related to attachment style or anxiety. Vasopressin decreased over time across both groups, suggesting no specific effect of retreat. Conclusion: These preliminary findings suggest that meditation training in the context of a silent residential retreat may reduce circulating levels of oxytocin. We interpret this finding from multiple theoretical perspectives, discussing key measurement limitations and proposing future study designs that may help to differentiate the effects of different meditation practices and contexts on oxytocin signaling.