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.

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).

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.

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).

Cultivating concern for others: Meditation training and motivated engagement with human suffering.

Contemplative traditions have long affirmed that compassion and kindness are trainable skills. While research on meditation practice has recently flourished, the mechanisms that might engender such changes are still poorly understood. Here, we present a motivational framework to explain why meditation training should increase concern for others and modulate empathic engagement with human suffering over time. Meditation practices are conceived as tools for enacting cognitive and emotion regulatory goals that are conditioned by the underlying ethical motivation of the training-to reduce and alleviate suffering. In support of this account, we present data from a randomized, wait-list-controlled study of intensive meditation. In Study 1, we use a novel cardiovascular index to show that 3 months of meditation training can increase the motivational salience of others' suffering, as compared to the salience of threats to oneself. In Study 2, we demonstrate that training-related changes in the ability to orient attention to suffering are mediated by the dynamic regulation of distress-related physiological arousal. Finally, in Study 3, we provide exploratory evidence suggesting that meditation training may influence how human suffering is encoded in memory, leaving lasting imprints on the recollection of emotional experience. Together, our findings suggest that meditation training can strengthen the motivational relevance of others' suffering, prompting a shift from self-focused to other-focused evaluative processing. Considering meditation training from a motivational standpoint offers an important perspective for understanding how compassion can be cultivated through intentional practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

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.

Investigating the protective effects of mindfulness-based attention training on mind wandering in applied settings.

Introduction: Mind wandering, a phenomenon in which attention drifts away from the task-at-hand, is associated with deleterious effects on performance and well-being. As such, efforts to curb mind wandering are warranted. Recently, mindfulness training (MT) has been found to protect against mind wandering. Yet, many MT programs are at risk of falling off the implementation cliff due to challenges implementing these programs in applied settings. To mitigate against this, early-stage research in small convenience samples may be necessary to spur stakeholder engagement and collaboration. Herein, the effects of MT on mind wandering were examined via an internal meta-analysis of early-stage studies of a manualized, context-adaptable short-form MT program, referred to as Mindfulness-Based Attention Training (MBAT). Methods: Five longitudinal studies (N = 304) were conducted in a variety of organizational cohorts. Self-reported mind wandering and meta-awareness, as well as accuracy (A') and response time variability (intra-individual coefficient of variation, ICV) during performance of the sustained attention to response task (SART) were assessed at baseline (T1) and 4 weeks later (T2) in MBAT and no-training participants. Results: Standardized mean change (SMC) from T1 to T2 significantly differed between MBAT and no-training groups for mind wandering (ΔSMC = -0.387, p < 0.001), meta-awareness (ΔSMC = -0.374, p < 0.001), and ICV (ΔSMC = -0.376, p = 0.043), suggesting potential protective effects in self-reported and performance-based metrics of mind wandering. Discussion: These results serve as preliminary proof-of-concept support for MBAT's protective effects on mind wandering. Further, they suggest that MBAT is amenable to implementation across a variety of applied and organizational settings and warrants additional research employing larger sample sizes in randomized controlled designs.

Shifting Baselines: Longitudinal Reductions in EEG Beta Band Power Characterize Resting Brain Activity with Intensive Meditation.

Objectives: A core assumption of meditation training is that cognitive capacities developed during formal practice will transfer to other contexts or activities as expertise develops over time. This implies that meditation training might influence domain-general neurocognitive systems, the spontaneous activity of which should be reflected in the dynamics of the resting brain. Previous research has demonstrated that 3 months of meditation training led to reductions in EEG beta band power during mindfulness of breathing practice. The current study extends these findings to ask whether concomitant shifts in power are observed during 2 min of eyes closed rest, when participants are not explicitly engaged in formal meditation. Methods: Experienced meditation practitioners were randomly assigned to practice 3 months of focused attention meditation in a residential retreat, or to serve as waitlist controls. The waitlist controls later completed their own 3-month retreat. Permutation-based cluster analysis of 88-channel resting EEG data was used to test for spectral changes in spontaneous brain activity over the course of the retreats. Results: Longitudinal reductions in EEG power in the beta frequency range were identified and replicated across the two independent training periods. Less robust reductions were also observed in the high alpha frequency range, and in individual peak alpha frequency. These changes closely mirror those previously observed during formal mindfulness of breathing meditation practice. Conclusions: These findings suggest that the neurocognitive effects of meditation training can extend beyond the bounds of formal practice, influencing the spontaneous activity of the resting brain. Rather than serving as an invariant baseline, resting states might carry meaningful training-related effects, blurring the line between state and trait change. Supplementary Information: The online version contains supplementary material available at 10.1007/s12671-022-01974-9.

Changes in the expression of inflammatory and epigenetic-modulatory genes after an intensive meditation retreat.

Background: Meditation retreats are characterized by intensive or concentrated periods of meditation practice, commonly undertaken in a residential setting. Although research indicates that meditation training can positively influence physical and mental health outcomes, the biological consequences of meditation retreat interventions are relatively understudied. In this study, we examined the influence of a month-long, silent meditation retreat on the expression of genes involved in epigenetic modulation and immune processes. Method: We assessed gene expression changes in experienced meditators attending a month-long Insight meditation retreat (n = 28), as compared to a community control group (n = 34) of experienced practitioners living their everyday lives. Blood samples were collected on day two of the retreat (Time 1) and again 3 weeks later (Time 2). Control participants were also assessed across a 3-week interval, during which they maintained their regular daily routines. Results: As compared to controls, retreat participants showed differential changes in the expression of several genes involved in chromatin modulation and inflammation. The most substantive finding was downregulation of the TNF pathway in retreat participants, which was not observed in controls. Conclusions: These findings indicate that meditation retreat participation may influence some of the inflammatory mechanisms involved in the development of chronic diseases, and that this style of psychosocial intervention may have therapeutic potential, particularly in experienced practitioners.

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.

Higher self-reported posttraumatic stress symptoms are associated with poorer working memory in active-duty service members.

OBJECTIVE: Posttraumatic stress is a significant issue facing military service members and can negatively impact working memory (WM), which is critical for performance success. Yet, few studies have examined the link between self-reported posttraumatic stress symptoms (PTSS) and WM performance in active-duty military cohorts. The present study utilized hierarchical linear modeling to examine this relationship by considering PTSS and underlying symptom clusters as well as WM demands related to load and affective interference in an active-duty military cohort (N = 515). METHOD: PTSS severity was assessed via the posttraumatic stress disorder checklist-military version (PCL-M), and behavioral performance was measured on a delayed-recognition WM task that manipulated mnemonic load (low vs. high load) and affective interference (negative combat-related vs. neutral civilian images presented during the delay interval). RESULTS: Examination of the relationship between PCL-M and WM performance demonstrated that higher total PCL-M scores (especially higher numbing and hyperarousal symptoms) were associated with poorer WM task performance, b = -0.083, p = .003, 95% CI [-0.137, -0.029], even after controlling for combat experiences and previous deployment status. This relationship was stronger on trials with negative, b = -0.114, p < .001, 95% CI [-0.175, -0.054], compared to neutral distracters, b = -0.052, p = .093, 95% CI [-0.112, 0.009]. CONCLUSIONS: These results suggest that PTSS are associated with performance costs on a WM task with combat-related negative distracters. Broadly, these findings highlight the need to address PTSS in active-duty cohorts and further investigate vulnerabilities related to cognitive demands and psychological health. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

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.

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.

Experience sampling of the degree of mind wandering distinguishes hidden attentional states.

Experience sampling of attentional states has consistently demonstrated that mind wandering is a frequent and disruptive obstacle when one must sustain attention during continuous task performance. Yet, methods commonly used to assess the subjective experience of mind wandering may conflate several potential sources of meaningful variation in individuals' degree of task engagement. In the present study, we examined evidence for distinct and identifiable patterns in subjective reports of the degree of task-related attentional focus during a sustained attention task in a large sample of adults (N = 537). Experience sampling probes embedded in the task assessed task-related focus using a continuum of response ratings ranging from 1 (on-task) to 6 (off-task). Participants used a range of probe response options in categorizing their current attentional state, and the continuum of probe ratings differentiated patterns of behavioral performance in the moments preceding probes. Markov-chain modeling of the categorical time series sequence of probe ratings further revealed distinct and behaviorally relevant hidden states underlying probe rating behavior. We replicated these findings in two additional independent data sets. Collectively, these findings suggest that three or more hidden attentional states best account for subjective ratings of task-related focus. The implications of these findings for models of sustained attention and mind wandering are discussed.

Memory load, distracter interference, and dynamic adjustments in cognitive control influence working memory performance across the lifespan.

Capacity-limited working memory (WM) systems have been known to degrade in older age. In line with inhibition-deficit theories of aging, WM deficits in older individuals have been attributed to failures in the ability to suppress the processing of task irrelevant, distracting information. Yet, other cognitive mechanisms underlying age-related WM deficits have been observed, including failures in WM with increasing memory load. Moreover, both distracting information and high memory load have been shown to trigger adjustments in cognitive control leading to subsequent performance benefits on later trials. However, no studies have characterized these dynamic adjustments across the life span or examined their contribution to WM deficits in older adults. We investigated the contribution of distracter interference, memory load, and dynamic adjustments in cognitive control on WM performance in 505 individuals with ages ranging from adolescence to older adulthood. Distracter interference and memory load were parametrically manipulated (high vs. low) in a delayed-recognition WM task, and accuracy was examined as a function of current (N) and previous (N-1) trial demands. Curvilinear models revealed that performance differs over the life span depending on specific WM task demands. Specifically, the ability to suppress task irrelevant distracters was greater in adulthood compared with adolescence, but worse in later life. In contrast, memory load resulted in performance deficits with increasing age, which were exacerbated when high load and interference demands combined. Dynamic adjustments in cognitive control was spared, in part, with memory-load triggered sequential trial effects maintained across the life span, but interference-triggered benefits observable up to middle age. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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.