Mindfulness meditators show altered distributions of early and late neural activity markers of attention in a response inhibition task

Athletes with meditation experience counteract the detrimental effect of mental fatigue on endurance performance and neurocognitive functions

The current study examined whether meditation experience is associated with changes in endurance performance and inhibitory control-relevant neurocognitive functions caused by mental fatigue. Twenty-four athletes with meditation experience (AME) and twenty-five athletes without meditation experience (AWME) underwent a 30-min incongruent Stroop test in mental fatigue condition (MF) and a 30-min congruent Stroop test in control condition (CON) in a randomised-counterbalanced order. Inhibitory control-relevant neurocognitive functions were assessed using Flanker task and event-related potentials, followed by an endurance task using the Bruce treadmill protocol. Visual analogue scale was used to evaluate perceived mental fatigue (VAS-MF) before (T1), after Stroop test (T2) and after Flanker task (T3), and VAS for motivation (VAS-M) was used to evaluate motivation in Flanker task and endurance task. Results indicated that, compared to the CON, AWME in the MF exhibited overall lower accuracy, smaller incongruent N2 amplitude of the Flanker task (ps < .05), and shorter time to exhaustion (TTE) of the endurance task (p < .001), whereas AME did not exhibited difference in these outcomes between the conditions. Along with athletes in the MF reported lower VAS-M in endurance task. These findings suggest the benefits of meditation experience in mitigating the negative effects of mental fatigue.

Parsing state mindfulness effects on neurobehavioral markers of cognitive control: A within-subject comparison of focused attention and open monitoring

Over the past two decades, scientific interest in understanding the relationship between mindfulness and cognition has accelerated. However, despite considerable investigative efforts, pervasive methodological inconsistencies within the literature preclude a thorough understanding of whether or how mindfulness influences core cognitive functions. The purpose of the current study is to provide an initial "proof-of-concept" demonstration of a new research strategy and methodological approach designed to address previous limitations. Specifically, we implemented a novel fully within-subject state induction protocol to elucidate the neurobehavioral influence of discrete mindfulness states-focused attention (FA) and open monitoring (OM), compared against an active control-on well-established behavioral and ERP indices of executive attention and error monitoring assessed during the Eriksen flanker task. Bayesian mixed modeling was used to test preregistered hypotheses pertaining to FA and OM effects on flanker interference, the stimulus-locked P3, and the response-locked ERN and Pe. Results yielded strong but unexpected evidence that OM selectively produced a more cautious and intentional response style, characterized by higher accuracy, slower RTs, and reduced P3 amplitude. Follow-up exploratory analyses revealed that trait mindfulness moderated the influence of OM, such that individuals with greater trait mindfulness responded more cautiously and exhibited higher trial accuracy and smaller P3s. Neither FA nor OM modulated the ERN or Pe. Taken together, our findings support the promise of our approach, demonstrating that theoretically distinct mindfulness states are functionally dissociable among mindfulness-naive participants and that interactive variability associated with different operational facets of mindfulness (i.e., state vs. trait) can be modeled directly.

Differences in attentional function between experienced mindfulness meditators and non-meditators

Introduction

Attentional enhancement has often been identified as the central cognitive mechanism underlying the benefits of mindfulness meditation. However, the extent to which this enhancement is observable in the neural processes underlying long-term meditation is unclear. This current study aimed to examine differences in attentional performance between meditators and controls (non-meditators) using a visual oddball task with concurrent electroencephalography (EEG) recordings.

Methods

Thirty-four participants were recruited, including 16 meditators and 18 healthy controls, who were non-meditators. The participants completed a visual oddball task, using visual stimuli, and EEG recording.

Results

Self-reports revealed that meditators had higher mindful attention scores than did the control group. The behavioral results showed that the meditators demonstrated faster reaction times than the non-meditators did. Neural findings indicated a higher P2 amplitude in the meditators than in the controls. The meditators demonstrated a significantly higher P3 in the target trials than in the distractor trials, which was not observed in the controls. Additionally, the time-frequency analysis demonstrated that the delta and theta powers in the meditators were significantly higher than those in the controls.

Conclusions

The study suggests the meditators exhibited greater attentional performance than the controls did, as revealed by EEG and behavioral measures. This study extends previous research on the effects of mindfulness meditation on attention and adds to our understanding of the effects of long-term mindfulness meditation.

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

A meta-analytical review of the impact of mindfulness on creativity: Framing current lines of research and defining moderator variables

Findings relating to the impact of mindfulness interventions on creative performance remain inconsistent, perhaps because of discrepancies between study designs, including variability in the length of mindfulness interventions, the absence of control groups or the tendencies to explore creativity as one unitary construct. To derive a clearer understanding of the impact that mindfulness interventions may exert on creative performance, two meta-analytical reviews were conducted, drawing respectively on studies using a control group design (n = 20) and studies using a pretest-posttest design (n = 17). A positive effect was identified between mindfulness and creativity, both for control group designs (d = 0.42, 95% CIs [0.29, 0.54]) and pretest-posttest designs (d = 0.59, 95% CIs [0.38, 0.81]). Subgroup analysis revealed that intervention length, creativity task (i.e., divergent vs. convergent thinking tasks) and control group type, were significant moderators for control group studies, whereas only intervention length was a significant moderator for pretest-posttest studies. Overall, the findings support the use of mindfulness as a tool to enhance creative performance, with more advantageous outcomes for convergent as opposed to divergent thinking tasks. We discuss the implications of study design and intervention length as key factors of relevance to future research aimed at advancing theoretical accounts of the relationship between mindfulness and creativity.

A comprehensive characterization of cognitive performance, clinical symptoms, and cortical activity following mild traumatic brain injury (mTBI)

OBJECTIVE

The objective of this study was to investigate clinical symptoms, cognitive performance and cortical activity following mild traumatic brain injury (mTBI).

METHODS

We recruited 30 individuals in the sub-acute phase post mTBI and 28 healthy controls with no history of head injury and compared these groups on clinical, cognitive and cortical activity measures. Measures of cortical activity included; resting state electroencephalography (EEG), task related EEG and combined transcranial magnetic stimulation with electroencephalography (TMS-EEG). Primary analyses investigated clinical, cognitive and cortical activity differences between groups. Exploratory analyses investigated the relationships between these measures.

RESULTS

At 4 weeks' post injury, mTBI participants exhibited significantly greater post concussive and clinical symptoms compared to controls; as well as reduced cognitive performance on verbal learning and working memory measures. mTBI participants demonstrated alterations in cortical activity while at rest and in response to stimulation with TMS.

CONCLUSIONS

The present study comprehensively characterized the multidimensional effect of mTBI in the sub-acute phase post injury, showing a broad range of differences compared to non-mTBI participants. Further research is needed to explore the relationship between these pathophysiologies and clinical/cognitive symptoms in mTBI.

Mindfulness Training Improves Attention: Evidence from Behavioral and Event-related Potential Analyses

Mindfulness meditation helps to improve attentional capacity. However, the neural correlates that indicate the mechanism through which mindfulness improves attention are unclear. To address this gap, we aimed to assess the effects of mindfulness training on sustained attentional capacity. Event-related potentials (ERPs) associated with the modified sustained attention response task (mSART) were used in this study. A total of 45 college students were randomly assigned to either the mindfulness group (n = 21) or the control group (n = 24). Participants in the mindfulness group received a three-week mindfulness training. The self-report results showed that the mindfulness group reported higher mindfulness scores (observing and non-judgment of inner experiences) after the training. The mindfulness group also scored lower on the state anxiety than the control group. Behavioral results also showed that self-caught mind wandering in the mindfulness group significantly decreased after the training, and the mindfulness group showed a faster response after the training. The ERP results showed that N2 amplitudes in the post-test were significantly greater than those in the pre-test in the mindfulness group. We did not find any interactions between group and time for P3. The findings suggest that mindfulness training can effectively improve sustained attentional capacity, as indicated by reduced mind wandering and increased N2 responses.

RELAX part 2: A fully automated EEG data cleaning algorithm that is applicable to Event-Related-Potentials

OBJECTIVE

Electroencephalography (EEG) is often used to examine neural activity time-locked to stimuli presentation, referred to as Event-Related Potentials (ERP). However, EEG is influenced by non-neural artifacts, which can confound ERP comparisons. Artifact cleaning reduces artifacts, but often requires time-consuming manual decisions. Most automated methods filter frequencies <1 Hz out of the data, so are not recommended for ERPs (which contain frequencies <1 Hz). Our aim was to test the RELAX (Reduction of Electroencephalographic Artifacts) pre-processing pipeline for use on ERP data.

METHODS

The cleaning performance of multiple versions of RELAX were compared to four commonly used EEG cleaning pipelines across both artifact cleaning metrics and the amount of variance in ERPs explained by different conditions in a Go-Nogo task. Results RELAX with Multi-channel Wiener Filtering (MWF) and wavelet-enhanced independent component analysis applied to artifacts identified with ICLabel (wICA_ICLabel) cleaned data most effectively and produced amongst the most dependable ERP estimates. RELAX with wICA_ICLabel only or MWF_only may detect effects better for some ERPs.

CONCLUSIONS

RELAX shows high artifact cleaning performance even when data is high-pass filtered at 0.25 Hz (applicable to ERP analyses).

SIGNIFICANCE

RELAX is easy to implement via EEGLAB in MATLAB and freely available on GitHub. Given its performance and objectivity we recommend RELAX to improve artifact cleaning and consistency across ERP research.

Dispositional Mindfulness and Inhibitory Control after Perceiving Neutral, Food and Money Related Stimuli

Previous studies have shown that dispositional mindfulness is positively associated with cognitive performance, including the ability to stop behavioral actions (formally called inhibitory control). However, some studies suggest that the relationship may be context dependent. The current study addressed previous limitations and focused on the role of reward context regarding the relationship between mindfulness and inhibitory control. Seventy-five participants (31 men, 44 women) between 18-50 years old (M = 30, SD = 9) were included in the final sample. Participants filled out a self-report measure of mindfulness and performed a stop signal task with three conditions that varied in terms of reward context. In the neutral condition, go stimuli (stimuli to which a response was required) were letters; in the food and money condition, these were pictures of food and money, respectively. Results showed that inhibitory control was reduced in the money condition relative to the neutral condition (p = 0.012). Mindfulness was positively correlated with inhibitory control, but only in the money condition (p = 0.001). However, results might differ when inhibitory control is required while perceiving a learned reward-related stimulus. The latter represents an open question for future research.

Mindfulness Meditation Improves Musical Aesthetic Emotion Processing in Young Adults

This study explored the behavioral and neural correlates of mindfulness meditation improvement in musical aesthetic emotion processing (MAEP) in young adults, using the revised across-modal priming paradigm. Sixty-two participants were selected from 652 college students who assessed their mindfulness traits using the Mindful Attention Awareness Scale (MAAS). According to the 27% ratio of the high and low total scores, participants were divided into two subgroups: high trait group (n = 31) and low trait group (n = 31). Participants underwent facial recognition and emotional arousal tasks while listening to music, and simultaneously recorded event-related potentials (ERPs). The N400, P3, and late positive component (LPC) were investigated. The behavioral results showed that mindfulness meditation improved executive control abilities in emotional face processing and effectively regulated the emotional arousal of repeated listening to familiar music among young adults. These improvements were associated with positive changes in key neural signatures of facial recognition (smaller P3 and larger LPC effects) and emotional arousal (smaller N400 and larger LPC effects). Our results show that P3, N400, and LPC are important neural markers for the improvement of executive control and regulating emotional arousal in musical aesthetic emotion processing, providing new evidence for exploring attention training and emotional processing. We revised the affecting priming paradigm and E-prime 3.0 procedure to fulfill the simultaneous measurement of music listening and experimental tasks and provide a new experimental paradigm to simultaneously detect the behavioral and neural correlates of mindfulness-based musical aesthetic processing.

Effects of Mindfulness Meditation on Musical Aesthetic Emotion Processing

Mindfulness meditation is a form of self-regulatory training for the mind and the body. The relationship between mindfulness meditation and musical aesthetic emotion processing (MAEP) remains unclear. This study aimed to explore the effect of temporary mindfulness meditation on MAEP while listening to Chinese classical folk instrumental musical works. A 2 [(groups: mindfulness meditation group (MMG); control group (CG)] × 3 (music emotions: calm music, happy music, and sad music) mixed experimental design and a convenience sample of university students were used to verify our hypotheses, which were based on the premise that temporary mindfulness meditation may affect MAEP (MMG vs. CG). Sixty-seven non-musically trained participants (65.7% female, age range: 18–22 years) were randomly assigned to two groups (MMG or CG). Participants in MMG were given a single 10-min recorded mindfulness meditation training before and when listening to music. The instruments for psychological measurement comprised of the Five Facet Mindfulness Questionnaire (FFMQ) and the Positive and Negative Affect Schedule (PANAS). Self-report results showed no significant between-group differences for PANAS and for the scores of four subscales of the FFMQ (p > 0.05 throughout), except for the non-judging of inner experience subscale. Results showed that temporary mindfulness meditation training decreased the negative emotional experiences of happy and sad music and the positive emotional experiences of calm music during recognition and experience and promoted beautiful musical experiences in individuals with no musical training. Maintaining a state of mindfulness while listening to music enhanced body awareness and led to experiencing a faster passage of musical time. In addition, it was found that Chinese classical folk instrumental musical works effectively induced aesthetic emotion and produced multidimensional aesthetic experiences among non-musically trained adults. This study provides new insights into the relationship between mindfulness and music emotion.

Regulation of Mindfulness-Based Music Listening on Negative Emotions Related to COVID-19: An ERP Study

The current study aimed to explore the behavioral and neural correlates of mindfulness-based music listening regulation of induced negative emotions related to COVID-19 using the face-word Stroop task. Eighty-five young adults visited the laboratory and were randomly assigned to three groups: a calm music group (CMG: n = 28), a happy music group (HMG: n = 30), and a sad music group (SMG: n = 27). Negative emotions were induced in all participants using a COVID-19 video, followed by the music intervention condition. Participants underwent the face-word Stroop tasks during which event-related potentials (ERPs) were recorded. The N2, N3, P3, and late positive component (LPC) were investigated. The results showed that calm music and happy music effectively regulate young adults' induced negative emotions, while young adults experienced more negative emotions when listening to sad music; the negative mood states at the post-induction phase inhibited the reaction of conflict control in face-word Stroop tasks, which manifested as lower accuracy (ACC) and slower reaction times (RTs). ERP results showed negative mood states elicited greater N2, N3, and LPC amplitudes and smaller P3 amplitudes. Further studies are needed to develop intervention strategies to enhance emotion regulation related to COVID-19 for other groups.

Interpretability of Spatiotemporal Dynamics of the Brain Processes Followed by Mindfulness Intervention in a Brain-Inspired Spiking Neural Network Architecture

Mindfulness training is associated with improvements in psychological wellbeing and cognition, yet the specific underlying neurophysiological mechanisms underpinning these changes are uncertain. This study uses a novel brain-inspired artificial neural network to investigate the effect of mindfulness training on electroencephalographic function. Participants completed a 4-tone auditory oddball task (that included targets and physically similar distractors) at three assessment time points. In Group A (n = 10), these tasks were given immediately prior to 6-week mindfulness training, immediately after training and at a 3-week follow-up; in Group B (n = 10), these were during an intervention waitlist period (3 weeks prior to training), pre-mindfulness training and post-mindfulness training. Using a spiking neural network (SNN) model, we evaluated concurrent neural patterns generated across space and time from features of electroencephalographic data capturing the neural dynamics associated with the event-related potential (ERP). This technique capitalises on the temporal dynamics of the shifts in polarity throughout the ERP and spatially across electrodes. Findings support anteriorisation of connection weights in response to distractors relative to target stimuli. Right frontal connection weights to distractors were associated with trait mindfulness (positively) and depression (inversely). Moreover, mindfulness training was associated with an increase in connection weights to targets (bilateral frontal, left frontocentral, and temporal regions only) and distractors. SNN models were superior to other machine learning methods in the classification of brain states as a function of mindfulness training. Findings suggest SNN models can provide useful information that differentiates brain states based on distinct task demands and stimuli, as well as changes in brain states as a function of psychological intervention.

Neural changes in early visual processing after 6 months of mindfulness training in older adults

Mindfulness has been shown to improve attentional performance, which is known to decline in aging. Long-latency electroencephalographic (EEG) event-related potential (ERP) changes have been reported immediately after mindfulness training, however the enduring stability of these effects is unknown. Furthermore, the ability of mindfulness to impact earlier stages of information processing is unclear. We examined neural activation using high density EEG in older adults engaged in mindfulness training to examine the long-term stability of training effects. After 6 months of training, mindfulness practitioners displayed enhanced neural activation during sensory encoding and perceptual processing of a visual cue. Enhanced perceptual processing of a visual cue was associated with increased neural activation during post-perceptual processing of a subsequent target. Similar changes were not observed in a control group engaged in computer-based attention training over the same period. Neural changes following mindfulness training were accompanied by behavioural improvements in attentional performance. Our results are suggestive of increased efficiency of the neural pathways subserving bottom-up visual processing together with an enhanced ability to mobilise top-down attentional processes during perceptual and post-perceptual processing following mindfulness training. These results indicate that mindfulness may enhance neural processes known to deteriorate in normal aging and age-related neurodegenerative diseases.

Learning dynamics of electrophysiological brain signals during human fear conditioning

Electrophysiological studies in rodents allow recording neural activity during threats with high temporal and spatial precision. Although fMRI has helped translate insights about the anatomy of underlying brain circuits to humans, the temporal dynamics of neural fear processes remain opaque and require EEG. To date, studies on electrophysiological brain signals in humans have helped to elucidate underlying perceptual and attentional processes, but have widely ignored how fear memory traces evolve over time. The low signal-to-noise ratio of EEG demands aggregations across high numbers of trials, which will wash out transient neurobiological processes that are induced by learning and prone to habituation. Here, our goal was to unravel the plasticity and temporal emergence of EEG responses during fear conditioning. To this end, we developed a new sequential-set fear conditioning paradigm that comprises three successive acquisition and extinction phases, each with a novel CS+/CS- set. Each set consists of two different neutral faces on different background colors which serve as CS+ and CS-, respectively. Thereby, this design provides sufficient trials for EEG analyses while tripling the relative amount of trials that tap into more transient neurobiological processes. Consistent with prior studies on ERP components, data-driven topographic EEG analyses revealed that ERP amplitudes were potentiated during time periods from 33-60 ms, 108-200 ms, and 468-820 ms indicating that fear conditioning prioritizes early sensory processing in the brain, but also facilitates neural responding during later attentional and evaluative stages. Importantly, averaging across the three CS+/CS- sets allowed us to probe the temporal evolution of neural processes: Responses during each of the three time windows gradually increased from early to late fear conditioning, while long-latency (460-730 ms) electrocortical responses diminished throughout fear extinction. Our novel paradigm demonstrates how short-, mid-, and long-latency EEG responses change during fear conditioning and extinction, findings that enlighten the learning curve of neurophysiological responses to threat in humans.

Determination of the Time Window of Event-Related Potential Using Multiple-Set Consensus Clustering

Clustering is a promising tool for grouping the sequence of similar time-points aimed to identify the attention blocks in spatiotemporal event-related potentials (ERPs) analysis. It is most likely to elicit the appropriate time window for ERP of interest if a suitable clustering method is applied to spatiotemporal ERP. However, how to reliably estimate a proper time window from entire individual subjects' data is still challenging. In this study, we developed a novel multiset consensus clustering method in which several clustering results of multiple subjects were combined to retrieve the best fitted clustering for all the subjects within a group. Then, the obtained clustering was processed by a newly proposed time-window detection method to determine the most suitable time window for identifying the ERP of interest in each condition/group. Applying the proposed method to the simulated ERP data and real data indicated that the brain responses from the individual subjects can be collected to determine a reliable time window for different conditions/groups. Our results revealed more precise time windows to identify N2 and P3 components in the simulated data compared to the state-of-the-art methods. Additionally, our proposed method achieved more robust performance and outperformed statistical analysis results in the real data for N300 and prospective positivity components. To conclude, the proposed method successfully estimates the time window for ERP of interest by processing the individual data, offering new venues for spatiotemporal ERP processing.

A Critical Analysis on Characterizing the Meditation Experience Through the Electroencephalogram

Meditation practices, originated from ancient traditions, have increasingly received attention due to their potential benefits to mental and physical health. The scientific community invests efforts into scrutinizing and quantifying the effects of these practices, especially on the brain. There are methodological challenges in describing the neural correlates of the subjective experience of meditation. We noticed, however, that technical considerations on signal processing also don't follow standardized approaches, which may hinder generalizations. Therefore, in this article, we discuss the usage of the electroencephalogram (EEG) as a tool to study meditation experiences in healthy individuals. We describe the main EEG signal processing techniques and how they have been translated to the meditation field until April 2020. Moreover, we examine in detail the limitations/assumptions of these techniques and highlight some good practices, further discussing how technical specifications may impact the interpretation of the outcomes. By shedding light on technical features, this article contributes to more rigorous approaches to evaluate the construct of meditation.

Human non-olfactory cognition phase-locked with inhalation

Olfactory stimulus acquisition is perfectly synchronized with inhalation, which tunes neuronal ensembles for incoming information. Because olfaction is an ancient sensory system that provided a template for brain evolution, we hypothesized that this link persisted, and therefore nasal inhalations may also tune the brain for acquisition of non-olfactory information. To test this, we measured nasal airflow and electroencephalography during various non-olfactory cognitive tasks. We observed that participants spontaneously inhale at non-olfactory cognitive task onset and that such inhalations shift brain functional network architecture. Concentrating on visuospatial perception, we observed that nasal inhalation drove increased task-related brain activity in specific task-related brain regions and resulted in improved performance accuracy in the visuospatial task. Thus, mental processes with no link to olfaction are nevertheless phase-locked with nasal inhalation, consistent with the notion of an olfaction-based template in the evolution of human brain function.