The EEG spectral properties of meditation and mind wandering differ between experienced meditators and novices

Mind Wandering during Implicit Learning Is Associated with Increased Periodic EEG Activity and Improved Extraction of Hidden Probabilistic Patterns

Mind wandering, occupying 30-50% of our waking time, remains an enigmatic phenomenon in cognitive neuroscience. A large number of studies showed a negative association between mind wandering and attention-demanding (model-based) tasks in both natural settings and laboratory conditions. Mind wandering, however, does not seem to be detrimental for all cognitive domains and was observed to benefit creativity and problem-solving. We examined if mind wandering may facilitate model-free processes, such as probabilistic learning, which relies on the automatic acquisition of statistical regularities with minimal attentional demands. We administered a well-established implicit probabilistic learning task combined with thought probes in healthy adults (N = 37, 30 females). To explore the neural correlates of mind wandering and probabilistic learning, participants were fitted with high-density electroencephalography. Our findings indicate that probabilistic learning was not only immune to periods of mind wandering but was positively associated with it. Spontaneous, as opposed to deliberate mind wandering, was particularly beneficial for extracting the probabilistic patterns hidden in the visual stream. Cortical oscillatory activity in the low-frequency (slow and delta) range, indicative of covert sleep-like states, was associated with both mind wandering and improved probabilistic learning, particularly in the early stages of the task. Given the importance of probabilistic implicit learning in predictive processing, our findings provide novel insights into the potential cognitive benefits of task-unrelated thoughts in addition to shedding light on its neural mechanisms.

Using Electroencephalography to Advance Mindfulness Science: A Survey of Emerging Methods and Approaches

Throughout the brief history of contemplative neuroscience, electroencephalography (EEG) has been a valuable and enduring methodology used to elucidate the neural correlates and mechanisms of mindfulness. In this review, we provide a reminder that longevity should not be conflated with obsoletion and that EEG continues to offer exceptional promise for addressing key questions and challenges that pervade the field today. Toward this end, we first outline the unique advantages of EEG from a research strategy and experimental design perspective, then highlight an array of new sophisticated data analytic approaches and translational paradigms. Along the way, we provide illustrative examples from our own work and the broader literature to showcase how these innovations can be leveraged to spark new insights and stimulate progress across both basic science and translational applications of mindfulness. Ultimately, we argue that EEG still has much to contribute to contemplative neuroscience, and we hope to solicit the interest of other investigators to make full use of its capabilities in service of maximizing its potential within the field.

From Confound to Clinical Tool: Mindfulness and the Observer Effect in Research and Therapy

The observer effect (OE), the idea that observing a phenomenon changes it, has important implications across scientific disciplines involving measurement and observation. While often viewed as a confounding variable to control for, this paper argues that the OE should be seriously accounted for, explored, and systematically leveraged in research and clinical settings. Specifically, mindfulness practices that cultivate present-moment, nonjudgmental awareness are proposed as a platform to account for, explore, and intentionally harness the OE. In research contexts, mindfulness training may allow participants to provide more precise self-reports by minimizing reactive biases that perturb the observed phenomena. Empirical evidence suggests that mindfulness enhances interoceptive awareness and reduces automatic judgment, potentially increasing measurement sensitivity, specificity, and validity. Clinically, psychotherapies often aim to make unconscious patterns explicitly observable to the client, capitalizing on the transformative potential of observation. Mindfulness directly cultivates this capacity for meta-awareness, allowing individuals to decenter from rigid cognitive-emotional patterns fueling psychopathology. Rather than avoiding unpleasant experiences such as cravings or anxiety, mindfulness guides individuals to simply observe these phenomena, reducing identification and reactivity. Mindfulness practices may leverage components of the OE, facilitating lasting psychological change. To further study the OE, developing an OE index to code observer influence is proposed. Overall, this paper highlights the ubiquity of the OE and advocates developing methods to intentionally account for and apply observer influences across research and therapeutic contexts.

Decoding Depth of Meditation: Electroencephalography Insights From Expert Vipassana Practitioners

Background

Meditation practices have demonstrated numerous psychological and physiological benefits, but capturing the neural correlates of varying meditative depths remains challenging. In this study, we aimed to decode self-reported time-varying meditative depth in expert practitioners using electroencephalography (EEG).

Methods

Expert Vipassana meditators (n = 34) participated in 2 separate sessions. Participants reported their meditative depth on a personally defined 1 to 5 scale using both traditional probing and a novel spontaneous emergence method. EEG activity and effective connectivity in theta, alpha, and gamma bands were used to predict meditative depth using machine/deep learning, including a novel method that fused source activity and connectivity information.

Results

We achieved significant accuracy in decoding self-reported meditative depth across unseen sessions. The spontaneous emergence method yielded improved decoding performance compared with traditional probing and correlated more strongly with postsession outcome measures. Best performance was achieved by a novel machine learning method that fused spatial, spectral, and connectivity information. Conventional EEG channel-level methods and preselected default mode network regions fell short in capturing the complex neural dynamics associated with varying meditation depths.

Conclusions

This study demonstrates the feasibility of decoding personally defined meditative depth using EEG. The findings highlight the complex, multivariate nature of neural activity during meditation and introduce spontaneous emergence as an ecologically valid and less obtrusive experiential sampling method. These results have implications for advancing neurofeedback techniques and enhancing our understanding of meditative practices.

Mindfulness meditation is associated with global EEG spectral changes in theta, alpha, and beta amplitudes

Mindfulness meditation is linked to a broad range of psychological and physical health benefits, potentially mediated by changes in neural oscillations. This study explored changes in neural oscillations associated with both immediate and regular mindfulness meditation practice. Electroencephalographic (EEG) data were collected from 40 healthy young adults (Mage = 20.8, 24 females) during eyes-closed resting and mindfulness meditation states in two separate recording sessions, six weeks apart. Participants were novice meditators, and following the first recording session, were randomly assigned to either a daily mindfulness meditation practice or classical music listening as an active control, which they completed until the second recording session. Traditional bands of delta (1.0-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), beta (13.5-30.0 Hz), and gamma (30.5-45.0 Hz) were used to explore changes in global EEG spectral amplitude. A significant increase in theta between sessions was observed in both groups and states. Alpha decreased significantly during meditation compared with rest, and a three-way interaction indicated a smaller reduction during meditation between sessions in the mindfulness group. There was a similar interaction in beta, which remained stable between sessions during both rest and meditation in the mindfulness group while varying in the classical music listening group. No significant effects were observed in global delta or gamma amplitudes. These findings suggest that changes in neural oscillations associated with breath-focused mindfulness meditation may be related to processes underlying attention and awareness. Further research is necessary to consolidate these findings, particularly in relation to the associated health benefits.

Mindfulness meditation alters neural oscillations independently of arousal

Neuroscience has identified that mindfulness meditation induces a state of relaxed alertness, characterised by changes in theta and alpha oscillations and reduced sympathetic arousal, although the underlying mechanisms remain unclear. This study aims to address this gap by examining changes in neural oscillations and arousal during mindfulness meditation using both traditional and data-driven methods. Fifty-two healthy young adults underwent electroencephalography (EEG) and skin conductance level (SCL) recordings during resting baseline and mindfulness meditation conditions, both conducted with eyes closed. The EEG data revealed a significant decrease in traditional alpha (8-13 Hz) amplitude during mindfulness meditation compared to rest. However, no significant differences were observed between conditions in traditional delta, theta, beta, or gamma amplitudes. Frequency Principal Components Analysis (fPCA) was employed as a data-driven approach, identifying six components consistent across conditions. A complex delta-theta-alpha component significantly increased during mindfulness meditation. In contrast, low alpha (~9.5 Hz) and low alpha-beta (~11 Hz) components decreased significantly during mindfulness meditation. No significant differences were observed between conditions in the delta, high alpha, and high alpha-beta components. Additionally, there were no significant differences in SCL between conditions, nor were there correlations between traditional alpha or fPCA components and SCL. These findings support the conceptualisation of mindfulness meditation as a state of relaxed alertness, characterised by changes in neural oscillations likely associated with attention and awareness. However, the observed changes do not appear to be driven by arousal.

Mindfulness Training in High-Demand Cohorts Alters Resting-State Electroencephalography: An Exploratory Investigation of Individual Alpha Frequency, Aperiodic 1/f Activity, and Microstates

Background

Mindfulness training (MT) programs have demonstrated utility as cognitive training tools, but there is little consensus on the neurophysiological processes that may underlie its benefits. It has been posited that intrinsic brain activity recorded at rest reflects the functional connectivity of large-scale brain networks and may provide insight into neuroplastic changes that support MT. In the current study, we indexed changes in several resting-state electroencephalography (EEG) parameters to investigate the neurophysiological underpinnings of MT.

Methods

Resting-state EEG data were collected from active-duty U.S. military personnel (N = 80) at 2 testing sessions: before (time [T] 1) and after (T2) engaging in an 8-week MT or active comparison intervention (positivity training). We examined longitudinal and/or groupwise differences in several EEG parameters through parameterization of power spectra (individual alpha frequency and 1/f activity) and microstate analysis.

Results

While no significant group × time differences were observed in individual alpha frequency, significant group × time effects were observed in several EEG parameters from T1 to T2. Compared with MT, positivity training was associated with a steepening of the 1/f slope and higher 1/f intercepts together with decreased duration and increased global field power of microstates.

Conclusions

Taken together, these results suggest that the effects of interventions may be differentiated in resting-state brain activity in a sample of military personnel. Such findings provide insight into the neural underpinnings of MT-related brain changes, but more research is required to elucidate how these may relate to task-related neural and performance changes with MT and whether results generalize to other mindfulness interventions in alternative cohorts and contexts.

Exploring neural markers of dereification in meditation based on EEG and personalized models of electrophysiological brain states

With mounting evidence for the benefits of meditation, there has been a growing interest in measuring and quantifying meditative states. This study introduces the Inner Dereification Index (IDI), a class of personalized models designed to quantify the distance from non-meditative states such as mind wandering based on a single individual's neural activity. In addition to demonstrating high classification accuracy (median AUC: 0.996) at distinguishing meditation from thinking states moment by moment, IDI can accurately stratify meditator cohorts by experience, and correctly identify the practices most effective at training the dereification aspect of meditation (decentering from immersion with thoughts and perceptions and recognizing them as mental constructs). These results suggest that IDI models may be a useful real-time proxy for dereification and meditation progress, requiring only 1 min of mind wandering data (and no meditation data) during model training. Thus, they show promise for applications such as real-time meditation feedback, progress tracking, personalization of practices, and potential therapeutic applications of neurofeedback-assisted generation of positive states of consciousness.

Meditation-type specific reduction in infra-slow activity of electroencephalogram

Purpose

Meditation is renowned for its positive effects on cognitive abilities and stress reduction. It has been reported that the amplitude of electroencephalographic (EEG) infra-slow activity (ISA, < 0.1 Hz) is reduced as the stress level decreases. Consequently, we aimed to determine if EEG ISA amplitude decreases as a result of meditation practice across various traditions.

Methods

To this end, we analyzed an open dataset comprising EEG data acquired during meditation sessions from experienced practitioners in the Vipassana tradition-which integrates elements of focused attention and open monitoring, akin to mindfulness meditation-and in the Himalayan Yoga and Isha Shoonya traditions, which emphasize focused attention and open monitoring, respectively.

Results

A general trend was observed where EEG ISA amplitude tended to decrease in experienced meditators from these traditions compared to novices, particularly significant in the 0.03-0.08 Hz band for Vipassana meditators. Therefore, our analysis focused on this ISA frequency band. Specifically, a notable decrease in EEG ISA amplitude was observed in Vipassana meditators, predominantly in the left-frontal region. This reduction in EEG ISA amplitude was also accompanied by a decrease in phase-amplitude coupling (PAC) between the ISA phase and alpha band (8-12 Hz) amplitude, which implied decreased neural excitability fluctuations.

Conclusion

Our findings suggest that not only does EEG ISA amplitude decrease in experienced meditators from traditions that incorporate both focused attention and open monitoring, but this decrease may also signify a diminished influence of neural excitability fluctuations attributed to ISA.

Suspending the Embodied Self in Meditation Attenuates Beta Oscillations in the Posterior Medial Cortex

Human experience is imbued by the sense of being an embodied agent. The investigation of such basic self-consciousness has been hampered by the difficulty of comprehensively modulating it in the laboratory while reliably capturing ensuing subjective changes. The present preregistered study fills this gap by combining advanced meditative states with principled phenomenological interviews: 46 long-term meditators (19 female, 27 male) were instructed to modulate and attenuate their embodied self-experience during magnetoencephalographic monitoring. Results showed frequency-specific (high-beta band) activity reductions in frontoparietal and posterior medial cortices (PMC). Importantly, PMC reductions were driven by a subgroup describing radical embodied self-disruptions, including suspension of agency and dissolution of a localized first-person perspective. Neural changes were correlated with lifetime meditation and interview-derived experiential changes, but not with classical self-reports. The results demonstrate the potential of integrating in-depth first-person methods into neuroscientific experiments. Furthermore, they highlight neural oscillations in the PMC as a central process supporting the embodied sense of self.

Assessing the effects of an 8-week mindfulness training program on neural oscillations and self-reports during meditation practice

Previous literature suggests that mindfulness meditation can have positive effects on mental health, however, its mechanisms of action are still unclear. In this pre-registered study, we investigate the effects of mindfulness training on lapses of attention (and their associated neural correlates) during meditation practice. For this purpose, we recorded Electroencephalogram (EEG) during meditation practice before and after 8 weeks of mindfulness training (or waitlist) in 41 participants (21 treatment and 20 controls). In order to detect lapses of attention and characterize their EEG correlates, we interrupted participants during meditation to report their level of focus and drowsiness. First, we show that self-reported lapses of attention during meditation practice were associated to an increased occurrence of theta oscillations (3-6 Hz), which were slower in frequency and more spatially widespread than theta oscillations occurring during focused attention states. Then, we show that mindfulness training did not reduce the occurrence of lapses of attention nor their associated EEG correlate (i.e. theta oscillations) during meditation. Instead, we find that mindfulness training was associated with a significant slowing of alpha oscillations in frontal electrodes during meditation. Crucially, frontal alpha slowing during meditation practice has been reported in experienced meditators and is thought to reflect relative decreases in arousal levels. Together, our findings provide insights into the EEG correlates of mindfulness meditation, which could have important implications for the identification of its mechanisms of action and/or the development of neuromodulation protocols aimed at facilitating meditation practice.

Augmenting complex and dynamic performance through mindfulness-based cognitive training: An evaluation of training adherence, trait mindfulness, personality and resting-state EEG

Human performance applications of mindfulness-based training have demonstrated its utility in enhancing cognitive functioning. Previous studies have illustrated how these interventions can improve performance on traditional cognitive tests, however, little investigation has explored the extent to which mindfulness-based training can optimise performance in more dynamic and complex contexts. Further, from a neuroscientific perspective, the underlying mechanisms responsible for performance enhancements remain largely undescribed. With this in mind, the following study aimed to investigate how a short-term mindfulness intervention (one week) augments performance on a dynamic and complex task (target motion analyst task; TMA) in young, healthy adults (n = 40, age range = 18-38). Linear mixed effect modelling revealed that increased adherence to the web-based mindfulness-based training regime (ranging from 0-21 sessions) was associated with improved performance in the second testing session of the TMA task, controlling for baseline performance. Analyses of resting-state electroencephalographic (EEG) metrics demonstrated no change across testing sessions. Investigations of additional individual factors demonstrated that enhancements associated with training adherence remained relatively consistent across varying levels of participants' resting-state EEG metrics, personality measures (i.e., trait mindfulness, neuroticism, conscientiousness), self-reported enjoyment and timing of intervention adherence. Our results thus indicate that mindfulness-based cognitive training leads to performance enhancements in distantly related tasks, irrespective of several individual differences. We also revealed nuances in the magnitude of cognitive enhancements contingent on the timing of adherence, regardless of total volume of training. Overall, our findings suggest that mindfulness-based training could be used in a myriad of settings to elicit transferable performance enhancements.

EEG changes induced by meditative practices: State and trait effects in healthy subjects and in patients with epilepsy

The effect of meditation on brain activity has been the topic of many studies in healthy subjects and in patients suffering from chronic diseases. These effects are either explored during meditation practice (state effects) or as a longer-term result of meditation training during the resting-state (trait). The topic of this article is to first review these findings by focusing on electroencephalography (EEG) changes in healthy subjects with or without experience in meditation. Modifications in EEG baseline rhythms, functional connectivity and advanced nonlinear parameters are discussed in regard to feasibility in clinical applications. Secondly, we provide a state-of-the-art of studies that proposed meditative practices as a complementary therapy in patients with epilepsy, in whom anxiety and depressive symptoms are prevalent. In these studies, the effects of standardized meditation programs including elements of traditional meditation practices such as mindfulness, loving-kindness and compassion are explored both at the level of psychological functioning and on the occurrence of seizures. Lastly, preliminary results are given regarding our ongoing study, the aim of which is to quantify the effects of a mindfulness self-compassion (MSC) practice on interictal and ictal epileptic activity. Feasibility, difficulties, and prospects of this study are discussed.

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.

Functional reorganization of the brain in distinct frequency bands during eyes-open meditation

Meditation is a self-regulatory process practiced primarily to reduce stress, manage emotions and mental health. The objective of this work is to study the information exchange between electrodes within and across the hemispheres during meditation using functional connectivity (FC) measures. We investigate the changes in the coherence between EEG electrode pairs during the meditation with open eyes practiced by long-term Brahmakumaris Rajyoga meditators and during listening to music by controls as the comparable task. FC derived from coherency, pairwise phase consistency (PPC) is used to study the changes in intra and interhemispheric coherence. Integrating connectivity (IC) derived from node degree strength has also been analyzed. Meditators show increased PPC in higher theta and alpha bands both within and across hemispheres. However, the control subjects with no knowledge of meditation show no change in theta band during the music session. Further, during baseline conditions, higher interhemispheric anterior to posterior IC is found in meditators in higher beta and slow gamma bands than controls. Distinct patterns of changes are observed with the PPC and IC measures in different frequency bands during meditation in the meditators and music-listening session in the control subjects indicating varied information processing between the right and left hemispheres. Increased IC is found between the frontal electrodes implying increased self-awareness in meditators. The PPC between the occipital electrodes in meditators is less than the controls in baseline condition indicating a possible modified visual information processing in Rajyoga meditators due to the long-term practice of meditation with open eyes. Overall, the changes in PPC and associated IC indicate increased functional integration during meditation supporting the hypothesis of communication through coherence and cortical integration theory during the non-ordinary state of consciousness induced by meditation.

Evaluating brain spectral and connectivity differences between silent mind-wandering and trance states

Trance is an altered state of consciousness characterized by alterations in cognition. In general, trance states induce mental silence (i.e., cognitive thought reduction), and mental silence can induce trance states. Conversely, mind-wandering is the mind's propensity to stray its attention away from the task at hand and toward content irrelevant to the current moment, and its main component is inner speech. Building on the previous literature on mental silence and trance states and incorporating inverse source reconstruction advances, the study's objectives were to evaluate differences between trance and mind-wandering states using: (1) electroencephalography (EEG) power spectra at the electrode level, (2) power spectra at the area level (source reconstructed signal), and (3) EEG functional connectivity between these areas (i.e., how they interact). The relationship between subjective trance depths ratings and whole-brain connectivity during trance was also evaluated. Spectral analyses revealed increased delta and theta power in the frontal region and increased gamma in the centro-parietal region during mind-wandering, whereas trance showed increased beta and gamma power in the frontal region. Power spectra at the area level and pairwise comparisons of the connectivity between these areas demonstrated no significant difference between the two states. However, subjective trance depth ratings were inversely correlated with whole-brain connectivity in all frequency bands (i.e., deeper trance is associated with less large-scale connectivity). Trance allows one to enter mentally silent states and explore their neurophenomenological processes. Limitations and future directions are discussed.

Effects of a Neuroscience-Based Mindfulness Meditation Program on Psychological Health: Pilot Randomized Controlled Trial

BACKGROUND

Mindfulness and meditation have a rich historical tradition, and a growing scientific base of evidence supports their use in creating positive psychological and neuroplastic changes for practitioners. Although meditation can be taught in various ways, the scientific community has yet to systematically study the impact of different types of meditation on neuropsychological outcomes, especially as it pertains to digital implementation. Therefore, it is critical that the instruction of mindfulness be evidence based because meditation is being used in both scientific and clinical settings.

OBJECTIVE

This study investigated the use of teacher cueing and the integration of neuroscience education into a meditation program. Compassion cueing was chosen as the element of experimental manipulation because traditional lineages of Buddhist meditation teach compassion for self and others as one of the primary outcomes of meditation. We hypothesized that participants receiving compassion cueing would have enhanced neuropsychological outcomes compared with those receiving functional cueing and that gains in neuroscience knowledge would relate to positive neuropsychological outcomes.

METHODS

Participants (n=89) were randomized to receive either functional cueing (control group) or compassion cueing (experimental group) and engaged with five 10-minute meditation sessions a week for 4 weeks. All intervention sessions were administered through digital presentation. All participants completed ecological momentary assessments before and after the daily intervention, as well as pre- and postintervention questionnaires.

RESULTS

Participants demonstrated significant benefits over time, including increased mindfulness and self-compassion, decreased depression, and gains in neuroscience content (all P<.001); however, no significant between-group differences were found. Daily scores from each day of the intervention showed a statistically significant shift from active toward settled. Importantly, long-term increases in mindfulness were positively correlated to changes in compassion (r=0.326; P=.009) and self-compassion (r=0.424; P<.001) and negatively correlated to changes in anxiety (r=-0.266; P=.03) and depression (r=-0.271; P=.03). Finally, the acute effects of meditation were significantly correlated to the longitudinal outcomes (with a small-to-medium effect size), especially those relevant to mindfulness.

CONCLUSIONS

We developed a novel neuroscience-based education-meditation program that enhanced self-regulation as evidenced by improved mindfulness, self-compassion, and mood state. Our findings demonstrate the behavioral importance of engaging with mindfulness meditation and reinforce the idea that the benefits of meditation are independent of teacher cueing behavior. Future studies will need to investigate the brain-based changes underlying these meditation-induced outcomes.

Effects of a randomised trial of 5-week heart rate variability biofeedback intervention on mind wandering and associated brain function

Previous research suggests that excessive negative self-related thought during mind wandering involves the default mode network (DMN) core subsystem and the orbitofrontal cortex (OFC). Heart rate variability (HRV) biofeedback, which involves slow paced breathing to increase HRV, is known to promote emotional well-being. However, it remains unclear whether it has positive effects on mind wandering and associated brain function. We conducted a study where young adults were randomly assigned to one of two 5-week interventions involving daily biofeedback that either increased heart rate oscillations via slow paced breathing (Osc+ condition) or had little effect on heart rate oscillations (active control or Osc- condition). The two intervention conditions did not differentially affect mind wandering and DMN core-OFC functional connectivity. However, the magnitude of participants' heart rate oscillations during daily biofeedback practice was associated with pre-to-post decreases in mind wandering and in DMN core-OFC functional connectivity. Furthermore, the reduction in the DMN core-OFC connectivity was associated with a decrease in mind wandering. Our results suggested that daily sessions involving high amplitude heart rate oscillations may help reduce negative mind wandering and associated brain function.

Electrophysiological correlates of mindfulness in patients with major depressive disorder

Objectives

Mindfulness-based interventions (MBI) can reduce both stress and depressive symptoms. However, the impact of mindfulness on stress level in depressed subjects remains unclear. This study aims to assess electrophysiological correlates of mindfulness in patients with major depressive disorder (MDD) at baseline, under stress exposure, and in relaxation following stress exposure.

Methods

Perceived mindfulness was assessed with the Freiburger Mindfulness Inventory (FMI) in 89 inpatients (mean age 51) with MDD [mean Beck Depression Inventory (BDI) 30]. Electrophysiological parameters [resting heart rate (RHR), heart rate variability (HRV), respiration rate, skin conductance, and skin temperature] were recorded at 5-min baseline, 1-min stress exposure, and 5-min self-induced relaxation.

Results

Freiburger Mindfulness Inventory was strongly inversely correlated with symptom severity measured by BDI (r = –0.53, p < 0.001). No correlations between FM score and electrophysiological parameters in any of the three conditions (baseline, stress exposure, relaxed state) could be found. The factor openness was associated with higher VLF (very low frequency of HRV) in the baseline condition. However, this correlation was no more significant after regression analysis when corrected for respiratory rate, age, and sex.

Conclusion

Autonomous nervous reactivity in depression was not associated with perceived mindfulness as measured by FMI score and presented electrophysiological parameters, despite the strong inverse correlation between state mindfulness and symptom severity.

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.