Source-space EEG neurofeedback links subjective experience with brain activity during effortless awareness meditation

Bridging the gap of brain and experience - Converging Neurophenomenology with Spatiotemporal Neuroscience

Neuroscience faces the challenge of connecting brain and mind, with the mind manifesting in first-person experience while the brain's neural activity can only be investigated in third-person perspective. To connect neural and mental states, Neurophenomenology provides a methodological toolkit for systematically linking first-person subjective experience with third-person objective observations of the brain's neural activity. However, beyond providing a systematic methodological strategy ('disciplined circularity'), it leaves open how neural activity and subjective experience are related among themselves, independent of our methodological strategy. The recently introduced Spatiotemporal Neuroscience suggests that neural activity and subjective experience share a commonly underlying feature as their "common currency", notably analogous spatiotemporal dynamics. Can Spatiotemporal Neuroscience inform Neurophenomenology to allow for a deeper and more substantiative connection of first-person experience and third-person neural activity? The goal of our paper is to show how Spatiotemporal Neuroscience and Neurophenomenology can be converged and integrated with each other to gain better understanding of the brain-mind connection. We describe their convergence on theoretical grounds which, subsequently, is illustrated by empirical examples like self, meditation, and depression. In conclusion, we propose that the integration of Neurophenomenology and Spatiotemporal Neuroscience can provide complementary insights, enrich both fields, allows for deeper understanding of brain-mind connection, and opens the door for developing novel methodological approaches in their empirical investigation.

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.

Closed-Loop Systems and Real-Time Neurofeedback in Mindfulness Meditation Research

Mindfulness meditation has numerous purported benefits for psychological well-being; however, problems such as adherence to mindfulness tasks, quality of mindfulness sessions, or dosage of mindfulness interventions may hinder individuals from accessing the purported benefits of mindfulness. Methodologies including closed-loop systems and real-time neurofeedback may provide tools to help bolster success in mindfulness task performance, titrate the exposure to mindfulness interventions, or improve engagement with mindfulness sessions. In this review, we explore the use of closed-loop systems and real-time neurofeedback to influence, augment, or promote mindfulness interventions. Various closed-loop neurofeedback signals from functional magnetic resonance imaging and electroencephalography have been used to provide subjective correlates of mindfulness states including functional magnetic resonance imaging region-of-interest-based signals (e.g., posterior cingulate cortex), functional magnetic resonance imaging network-based signals (e.g., default mode network, central executive network, salience network), and electroencephalography spectral-based signals (e.g., alpha, theta, and gamma bands). Past research has focused on how successful interventions have aligned with the subjective mindfulness meditation experience. Future research may pivot toward using appropriate control conditions (e.g., mindfulness only or sham neurofeedback) to quantify the effects of closed-loop systems and neurofeedback-guided mindfulness meditation in improving cognition and well-being.

An Overview of Neurophenomenological Approaches to Meditation and Their Relevance to Clinical Research

There is a renewed interest in taking phenomenology seriously in consciousness research, contemporary psychiatry, and neurocomputation. The neurophenomenology research program, pioneered by Varela, rigorously examines subjective experience using first-person methodologies, inspired by phenomenology and contemplative practices. This review explores recent advancements in neurophenomenological approaches, particularly their application to meditation practices and potential clinical research translations. First, we examine innovative multidimensional phenomenological assessment tools designed to capture subtle, dynamic shifts in experiential content and structures of consciousness during meditation. These experience sampling approaches enable shedding new light on the mechanisms and dynamic trajectories of meditation practice and retreat. Second, we highlight how empirical studies in neurophenomenology leverage the expertise of experienced meditators to deconstruct aversive and self-related processes, providing detailed first-person reports that guide researchers in identifying novel behavioral and neurodynamic markers associated with pain regulation, self-dissolution, and acceptance of mortality. Finally, we discuss a recent framework, deep computational neurophenomenology, that updates the theoretical ambitions of neurophenomenology to naturalize phenomenology. This framework uses the formalism of deep parametric active inference, where parametric depth refers to a property of generative models that can form beliefs about the parameters of their own modeling process. Collectively, these methodological innovations, centered around rigorous first-person investigation, highlight the potential of epistemologically beneficial mutual constraints among phenomenological, computational, and neurophysiological domains. This could contribute to an integrated understanding of the biological basis of mental illness, its treatment, and its tight connections to the lived experience of the patient.

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.

High-precision neurofeedback-guided meditation training optimises real-world self-guided meditation practice for well-being

Meditation can benefit well-being and mental health, but novices often struggle to effectively recognize and disengage from mental processes during meditation due to limited awareness, potentially diminishing meditation's benefits. We investigated whether personalised high-precision neurofeedback (NF) can improve disengagement from mental activity during meditation and enhance meditation's outcomes. In a single-blind, controlled, longitudinal paradigm, 40 novice meditators underwent two consecutive days of meditation training with intermittent visual feedback from either their own (N=20) or a matched participant's (N=20; control group) posterior cingulate cortex (PCC) activity measured using 7 Tesla functional magnetic resonance imaging. During training, the experimental group showed stronger functional decoupling of PCC from dorsolateral prefrontal cortex, indicating better control over disengagement from mental processes during meditation. This led to greater improvements in emotional well-being and mindful awareness of mental processes during a week of real-world self-guided meditation. We provide compelling evidence supporting the utility of high-precision NF-guided meditation training to optimise real-world meditation practice for well-being.

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.

Mindfulness-based Neurofeedback: A Systematic Review of EEG and fMRI studies

Neurofeedback concurrent with mindfulness meditation may reveal meditation effects on the brain and facilitate improved mental health outcomes. Here, we systematically reviewed EEG and fMRI studies of mindfulness meditation with neurofeedback (mbNF) and followed PRISMA guidelines. We identified 10 fMRI reports, consisting of 177 unique participants, and 9 EEG reports, consisting of 242 participants. Studies of fMRI focused primarily on downregulating the default-mode network (DMN). Although studies found decreases in DMN activations during neurofeedback, there is a lack of evidence for transfer effects, and the majority of studies did not employ adequate controls, e.g. sham neurofeedback. Accordingly, DMN decreases may have been confounded by general task-related deactivation. EEG studies typically examined alpha, gamma, and theta frequency bands, with the most robust evidence supporting the modulation of theta band activity. Both EEG and fMRI mbNF have been implemented with high fidelity in clinical populations. However, the mental health benefits of mbNF have not been established. In general, mbNF studies would benefit from sham-controlled RCTs, as well as clear reporting (e.g. CRED-NF).

Transcranial focused ultrasound to the posterior cingulate cortex modulates default mode network and subjective experience: an fMRI pilot study

Background

Transcranial focused ultrasound (TFUS) is an emerging neuromodulation tool for temporarily altering brain activity and probing network functioning. The effects of TFUS on the default mode network (DMN) are unknown.

Objective

The study examined the effects of transcranial focused ultrasound (TFUS) on the functional connectivity of the default mode network (DMN), specifically by targeting the posterior cingulate cortex (PCC). Additionally, we investigated the subjective effects of TFUS on mood, mindfulness, and self-related processing.

Methods

The study employed a randomized, single-blind design involving 30 healthy subjects. Participants were randomly assigned to either the active TFUS group or the sham TFUS group. Resting-state functional magnetic resonance imaging (rs-fMRI) scans were conducted before and after the TFUS application. To measure subjective effects, the Toronto Mindfulness Scale, the Visual Analog Mood Scale, and the Amsterdam Resting State Questionnaire were administered at baseline and 30 min after sonication. The Self Scale and an unstructured interview were also administered 30 min after sonication.

Results

The active TFUS group exhibited significant reductions in functional connectivity along the midline of the DMN, while the sham TFUS group showed no changes. The active TFUS group demonstrated increased state mindfulness, reduced Global Vigor, and temporary alterations in the sense of ego, sense of time, and recollection of memories. The sham TFUS group showed an increase in state mindfulness, too, with no other subjective effects.

Conclusions

TFUS targeted at the PCC can alter DMN connectivity and cause changes in subjective experience. These findings support the potential of TFUS to serve both as a research tool and as a potential therapeutic intervention.

Modest Effects of Neurofeedback-Assisted Meditation Using a Wearable Device on Stress Reduction: A Randomized, Double-Blind, and Controlled Study

BACKGROUND

To evaluate the therapeutic effectiveness and safety of a neurofeedback wearable device for stress reduction.

METHODS

A randomized, double-blind, controlled study was designed. Participants had psychological stress with depression or sleep disturbances. They practiced either neurofeedback-assisted meditation (n = 20; female, 15 [75.0%]; age, 49.40 ± 11.76 years) or neurofeedback non-assisted meditation (n = 18; female, 11 [61.1%]; age, 48.67 ± 12.90 years) for 12 minutes twice a day for two weeks. Outcome variables were self-reported questionnaires, including the Korean version of the Perceived Stress Scale, Beck Depression Inventory-II, Insomnia Severity Index, Pittsburgh Sleep Quality Index, and State Trait Anxiety Index, quantitative electroencephalography (qEEG), and blood tests. Satisfaction with device use was measured at the final visit.

RESULTS

The experimental group had a significant change in PSS score after two weeks of intervention compared with the control group (6.45 ± 0.95 vs. 3.00 ± 5.54, P = 0.037). State anxiety tended to have a greater effect in the experimental group than in the control group (P = 0.078). Depressive mood and sleep also improved in each group, with no significant difference between the two groups. There were no significant differences in stress-related physiological parameters, such as stress hormones or qEEG, between the two groups. Subjective device satisfaction was significantly higher in the experimental group than in the control group (P = 0.008).

CONCLUSION

Neurofeedback-assisted meditation using a wearable device can help improve subjective stress reduction compared with non-assisted meditation. These results support neurofeedback as an effective adjunct to meditation for relieving stress.

TRIAL REGISTRATION

Clinical Research Information Service Identifier: KCT0007413.

Protocol for a Pilot Study on the Neurocardiac Mechanism of an Interoceptive Compassion-Based Heart-Smile Training for Depression

Background

Heart-Smile Training (HST) is an interoceptive compassion-based behavioral intervention that in case reports has been beneficial for depression. Interoception refers to the awareness and regulation of physiological signals from inside the body. Depressed patients often have diminished interoceptive awareness and often experience disconnection from bodily needs and sensations. In addition to interoceptive dysfunction, depression often involves negative self-evaluation and self-critical rumination. HST is a compassion-based meditation training program that explicitly cultivates interoceptive awareness of the heart area. This study aims to investigate the possible neurocardiac mechanisms engaged through HST for depression patients.

Methods

We plan to enroll 50 subjects to be randomized into a 4-week HST intervention group and a waitlist group. A battery of psychological questionnaires will be administered at baseline and post-intervention timepoints, and electroencephalography (EEG) will be collected during compassion meditation guided by pre-recorded audio. The primary clinical outcome measures are on the feasibility of the intervention and research procedures, the primary mechanistic outcome measure is the post-intervention change in Heartbeat Evoked Potential (HEP) amplitude. Secondary outcome measures include changes in depression severity and EEG gamma spectral activity. Exploratory outcome measures include effects of HST on skin conductance response, heart rate variability, EEG spectral properties in other frequency bands, as well as a list of psychological questionnaires that measure depression and anxiety symptoms, emotion regulation, mindfulness, interoceptive awareness, self-compassion, gratitude, sleep quality, quality of life and social connectedness.

Results

Results not yet available.

Conclusion

This is the first study on the feasibility and interoceptive neurocardiac mechanism of HST. Our findings will provide frontier knowledge on the physiological working mechanism of behavioral interventions with an interoception-based meditative approach. https://clinicaltrials.gov/study/NCT05564533.

Eliciting brain waves of people with cognitive impairment during meditation exercises using portable electroencephalography in a smart-home environment: a pilot study

Objectives

Meditation imparts relaxation and constitutes an important non-pharmacological intervention for people with cognitive impairment. Moreover, EEG has been widely used as a tool for detecting brain changes even at the early stages of Alzheimer's Disease (AD). The current study investigates the effect of meditation practices on the human brain across the AD spectrum by using a novel portable EEG headband in a smart-home environment.

Methods

Forty (40) people (13 Healthy Controls-HC, 14 with Subjective Cognitive Decline-SCD and 13 with Mild Cognitive Impairment-MCI) participated practicing Mindfulness Based Stress Reduction (Session 2-MBSR) and a novel adaptation of the Kirtan Kriya meditation to the Greek culture setting (Session 3-KK), while a Resting State (RS) condition was undertaken at baseline and follow-up (Session 1-RS Baseline and Session 4-RS Follow-Up). The signals were recorded by using the Muse EEG device and brain waves were computed (alpha, theta, gamma, and beta).

Results

Analysis was conducted on four-electrodes (AF7, AF8, TP9, and TP10). Statistical analysis included the Kruskal-Wallis (KW) nonparametric analysis of variance. The results revealed that both states of MBSR and KK lead to a marked difference in the brain's activation patterns across people at different cognitive states. Wilcoxon Signed-ranks test indicated for HC that theta waves at TP9, TP10 and AF7, AF8 in Session 3-KK were statistically significantly reduced compared to Session 1-RS Z = -2.271, p = 0.023, Z = -3.110, p = 0.002 and Z = -2.341, p = 0.019, Z = -2.132, p = 0.033, respectively.

Conclusion

The results showed the potential of the parameters used between the various groups (HC, SCD, and MCI) as well as between the two meditation sessions (MBSR and KK) in discriminating early cognitive decline and brain alterations in a smart-home environment without medical support.

Source localization using recursively applied and projected MUSIC with flexible extent estimation

Magneto- and electroencephalography (M/EEG) are widespread techniques to measure neural activity in-vivo at a high temporal resolution but low spatial resolution. Locating the neural sources underlying the M/EEG poses an inverse problem, which is ill-posed. We developed a new method based on Recursive Application of Multiple Signal Classification (MUSIC). Our proposed method is able to recover not only the locations but, in contrast to other inverse solutions, also the extent of active brain regions flexibly (FLEX-MUSIC). This is achieved by allowing it to search not only for single dipoles but also dipole clusters of increasing extent to find the best fit during each recursion. FLEX-MUSIC achieved the highest accuracy for both single dipole and extended sources compared to all other methods tested. Remarkably, FLEX-MUSIC was capable to accurately estimate the level of sparsity in the source space (r = 0.82), whereas all other approaches tested failed to do so (r ≤ 0.18). The average computation time of FLEX-MUSIC was considerably lower compared to a popular Bayesian approach and comparable to that of another recursive MUSIC approach and eLORETA. FLEX-MUSIC produces only few errors and was capable to reliably estimate the extent of sources. The accuracy and low computation time of FLEX-MUSIC renders it an improved technique to solve M/EEG inverse problems both in neuroscience research and potentially in pre-surgery diagnostic in epilepsy.

Preksha Dhyāna Meditation Effect on the DNA Methylation Signature in College Students

Introduction: The stress and psychological factors affect the human transcriptomic and epigenomic landscapes. Preksha Dhyana meditation (PM) was found to be effective, in novice healthy college student meditators, at the cognitive skills and transcriptomic levels. Recently published data showed that PM induced alterations at the transcriptome level in healthy and novice college students. Methods: To decipher potential mechanisms underlying the PM effect at the cellular level, array-based methylation analyses in peripheral blood were performed at baseline and 8 weeks postintervention in 34 participants. Results: Overall, 470 CpG sites were nominally differentially methylated (p ≤ 0.05 and change magnitude from ≥3% to ≤ -3%) between baseline and 8 weeks postintervention with 180 sites hypermethylated and 290 sites hypomethylated. Pathway analysis of the genes linked to the differentially methylated sites revealed the enrichment of several molecular and cellular signaling pathways, especially metabolic and brain function signaling pathways. Conclusions: Besides its beneficial effects on cognitive skills and transcriptome alterations, the current data indicate that PM meditation also affects the DNA methylation profile of novice and healthy college students 8 weeks postintervention. Clinical Trial Registration number: NCT03779269.

Beyond the veil of duality-topographic reorganization model of meditation

Meditation can exert a profound impact on our mental life, with proficient practitioners often reporting an experience free of boundaries between a separate self and the environment, suggesting an explicit experience of "nondual awareness." What are the neural correlates of such experiences and how do they relate to the idea of nondual awareness itself? In order to unravel the effects that meditation has on the brain's spatial topography, we review functional magnetic resonance imaging brain findings from studies specific to an array of meditation types and meditator experience levels. We also review findings from studies that directly probe the interaction between meditation and the experience of the self. The main results are (i) decreased posterior default mode network (DMN) activity, (ii) increased central executive network (CEN) activity, (iii) decreased connectivity within posterior DMN as well as between posterior and anterior DMN, (iv) increased connectivity within the anterior DMN and CEN, and (v) significantly impacted connectivity between the DMN and CEN (likely a nonlinear phenomenon). Together, these suggest a profound organizational shift of the brain's spatial topography in advanced meditators-we therefore propose a topographic reorganization model of meditation (TRoM). One core component of the TRoM is that the topographic reorganization of DMN and CEN is related to a decrease in the mental-self-processing along with a synchronization with the more nondual layers of self-processing, notably interoceptive and exteroceptive-self-processing. This reorganization of the functionality of both brain and self-processing can result in the explicit experience of nondual awareness. In conclusion, this review provides insight into the profound neural effects of advanced meditation and proposes a result-driven unifying model (TRoM) aimed at identifying the inextricably tied objective (neural) and subjective (experiential) effects of meditation.

Deep neural networks constrained by neural mass models improve electrophysiological source imaging of spatiotemporal brain dynamics

Many efforts have been made to image the spatiotemporal electrical activity of the brain with the purpose of mapping its function and dysfunction as well as aiding the management of brain disorders. Here, we propose a non-conventional deep learning-based source imaging framework (DeepSIF) that provides robust and precise spatiotemporal estimates of underlying brain dynamics from noninvasive high-density electroencephalography (EEG) recordings. DeepSIF employs synthetic training data generated by biophysical models capable of modeling mesoscale brain dynamics. The rich characteristics of underlying brain sources are embedded in the realistic training data and implicitly learned by DeepSIF networks, avoiding complications associated with explicitly formulating and tuning priors in an optimization problem, as often is the case in conventional source imaging approaches. The performance of DeepSIF is evaluated by 1) a series of numerical experiments, 2) imaging sensory and cognitive brain responses in a total of 20 healthy subjects from three public datasets, and 3) rigorously validating DeepSIF's capability in identifying epileptogenic regions in a cohort of 20 drug-resistant epilepsy patients by comparing DeepSIF results with invasive measurements and surgical resection outcomes. DeepSIF demonstrates robust and excellent performance, producing results that are concordant with common neuroscience knowledge about sensory and cognitive information processing as well as clinical findings about the location and extent of the epileptogenic tissue and outperforming conventional source imaging methods. The DeepSIF method, as a data-driven imaging framework, enables efficient and effective high-resolution functional imaging of spatiotemporal brain dynamics, suggesting its wide applicability and value to neuroscience research and clinical applications.

Characteristics of Kundalini-Related Sensory, Motor, and Affective Experiences During Tantric Yoga Meditation

Traditional spiritual literature contains rich anecdotal reports of spontaneously arising experiences occurring during meditation practice, but formal investigation of such experiences is limited. Previous work has sometimes related spontaneous experiences to the Indian traditional contemplative concept of kundalini. Historically, descriptions of kundalini come out of Tantric schools of Yoga, where it has been described as a “rising energy” moving within the spinal column up to the brain. Spontaneous meditation experiences have previously been studied within Buddhist and Christian practices and within eclectic groups of contemplative practitioners. Prior explorations of kundalini have emphasized extreme experiences, sometimes having clinical consequences. We conducted a first such investigation of kundalini-related experiences within a sample of meditators from a single Tantric Yoga tradition (known as Ananda Marga) that emphasizes the role of kundalini. We developed a semi-structured questionnaire to conduct an exploratory pilot investigation of spontaneous sensory, motor and affective experiences during meditation practice. In addition to identifying the characteristics of subjective experiences, we measured quantity of meditation, supplemental practices, trait affect and trait mindfulness. We administered it to 80 volunteers at two Ananda Marga retreats. Among reported experiences, we found the highest prevalence for positive mood shifts, followed by motor and then sensory experiences. The frequency of spontaneous experiences was not related to the quantity of practiced meditation or trait measures of mindfulness and affect. Self-reports included multiple descriptions of rising sensations, sometimes being directly called kundalini. Experiences with rising sensations were complex and many included references to positive affect, including ecstatic qualities. There were also reports of spontaneous anomalous experiences. These experiences of rising sensations resemble prior clinical descriptions that were considered kundalini-related. The individuals who reported rising sensations could not be distinguished from other participants based on the incidence of experiences, quantity of meditation practice, or trait measures of mindfulness and affect. In contrast, greater amount of Tantric Yoga meditation practice was associated with greater positive affect, less negative affect and greater mindfulness. Further study of these exploratory findings and how they may be related to spiritual and well-being goals of meditation is warranted along with scientific investigation of purported kundalini phenomena.

Tackling the Electro-Topography of the Selves Through the Sphere Model of Consciousness

In the current hypothesis paper, we propose a novel examination of consciousness and self-awareness through the neuro-phenomenological theoretical model known as the Sphere Model of Consciousness (SMC). Our aim is to create a practical instrument to address several methodological issues in consciousness research. We present a preliminary attempt to validate the SMC via a simplified electrophysiological topographic map of the Self. This map depicts the gradual shift from faster to slower frequency bands that appears to mirror the dynamic between the various SMC states of Self. In order to explore our hypothesis that the SMC's different states of Self correspond to specific frequency bands, we present a mini-review of studies examining the electrophysiological activity that occurs within the different states of Self and in the context of specific meditation types. The theoretical argument presented here is that the SMC's hierarchical organization of three states of the Self mirrors the hierarchical organization of Focused Attention, Open Monitoring, and Non-Dual meditation types. This is followed by testable predictions and potential applications of the SMC and the hypotheses derived from it. To our knowledge, this is the first integrated electrophysiological account that combines types of Self and meditation practices. We suggest this electro-topographic framework of the Selves enables easier, clearer conceptualization of the connections between meditation types as well as increased understanding of wakefulness states and altered states of consciousness.

Mindfulness Practice with a Brain-Sensing Device Improved Cognitive Functioning of Elementary School Children: An Exploratory Pilot Study

This is the first pilot study with children that has assessed the effects of a brain-computer interface-assisted mindfulness program on neural mechanisms and associated cognitive performance. The participants were 31 children aged 9-10 years who were randomly assigned to either an eight-session mindfulness training with EEG-feedback or a passive control group. Mindfulness-related brain activity was measured during the training, while cognitive tests and resting-state brain activity were measured pre- and post-test. The within-group measurement of calm/focused brain states and mind-wandering revealed a significant linear change. Significant positive changes were detected in children's inhibition, information processing, and resting-state brain activity (alpha, theta) compared to the control group. Elevated baseline alpha activity was associated with less reactivity in reaction time on a cognitive test. Our exploratory findings show some preliminary support for a potential executive function-enhancing effect of mindfulness supplemented with EEG-feedback, which may have some important implications for children's self-regulated learning and academic achievement.

Alpha and theta oscillations are inversely related to progressive levels of meditation depth

Meditation training is proposed to enhance mental well-being by modulating neural activity, particularly alpha and theta brain oscillations, and autonomic activity. Although such enhancement also depends on the quality of meditation, little is known about how these neural and physiological changes relate to meditation quality. One model characterizes meditation quality as five increasing levels of ‘depth’: hindrances, relaxation, concentration, transpersonal qualities and nonduality. We investigated the neural oscillatory (theta, alpha, beta and gamma) and physiological (respiration rate, heart rate and heart rate variability) correlates of the self-reported meditation depth in long-term meditators (LTMs) and meditation-naïve controls (CTLs). To determine the neural and physiological correlates of meditation depth, we modelled the change in the slope of the relationship between self-reported experiential degree at each of the five depth levels and the multiple neural and physiological measures. CTLs reported experiencing more ‘hindrances’ than LTMs, while LTMs reported more ‘transpersonal qualities’ and ‘nonduality’ compared to CTLs, confirming the experiential manipulation of meditation depth. We found that in both groups, theta (4–6 Hz) and alpha (7–13 Hz) oscillations were related to meditation depth in a precisely opposite manner. The theta amplitude positively correlated with ‘hindrances’ and increasingly negatively correlated with increasing meditation depth levels. Alpha amplitude negatively correlated with ‘hindrances’ and increasingly positively with increasing depth levels. The increase in the inverse association between theta and meditation depth occurred over different scalp locations in the two groups—frontal midline in LTMs and frontal lateral in CTLs—possibly reflecting the downregulation of two different aspects of executive processing—monitoring and attention regulation, respectively—during deep meditation. These results suggest a functional dissociation of the two classical neural signatures of meditation training, namely, alpha and theta oscillations. Moreover, while essential for overcoming ‘hindrances’, executive neural processing appears to be downregulated during deeper meditation experiences.

Cortical and autonomic responses during staged Taoist meditation: Two distinct meditation strategies

Meditation is a consciousness state associated with specific physiological and neural correlates. Numerous investigations of these correlates reported controversial results which prevented a consistent depiction of the underlying neurophysiological processes. Here we investigated the dynamics of multiple neurophysiological indicators during a staged meditation session. We measured the physiological changes at rest and during the guided Taoist meditation in experienced meditators and naive subjects. We recorded EEG, respiration, galvanic skin response, and photoplethysmography. All subjects followed the same instructions split into 16 stages. In the experienced meditators group we identified two subgroups with different physiological markers dynamics. One subgroup showed several signs of general relaxation evident from the changes in heart rate variability, respiratory rate, and EEG rhythmic activity. The other subgroup exhibited mind concentration patterns primarily noticeable in the EEG recordings while no autonomic responses occurred. The duration and type of previous meditation experience or any baseline indicators we measured did not explain the segregation of the meditators into these two groups. These results suggest that two distinct meditation strategies could be used by experienced meditators, which partly explains the inconsistent results reported in the earlier studies evaluating meditation effects. Our findings are also relevant to the development of the high-end biofeedback systems.

Moral Injury and the Absurd: The suffering of moral paradox

Drawing upon qualitative and construct validity evidence within MI research and the oral histories of combat-exposed Veterans, this paper explores the role of moral paradox (MP) as a precondition of moral injury (MI). Research is recommended to clearly delineate MP as a causative factor leading to more intractable cases of MI in the definitional literature, beyond the recognized impact of perpetration and betrayal-based conditions. Veteran stories collected during the normal course of providing spiritual care to combat-exposed Veterans and used by permission will provide insight into the theoretical concepts and interrelations of MP; proposed here as: circumstances in which moral obligations and/or ethical values come into conflict, forcing a choice between sides, none of which can be honored without violating the other. Acquainted with religious traditions that elucidate the perplexity and liberating effects of paradox, the work of Chaplains will also be recommended to address the problem of MP in wartime situations, highlighting the efficacy of acceptance-based spiritual interventions and therapeutic programs. Psychological and spiritual interventions that facilitate self-transcendence and non-dual awareness through experiential acceptance and a subscale measuring paradox-induced injury will be recommended for future research as well.

A Multivariate Randomized Controlled Experiment about the Effects of Mindfulness Priming on EEG Neurofeedback Self-Regulation Serious Games

Neurofeedback training (NFT) is a technique often proposed to train brain activity SR with promising results. However, some criticism has been raised due to the lack of evaluation, reliability, and validation of its learning effects. The current work evaluates the hypothesis that SR learning may be improved by priming the subject before NFT with guided mindfulness meditation (MM). The proposed framework was tested in a two-way parallel-group randomized controlled intervention with a single session alpha NFT, in a simplistic serious game design. Sixty-two healthy naïve subjects, aged between 18 and 43 years, were divided into MM priming and no-priming groups. Although both the EG and CG successfully attained the up-regulation of alpha rhythms (F(1,59) = 20.67, p < 0.001, ηp2 = 0.26), the EG showed a significantly enhanced ability (t(29) = 4.38, p < 0.001) to control brain activity, compared to the CG (t(29) = 1.18, p > 0.1). Furthermore, EG superior performance on NFT seems to be explained by the subject’s lack of awareness at pre-intervention, less vigour at post-intervention, increased task engagement, and a relaxed non-judgemental attitude towards the NFT tasks. This study is a preliminary validation of the proposed assisted priming framework, advancing some implicit and explicit metrics about its efficacy on NFT performance, and a promising tool for improving naïve “users” self-regulation ability.

Exercise in Aging: Be Balanced

The beneficial effects of exercise are recognized for preventing physical and cognitive decline during the aging process. However, there is still a gap concerning recommended intensity, volume, frequency and mode of exercise especially for older people. The aim of this study was to investigate an appropriate type of physical activity (PA) model for healthy aging. A commentary of the influence of PA and exercise on healthy aging through an online search of the databases Web of Science, PubMed and Google Scholar. Two living groups can be considered as potential references: modern hunter-gatherer small-scale population and master athletes. Greater physical activity is proposed for healthy aging than that recommended by WHO. Additionally, mindfulness meditation techniques during exercise are recommended especially for persons practicing long-duration exercises. Complex and compound exercise and workouts should include challenging exercises adjusted and balanced to provide clients, especially older people, with noticeable changes and progress.

RT-NET: real-time reconstruction of neural activity using high-density electroencephalography

High-density electroencephalography (hdEEG) has been successfully used for large-scale investigations of neural activity in the healthy and diseased human brain. Because of their high computational demand, analyses of source-projected hdEEG data are typically performed offline. Here, we present a real-time noninvasive electrophysiology toolbox, RT-NET, which has been specifically developed for online reconstruction of neural activity using hdEEG. RT-NET relies on the Lab Streaming Layer for acquiring raw data from a large number of EEG amplifiers and for streaming the processed data to external applications. RT-NET estimates a spatial filter for artifact removal and source activity reconstruction using a calibration dataset. This spatial filter is then applied to the hdEEG data as they are acquired, thereby ensuring low latencies and computation times. Overall, our analyses show that RT-NET can estimate real-time neural activity with performance comparable to offline analysis methods. It may therefore enable the development of novel brain–computer interface applications such as source-based neurofeedback.

Examining the Potential Synergistic Effects Between Mindfulness Training and Psychedelic-Assisted Therapy

Mindfulness-based interventions and psychedelic-assisted therapy have been experimentally utilised in recent years as alternative treatments for various psychopathologies with moderate to great success. Both have also demonstrated significant post-acute and long-term decreases in clinical symptoms and enhancements in well-being in healthy participants. These two therapeutic interventions share various postulated salutogenic mechanisms, such as the ability to alter present-moment awareness and anti-depressive action, via corresponding neuromodulatory effects. Recent preliminary evidence has also demonstrated that psychedelic administration can enhance mindfulness capacities which has already been demonstrated robustly as a result of mindfulness-based interventions. These shared mechanisms between mindfulness-based interventions and psychedelic therapy have led to scientists theorising, and recently demonstrating, synergistic effects when both are used in combination, in the form of potentiated therapeutic benefit. These synergistic results hold great promise but require replication in bigger sample groups and better controlled methodologies, to fully delineate the effect of set and setting, before they can be extended onto clinical populations.

On the Neurobiology of Meditation: Comparison of Three Organizing Strategies to Investigate Brain Patterns during Meditation Practice

Three broad organizing strategies have been used to study meditation practices: (1) consider meditation practices as using similar processes and so combine neural images across a wide range of practices to identify the common underlying brain patterns of meditation practice, (2) consider meditation practices as unique and so investigate individual practices, or (3) consider meditation practices as fitting into larger categories and explore brain patterns within and between categories. The first organizing strategy combines meditation practices defined as deep concentration, attention to external and internal stimuli, and letting go of thoughts. Brain patterns of different procedures would all contribute to the final averages, which may not be representative of any practice. The second organizing strategy generates a multitude of brain patterns as each practice is studied individually. The rich detail of individual differences within each practice makes it difficult to identify reliable patterns between practices. The third organizing principle has been applied in three ways: (1) grouping meditations by their origin—Indian or Buddhist practices, (2) grouping meditations by the procedures of each practice, or (3) grouping meditations by brain wave frequencies reported during each practice. Grouping meditations by their origin mixes practices whose procedures include concentration, mindfulness, or effortless awareness, again resulting in a confounded pattern. Grouping meditations by their described procedures yields defining neural imaging patterns within each category, and clear differences between categories. Grouping meditations by the EEG frequencies associated with their procedures yields an objective system to group meditations and allows practices to “move” into different categories as subjects’ meditation experiences change over time, which would be associated with different brain patterns. Exploring meditations within theoretically meaningful categories appears to yield the most reliable picture of meditation practices.

Mindfulness Improves Brain-Computer Interface Performance by Increasing Control Over Neural Activity in the Alpha Band

Brain-computer interfaces (BCIs) are promising tools for assisting patients with paralysis, but suffer from long training times and variable user proficiency. Mind-body awareness training (MBAT) can improve BCI learning, but how it does so remains unknown. Here, we show that MBAT allows participants to learn to volitionally increase alpha band neural activity during BCI tasks that incorporate intentional rest. We trained individuals in mindfulness-based stress reduction (MBSR; a standardized MBAT intervention) and compared performance and brain activity before and after training between randomly assigned trained and untrained control groups. The MBAT group showed reliably faster learning of BCI than the control group throughout training. Alpha-band activity in electroencephalogram signals, recorded in the volitional resting state during task performance, showed a parallel increase over sessions, and predicted final BCI performance. The level of alpha-band activity during the intentional resting state correlated reliably with individuals' mindfulness practice as well as performance on a breath counting task. Collectively, these results show that MBAT modifies a specific neural signal used by BCI. MBAT, by increasing patients' control over their brain activity during rest, may increase the effectiveness of BCI in the large population who could benefit from alternatives to direct motor control.

Meditation and the Wandering Mind: A Theoretical Framework of Underlying Neurocognitive Mechanisms

During the practice of meditation, the tendency of the mind to wander away from the object of focus is ubiquitous. The occurrence of mind wandering in the context of meditation provides individuals a unique and intimate opportunity to closely examine the nature of the wandering mind by cultivating an awareness of ongoing thought patterns, while simultaneously aiming to cultivate equanimity (evenness of temper or disposition) and compassion toward the content of thoughts, interpretations, and bodily sensations. In this article we provide a theoretical framework that highlights the neurocognitive mechanisms by which contemplative practices influence the neural and phenomenological processes underlying spontaneous thought. Our theoretical model focuses on several converging mechanisms: the role of meta-awareness in facilitating an increased moment-to-moment awareness of spontaneous thought processes, the effects of meditation practice on key structures underlying both the top-down cognitive processes and bottom-up sensory processes implicated in attention and emotion regulation, and the influence of contemplative practice on the neural substrates underlying perception and perceptual decoupling.

Nondual Awareness and the Whole Person

Integrative Health aims to treat the whole person and to do so within the context of whole systems and practices. We raise questions as to what constitutes the whole person and what must be taken into account to support the creation of optimal well-being. We propose that in order to fully account for the whole person, the transcendent aspects of human awareness, the development of which is the goal of many meditative traditions, must be taken into account. “Nondual awareness” is a term increasingly used in the literature to describe a state of awareness that is characterized by the experience of nonseparation, compassion, and love. Well-being in this state does not depend on anything being experienced per se, but it is rather an innate attribute of living in nonduality. For these reasons, nondual awareness can be considered foundational to the realization of the whole person and achieving the state of optimal well-being.

Brainwave Self-Regulation During Bispectral IndexTM Neurofeedback in Trauma Center Nurses and Physicians After Receiving Mindfulness Instructions

Fifty-seven level I trauma center nurses/physicians participated in a 4-day intervention to learn relaxed alertness using mindfulness-based instructions and EEG neurofeedback. Neurofeedback was provided by a Bispectral Index^TM (BIS) system that continuously displays a BIS value (0-100) on the monitor screen. Reductions in the BIS value indicate that power in a high-frequency band (30-47 Hz) is decreased and power in an intermediate band (11-20 Hz) is increased. A wellbeing tool with four positive affect and seven negative affect items based on a 5-category Likert scale was used. The wellbeing score is the sum of the positive affect items (positive affect score) and the reverse-scored negative affect items (non-stress score). Of functional concern were four negative affect items rated as moderately, quite a bit, or extremely in a large percent. Of greater concern were all four positive affect items rated as very slightly or none at all, a little, or moderately in over half of the participants. Mean and nadir BIS values were markedly decreased during neurofeedback when compared to baseline values. Post-session relaxation scores were higher than pre-session relaxation scores. Post-session relaxation scores had an inverse relationship with mean and nadir BIS values. Mean and nadir BIS values were inversely associated with NFB cognitive states (i.e., widening the visual field, decreasing effort, attention to space, and relaxed alertness). For all participants, the wellbeing score was higher on day 4 than on day 1. Participants had a higher wellbeing score on day 4 than a larger group of nurses/physicians who did not participate in the BIS neurofeedback trial. Eighty percent of participants demonstrated an improvement in the positive affect or non-stress score on day 4, when compared to day 1; the wellbeing, non-stress, and positive affect scores were substantially higher on day 4 than on day 1. Additionally, for that 80% of participants, the improvements in wellbeing and non-stress were associated with reductions in day 3 BIS values. These findings indicate that trauma center nurses/physicians participating in an EEG neurofeedback trial with mindfulness instructions had improvements in wellbeing. Clinical Trial Registration: www.ClinicalTrials.gov, identifier NCT03152331. Registered May 15, 2017.

Neurofeedback: Principles, appraisal, and outstanding issues

Neurofeedback is a form of brain training in which subjects are fed back information about some measure of their brain activity which they are instructed to modify in a way thought to be functionally advantageous. Over the last 20 years, neurofeedback has been used to treat various neurological and psychiatric conditions, and to improve cognitive function in various contexts. However, in spite of a growing popularity, neurofeedback protocols typically make (often covert) assumptions on what aspects of brain activity to target, where in the brain to act and how, which have far-reaching implications for the assessment of its potential and efficacy. Here we critically examine some conceptual and methodological issues associated with the way neurofeedback's general objectives and neural targets are defined. The neural mechanisms through which neurofeedback may act at various spatial and temporal scales, and the way its efficacy is appraised are reviewed, and the extent to which neurofeedback may be used to control functional brain activity discussed. Finally, it is proposed that gauging neurofeedback's potential, as well as assessing and improving its efficacy will require better understanding of various fundamental aspects of brain dynamics and a more precise definition of functional brain activity and brain-behaviour relationships.

From research to clinic: A sensor reduction method for high-density EEG neurofeedback systems

OBJECTIVE

To accurately deliver a source-estimated neurofeedback (NF) signal developed on a 128-sensors EEG system on a reduced 32-sensors EEG system.

METHODS

A linearly constrained minimum variance beamformer algorithm was used to select the 64 sensors which contributed most highly to the source signal. Monte Carlo-based sampling was then used to randomly generate a large set of reduced 32-sensors montages from the 64 beamformer-selected sensors. The reduced montages were then tested for their ability to reproduce the 128-sensors NF. The high-performing montages were then pooled and analyzed by a k-means clustering machine learning algorithm to produce an optimized reduced 32-sensors montage.

RESULTS

Nearly 4500 high-performing montages were discovered from the Monte Carlo sampling. After statistically analyzing this pool of high performing montages, a set of refined 32-sensors montages was generated that could reproduce the 128-sensors NF with greater than 80% accuracy for 72% of the test population.

CONCLUSION

Our Monte Carlo reduction method was used to create reliable reduced-sensors montages which could be used to deliver accurate NF in clinical settings.

SIGNIFICANCE

A translational pathway is now available by which high-density EEG-based NF measures can be delivered using clinically accessible low-density EEG systems.

Improving efficiency in neuroimaging research through application of Lean principles

INTRODUCTION

"Lean" is a set of management principles which focus on increasing value and efficiency by reducing or avoiding waste (e.g., overproduction, defects, inventory, transportation, waiting, motion, over processing). It has been applied to manufacturing, education, and health care, leading to optimized process flow, increased efficiency and increased team empowerment. However, to date, it has not been applied to neuroimaging research.

METHODS

Lean principles, such as Value stream mapping (e.g. a tool with which steps in the workflow can be identified on which to focus improvement efforts), 5S (e.g. an organizational method to boost workplace efficiency and efficacy) and Root-cause analysis (e.g. a problem-solving approach to identify key points of failure in a system) were applied to an ongoing, large neuroimaging study that included seven research visits per participant. All team members participated in a half-day exercise in which the entire project flow was visualized and areas of inefficiency were identified. Changes focused on removing obstacles, standardization, optimal arrangement of equipment and root-cause-analysis. A process for continuous improvement was also implemented. Total time of an experiment was recorded before implementation of Lean for two participants and after implementation of Lean for two participants. Satisfaction of team members was assessed anonymously on a 5-item Likert scale, ranging from much worsened to much improved.

RESULTS

All team members (N = 6) considered the overall experience of conducting an experiment much improved after implementation of Lean. Five out of six team members indicated a much-improved reduction in time, with the final team member considering this somewhat improved. Average experiment time was reduced by 13% after implementation of Lean (from 142 and 147 minutes to 124 and 128 minutes).

DISCUSSION

Lean principles can be successfully applied to neuroimaging research. Training in Lean principles for junior research scientists is recommended.

Can Mindfulness Address Maladaptive Eating Behaviors? Why Traditional Diet Plans Fail and How New Mechanistic Insights May Lead to Novel Interventions

Emotional and other maladaptive eating behaviors develop in response to a diversity of triggers, from psychological stress to the endless external cues in our modern food environment. While the standard approach to food- and weight-related concerns has been weight-loss through dietary restriction, these interventions have produced little long-term benefit, and may be counterproductive. A growing understanding of the behavioral and neurobiological mechanisms that underpin habit formation may explain why this approach has largely failed, and pave the way for a new generation of non-pharmacologic interventions. Here, we first review how modern food environments interact with human biology to promote reward-related eating through associative learning, i.e., operant conditioning. We also review how operant conditioning (positive and negative reinforcement) cultivates habit-based reward-related eating, and how current diet paradigms may not directly target such eating. Further, we describe how mindfulness training that targets reward-based learning may constitute an appropriate intervention to rewire the learning process around eating. We conclude with examples that illustrate how teaching patients to tap into and act on intrinsic (e.g., enjoying healthy eating, not overeating, and self-compassion) rather than extrinsic reward mechanisms (e.g., weighing oneself), is a promising new direction in improving individuals' relationship with food.

Virtual Reality for Anxiety Reduction Demonstrated by Quantitative EEG: A Pilot Study

While previous research has established that virtual reality (VR) can be successfully used in the treatment of anxiety disorders, including phobias and PTSD, no research has examined changes in brain patterns associated with the use of VR for generalized anxiety management. In the current study, we compared a brief nature-based mindfulness VR experience to a resting control condition on anxious participants. Self-reported anxiety symptoms and resting-state EEG were recorded across intervals containing quiet rest or the VR intervention. EEG activity was analyzed as a function of global power shifts in Alpha and Beta activity, and with sLORETA current source density estimates of cingulate cortex regions of interest. Results demonstrated that both a quiet rest control condition and the VR meditation significantly reduced subjective reports of anxiety and increased Alpha power. However, the VR intervention uniquely resulted in shifting proportional power from higher Beta frequencies into lower Beta frequencies, and significantly reduced broadband Beta activity in the anterior cingulate cortex. These effects are consistent with a physiological reduction of anxiety. This pilot study provides preliminary evidence supporting the therapeutic potential of VR for anxiety management and stress reduction programs.

Mindfulness-based treatment of addiction: current state of the field and envisioning the next wave of research

Contemporary advances in addiction neuroscience have paralleled increasing interest in the ancient mental training practice of mindfulness meditation as a potential therapy for addiction. In the past decade, mindfulness-based interventions (MBIs) have been studied as a treatment for an array addictive behaviors, including drinking, smoking, opioid misuse, and use of illicit substances like cocaine and heroin. This article reviews current research evaluating MBIs as a treatment for addiction, with a focus on findings pertaining to clinical outcomes and biobehavioral mechanisms. Studies indicate that MBIs reduce substance misuse and craving by modulating cognitive, affective, and psychophysiological processes integral to self-regulation and reward processing. This integrative review provides the basis for manifold recommendations regarding the next wave of research needed to firmly establish the efficacy of MBIs and elucidate the mechanistic pathways by which these therapies ameliorate addiction. Issues pertaining to MBI treatment optimization and sequencing, dissemination and implementation, dose–response relationships, and research rigor and reproducibility are discussed.

Controlling the Temporal Structure of Brain Oscillations by Focused Attention Meditation

Our focus of attention naturally fluctuates between different sources of information even when we desire to focus on a single object. Focused attention (FA) meditation is associated with greater control over this process, yet the neuronal mechanisms underlying this ability are not entirely understood. Here, we hypothesize that the capacity of attention to transiently focus and swiftly change relates to the critical dynamics emerging when neuronal systems balance at a point of instability between order and disorder. In FA meditation, however, the ability to stay focused is trained, which may be associated with a more homogeneous brain state. To test this hypothesis, we applied analytical tools from criticality theory to EEG in meditation practitioners and meditation-naïve participants from two independent labs. We show that in practitioners-but not in controls-FA meditation strongly suppressed long-range temporal correlations (LRTC) of neuronal oscillations relative to eyes-closed rest with remarkable consistency across frequency bands and scalp locations. The ability to reduce LRTC during meditation increased after one year of additional training and was associated with the subjective experience of fully engaging one's attentional resources, also known as absorption. Sustained practice also affected normal waking brain dynamics as reflected in increased LRTC during an eyes-closed rest state, indicating that brain dynamics are altered beyond the meditative state. Taken together, our findings suggest that the framework of critical brain dynamics is promising for understanding neuronal mechanisms of meditative states and, specifically, we have identified a clear electrophysiological correlate of the FA meditation state.

The brain on silent: mind wandering, mindful awareness, and states of mental tranquility

Mind wandering and mindfulness are often described as divergent mental states with opposing effects on cognitive performance and mental health. Spontaneous mind wandering is typically associated with self-reflective states that contribute to negative processing of the past, worrying/fantasizing about the future, and disruption of primary task performance. On the other hand, mindful awareness is frequently described as a focus on present sensory input without cognitive elaboration or emotional reactivity, and is associated with improved task performance and decreased stress-related symptomology. Unfortunately, such distinctions fail to acknowledge similarities and interactions between the two states. Instead of an inverse relationship between mindfulness and mind wandering, a more nuanced characterization of mindfulness may involve skillful toggling back and forth between conceptual and nonconceptual processes and networks supporting each state, to meet the contextually specified demands of the situation. In this article, we present a theoretical analysis and plausible neurocognitive framework of the restful mind, in which we attempt to clarify potentially adaptive contributions of both mind wandering and mindful awareness through the lens of the extant neurocognitive literature on intrinsic network activity, meditation, and emerging descriptions of stillness and nonduality. A neurophenomenological approach to probing modality-specific forms of concentration and nonconceptual awareness is presented that may improve our understanding of the resting state. Implications for future research are discussed.

Meditation is associated with increased brain network integration

INTRODUCTION

This study aims to identify novel quantitative EEG measures associated with mindfulness meditation. As there is some evidence that meditation is associated with higher integration of brain networks, we focused on EEG measures of network integration.

METHODS

Sixteen novice meditators and sixteen experienced meditators participated in the study. Novice meditators performed a basic meditation practice that supported effortless awareness, which is an important quality of experience related to mindfulness practices, while their EEG was recorded. Experienced meditators performed a self-selected meditation practice that supported effortless awareness. Network integration was analyzed with maximum betweenness centrality and leaf fraction (which both correlate positively with network integration) as well as with diameter and average eccentricity (which both correlate negatively with network integration), based on a phase-lag index (PLI) and minimum spanning tree (MST) approach. Differences between groups were assessed using repeated-measures ANOVA for the theta (4-8 Hz), alpha (8-13 Hz) and lower beta (13-20 Hz) frequency bands.

RESULTS

Maximum betweenness centrality was significantly higher in experienced meditators than in novices (P = 0.012) in the alpha band. In the same frequency band, leaf fraction showed a trend toward being significantly higher in experienced meditators than in novices (P = 0.056), while diameter and average eccentricity were significantly lower in experienced meditators than in novices (P = 0.016 and P = 0.028 respectively). No significant differences between groups were observed for the theta and beta frequency bands.

CONCLUSION

These results show that alpha band functional network topology is better integrated in experienced meditators than in novice meditators during meditation. This novel finding provides the rationale to investigate the temporal relation between measures of functional connectivity network integration and meditation quality, for example using neurophenomenology experiments.