Review of the Neural Oscillations Underlying Meditation

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.

ENIGMA-Meditation: Worldwide Consortium for Neuroscientific Investigations of Meditation Practices

Meditation is a family of ancient and contemporary contemplative mind-body practices that can modulate psychological processes, awareness, and mental states. Over the last 40 years, clinical science has manualized meditation practices and designed various meditation interventions that have shown therapeutic efficacy for disorders including depression, pain, addiction, and anxiety. Over the past decade, neuroimaging has been used to examine the neuroscientific basis of meditation practices, effects, states, and outcomes for clinical and nonclinical populations. However, the generalizability and replicability of current neuroscientific models of meditation have not yet been established, because they are largely based on small datasets entrenched with heterogeneity along several domains of meditation (e.g., practice types, meditation experience, clinical disorder targeted), experimental design, and neuroimaging methods (e.g., preprocessing, analysis, task-based, resting-state, structural magnetic resonance imaging). These limitations have precluded a nuanced and rigorous neuroscientific phenotyping of meditation practices and their potential benefits. Here, we present ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis)-Meditation, the first worldwide collaborative consortium for neuroscientific investigations of meditation practices. ENIGMA-Meditation will enable systematic meta- and mega-analyses of globally distributed neuroimaging datasets of meditation using shared, standardized neuroimaging methods and tools to improve statistical power and generalizability. Through this powerful collaborative framework, existing neuroscientific accounts of meditation practices can be extended to generate novel and rigorous neuroscientific insights that account for multidomain heterogeneity. ENIGMA-Meditation will inform neuroscientific mechanisms that underlie therapeutic action of meditation practices on psychological and cognitive attributes, thereby advancing the field of meditation and contemplative neuroscience.

Research on visual comfort of color matching in space station experiment module

Considering the living environment, appropriate color adjustment has a positive effect on improving the visual comfort of astronauts, promoting their physical and mental health, and enhancing work efficiency. This article takes the Chinese space station experimental module as a prototype, and through simulation experiments, uses a method that combines physiological signals with subjective evaluation to compare the differences in the impact of 9 different color matching schemes on human visual comfort. The results showed that using 2-3 colors for pairing resulted in the highest visual comfort for people, and people were more willing to choose cool, white, or cool, warm, and white combinations. Among them, spaces using blue, green, and white combinations could help alleviate visual fatigue, while spaces using yellow, green, and white combinations could help people maintain or form a good psychological state. Finally, the experimental results were discussed, and prospects for the future development and construction of space stations were discussed.

Oscillating Mindfully: Using Machine Learning to Characterize Systems-Level Electrophysiological Activity During Focused Attention Meditation

Background

There has been rapid growth of neuroelectrophysiological studies that aspire to uncover the "black box" of mindfulness and meditation. Reliance on traditional data analysis methods hinders understanding of the complex, nonlinear, multidimensional, and systemic nature of the functional neuroelectrophysiology of meditation states.

Methods

Thus, to reveal the complex systemic neuroelectrophysiology of meditation, we applied a machine learning extreme gradient boosting classification algorithm and 4 complementary feature importance methods to extract systemic electroencephalography features characterizing mindful states from electroencephalography recorded during a focused attention meditation and a control mind-wandering state among 26 experienced meditators.

Results

The algorithm classified meditation versus mind-wandering states with 83% accuracy, with an area under the receiver operating characteristic curve of 79% and F1 score of 74%. Feature importance techniques identified 10 electroencephalography features associated with increased power and coherence of high-frequency oscillations during focused attention meditation relative to an instructed mind-wandering state.

Conclusions

The findings help delineate the complex systemic oscillatory activity that characterizes meditation.

Novel machine learning-driven comparative analysis of CSP, STFT, and CSP-STFT fusion for EEG data classification across multiple meditation and non-meditation sessions in BCI pipeline

This study focuses on classifying multiple sessions of loving kindness meditation (LKM) and non-meditation electroencephalography (EEG) data. This novel study focuses on using multiple sessions of EEG data from a single individual to train a machine learning pipeline, and then using a new session data from the same individual for the classification. Here, two meditation techniques, LKM-Self and LKM-Others were compared with non-meditation EEG data for 12 participants. Among many tested, three BCI pipelines we built produced promising results, successfully detecting features in meditation/ non-meditation EEG data. While testing different feature extraction algorithms, a common neural network structure was used as the classification algorithm to compare the performance of the feature extraction algorithms. For two of those pipelines, Common Spatial Patterns (CSP) and Short Time Fourier Transform (STFT) were successfully used as feature extraction algorithms where both these algorithms are significantly new for meditation EEG. As a novel concept, the third BCI pipeline used a feature extraction algorithm that fused the features of CSP and STFT, achieving the highest classification accuracies among all tested pipelines. Analyses were conducted using EEG data of 3, 4 or 5 sessions, totaling 3960 tests on the entire dataset. At the end of the study, when considering all the tests, the overall classification accuracy using SCP alone was 67.1%, and it was 67.8% for STFT alone. The algorithm combining the features of CSP and STFT achieved an overall classification accuracy of 72.9% which is more than 5% higher than the other two pipelines. At the same time, the highest mean classification accuracy for the 12 participants was achieved using the pipeline with the combination of CSP STFT algorithm, reaching 75.5% for LKM-Self/ non-meditation for the case of 5 sessions of data. Additionally, the highest individual classification accuracy of 88.9% was obtained by the participant no. 14. Furthermore, the results showed that the classification accuracies for all three pipelines increased with the number of training sessions increased from 2 to 3 and then to 4. The study was successful in classifying a new session of EEG meditation/ non-meditation data after training machine learning algorithms using a different set of session data, and this achievement will be beneficial in the development of algorithms that support meditation.

Immersive gamma music as a tool for enhancing glymphatic clearance in astronauts while improving their mental well-being

Spaceflight occurs under extreme environmental conditions that pose significant risks to the physical and mental health and well-being of astronauts. Certain factors, such as prolonged isolation, monotony, disrupted circadian rhythms, heavy workload, and weightlessness in space, can trigger psychological distress and may contribute to a variety of mental health problems, including mood and anxiety disturbances. Recent findings regarding spaceflight-associated alterations in cerebrospinal fluid spaces, demonstrating enlargement of the brain's perivascular spaces from preflight to postflight, at least suggest reduced glymphatic clearance in microgravity, and have raised concerns about long-term cognitive health in astronauts. Therefore, it is critical for future long-duration human exploration missions to identify, develop and validate all potentially effective long-term countermeasures capable of reducing the risk of perivascular space enlargement and impaired glymphatic transport in space mission crews. Furthermore, it is crucial to implement effective strategies that would allow crew members to maintain optimal psychological well-being during future long-duration space exploration. In the present paper, we propose "immersive gamma music" as an add-on countermeasure that in combination with existing countermeasures can optimize glymphatic clearance in astronauts while improving their mental well-being. If confirmed, this approach could enrich the practice of space medicine, and might become increasingly important, given the plans for future human missions, including a return to the Moon and manned missions to Mars.

Brain Wave Oscillations as an Objective Neurophysiological Biomarker of Homeopathic Subjective Well-Being

BACKGROUND

 Homeopathy uses the "similitude principle" to arouse a therapeutic reaction in the body against its own disorders. For this to occur optimally, the medicinal pathogenetic effects must present similarity with the totality of the individual's symptoms. To assess if this similarity has been successfully achieved, Hahnemann states that "improvement in the disposition and mind"-i.e., subjective well-being-is the most important parameter to consider.

AIM

 Our aim was to perform a narrative review of the literature, exploring what is known about subjective well-being as a marker of therapeutic action, and to formulate ways in which subjective well-being might be quantifiable and applied in future homeopathy research.

RESULTS

 The concept of subjective well-being has been extensively studied in the complementary and conventional medical literature. Improved well-being has been observed in clinical trials, including those in the fields of positive psychology and meditation. Positive subjective outcomes of this nature are supported by objective evidence through associated changes in brain oscillatory activity using electroencephalography and/or "brain mapping" by functional magnetic resonance imaging. Neurophysiological responses in the brain have been identified in subjects after they ingested a homeopathic medicine.

CONCLUSIONS

 The concept of subjective well-being is supported by a body of literature and is a measurable entity. When viewed from the perspective of electrophysiological changes, brain activity is an objective neurophysiological biomarker with a potential to quantify individual well-being in the context of homeopathy research.

Multimodal neurophenomenology of advanced concentration absorption meditation: An intensively sampled case study of Jhana

Using a combination of fMRI, EEG, and phenomenology ratings, we examined the neurophenomenology of advanced concentrative absorption meditation, namely jhanas (ACAM-J), in a practitioner with over 23,000 h of meditation practice. Our study shows that ACAM-J states induce reliable changes in conscious experience and that these experiences are related to neural activity. Using resting-state fMRI functional connectivity, we found that ACAM-J is associated with decreased within-network modularity, increased global functional connectivity (GFC), and desegregation of the default mode and visual networks. Compared to control tasks, the ACAM-J were also related to widespread decreases in broadband EEG oscillatory power and increases in Lempel-Ziv complexity (LZ, a measure of brain entropy). Some fMRI findings varied by the control task used, while EEG results remained consistent, emphasizing both shared and unique neural features of ACAM-J. These differences in fMRI and EEG-measured neurophysiological properties correlated with specific changes in phenomenology - and especially with ACAM-J-induced states of bliss - enriching our understanding of these advanced meditative states. Our results show that advanced meditation practices markedly dysregulate high-level brain systems via practices of enhanced attention to sensations, corroborating recent neurocognitive theories of meditation as the deconstruction of the brain's cortical hierarchy. Overall, our results suggest that ACAM-J is associated with the modulation of large-scale brain networks in both fMRI and EEG, with potential implications for understanding the mechanisms of deep concentration practices and their effects on subjective experience.

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.

Influence of mindfulness meditation on intracranial EEG parameters in epileptic and non-epileptic brain areas

OBJECTIVE

Mind-wandering is a pervasive human brain state and, when in excess, may promote negative affect and neuropsychiatric conditions. Mindfulness meditation may promote alternate brain states, improving affect and reducing stress. An understanding of the neural basis between these brain states could thus advance treatment of neuropsychiatric conditions, including those associated with epilepsy.

METHODS

To explore the neural basis of mindfulness meditation versus mind-wandering, we enrolled eight patients in a trial of structured mindfulness meditation and open mind-wandering who underwent stereo electroencephalography (sEEG) within the mesial temporal lobe for seizure localization. Electrophysiology was compared between mind-wandering and mindfulness separately for epileptic and non-epileptic MTL. Using fitting-one-over-f modeling, periodic components of electrophysiology were compared in canonical frequency bands of theta (4-8 Hz), alpha (8-13 Hz), beta (13-30 Hz), and gamma (30-55 Hz). Aperiodic components of the power spectra were assessed by the model offset, knee, and exponent.

RESULTS

We found a significant reduction in gamma power (30-55 Hz) within the mesial temporal lobe (MTL) during mindfulness meditation compared with mind-wandering in non-epileptic (p = 1.20E-4) but not in epileptic MTL (p = 0.352).There was also a significant difference between epileptic versus non-epileptic MTL in gamma power between conditions (p = 0.011). There were no significant changes in power across any frequency band within epileptic mesial temporal MTL between brain states. Conversely, there were significant differences between mind-wandering and mindfulness within epileptic MTL in aperiodic components (offset, knee, and exponent, all p < 0.05), while no differences in aperiodic components were seen in non-epileptic MTL (all p > 0.70).

SIGNIFICANCE

Intracranial electrophysiologic modulations between brain state (mind-wandering versus mindfulness) may differ between epileptic and non-epileptic MTL. Modulations in gamma activity in non-epileptic MTL may represent functional changes in brain state, while aperiodic changes in epileptic MTL may modulate propensity for seizures.

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.

The gamma rhythm as a guardian of brain health

Gamma oscillations in brain activity (30-150 Hz) have been studied for over 80 years. Although in the past three decades significant progress has been made to try to understand their functional role, a definitive answer regarding their causal implication in perception, cognition, and behavior still lies ahead of us. Here, we first review the basic neural mechanisms that give rise to gamma oscillations and then focus on two main pillars of exploration. The first pillar examines the major theories regarding their functional role in information processing in the brain, also highlighting critical viewpoints. The second pillar reviews a novel research direction that proposes a therapeutic role for gamma oscillations, namely the gamma entrainment using sensory stimulation (GENUS). We extensively discuss both the positive findings and the issues regarding reproducibility of GENUS. Going beyond the functional and therapeutic role of gamma, we propose a third pillar of exploration, where gamma, generated endogenously by cortical circuits, is essential for maintenance of healthy circuit function. We propose that four classes of interneurons, namely those expressing parvalbumin (PV), vasointestinal peptide (VIP), somatostatin (SST), and nitric oxide synthase (NOS) take advantage of endogenous gamma to perform active vasomotor control that maintains homeostasis in the neuronal tissue. According to this hypothesis, which we call GAMER (GAmma MEdiated ciRcuit maintenance), gamma oscillations act as a 'servicing' rhythm that enables efficient translation of neural activity into vascular responses that are essential for optimal neurometabolic processes. GAMER is an extension of GENUS, where endogenous rather than entrained gamma plays a fundamental role. Finally, we propose several critical experiments to test the GAMER hypothesis.

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.

Home-based EEG Neurofeedback for the Treatment of Chronic Pain: A Randomized Controlled Clinical Trial

This parallel, 2-arm, blinded, randomized controlled superiority trial examined whether, when added to usual care, active-electroencephalography neurofeedback (EEG NFB) was safe and more effective than sham control-EEG NFB for chronic pain. In total, 116 participants with chronic pain were randomly assigned (1:1) to usual care plus ≥32 sessions of active-EEG NFB upregulating relative alpha power over C4 or usual care plus ≥32 sessions of sham control-EEG NFB. Per-protocol analyses revealed no significant between-group differences in the primary outcome, Brief Pain Inventory average pain (mean difference [95% confidence interval]: -.04 [-.39 to .31], P = .90), or any secondary outcomes. However, 44% of participants in the active-EEG NFB group and 45% in the control-EEG NFB group reported at least a moderate (≥30%), clinically important improvement in Brief Pain Inventory average pain. The number of treatment-emergent adverse events were similar in both groups (P = .83), and none were serious. Post hoc analyses revealed similar upregulated relative alpha power in both groups during training, with concordant positive rewards delivered to the active-EEG group 100% of the time and the control-EEG group ∼25% of the time, suggesting a partially active sham intervention. When added to usual care, the active-EEG NFB intervention used in this study was not superior to the sham control-EEG NFB intervention. However, a large proportion of participants in both groups reported a clinically important reduction in pain intensity. A partially active sham intervention may have obscured between-group differences. The intervention was free of important side effects, with no safety concerns identified. PERSPECTIVE: This study is the first attempt at an appropriately blinded, randomized, sham-controlled trial of alpha EEG NFB for the treatment of chronic pain. The findings may interest people living with chronic pain, clinicians involved in chronic pain management, and may inform the design of future EEG NFB trials. TRIAL REGISTRATION: Australian New Zealand Clinical Trials Registry (ANZCTR): ACTRN12621000667819.

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.

Art, meditation and cognitive science: a framework for museum-based community meditation programme during the COVID-19 pandemic in Singapore

In 2020, the COVID-19 pandemic caused mandatory lockdowns worldwide, exacerbating mental health issues created by social isolation. Aimed to improve mental health and maintain engagement, the Singapore Art Museum (SAM) rapidly deployed an online programme called Unwind with SAM to engage the public with the museum's contemporary art collection coupled with meditation. The programme focused on the positive effect of arts on mental health, combined with the cognitive benefits of meditation by 'slow-looking' at artworks. This practice-based report reflects on the processes and explores the potential between art, contemplation and cognitive sciences. The first section outlines the current landscape of art and wellness approaches in museums. The second section explains the philosophical framework that guides the programme, alongside a breakdown of components and design rationale. The final part provides a critical reflection and concludes with recommendations for practitioners, managers and scientists to utilise the framework for designing future programmes.

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).

Spatiotemporal whole-brain activity and functional connectivity of melodies recognition

Music is a non-verbal human language, built on logical, hierarchical structures, that offers excellent opportunities to explore how the brain processes complex spatiotemporal auditory sequences. Using the high temporal resolution of magnetoencephalography, we investigated the unfolding brain dynamics of 70 participants during the recognition of previously memorized musical sequences compared to novel sequences matched in terms of entropy and information content. Measures of both whole-brain activity and functional connectivity revealed a widespread brain network underlying the recognition of the memorized auditory sequences, which comprised primary auditory cortex, superior temporal gyrus, insula, frontal operculum, cingulate gyrus, orbitofrontal cortex, basal ganglia, thalamus, and hippocampus. Furthermore, while the auditory cortex responded mainly to the first tones of the sequences, the activity of higher-order brain areas such as the cingulate gyrus, frontal operculum, hippocampus, and orbitofrontal cortex largely increased over time during the recognition of the memorized versus novel musical sequences. In conclusion, using a wide range of analytical techniques spanning from decoding to functional connectivity and building on previous works, our study provided new insights into the spatiotemporal whole-brain mechanisms for conscious recognition of auditory sequences.

Network analysis of meditative states in highly skilled meditators using EEG and horizontal visibility graphs

The benefits of meditation are increasingly recognized, and some forms are now used for clinical intervention. However, the electrophysiological correlates of meditative states are not yet well understood, and the limited predictive accuracy of known markers of meditation suggest that not all information relevant to meditation has been captured by previous work.Here, we convert electroencephalography (EEG) time series into scale-free networks using horizontal visibility graphs (HVGs), which are well-suited to distinguishing deterministic dynamical systems from stochastic systems, allowing them to model novel aspects of cortical oscillatory activity. Based on HVGs, we introduce and evaluate a general class of predictors, which can be used to augment existing features in contemplative neuroscience, and exhibit high predictive power for several types of meditation.We show the statistical significance of these network predictors - and their increased performance compared to popular spectral and non-linear features such as complexity or entropy - on data from highly skilled meditators, in a continuous setting applicable to real-time analysis and applications such as neurofeedback.

Global Effect on Cortical Activity in Young Indian Males in Response to "OM" Chanting: A High-Density Quantitative Electro-Encephalography Study

Background

Meditation using the "OM" mantra is the most widely used practice in India. Though reports have been published about the relaxation effect during both verbal "OM" chanting and listening to "OM" chanting, there is a paucity of literature concerning the cortical areas activated/deactivated after verbal "OM" chanting and listening to "OM" chanting using quantitative electro-encephalography (qEEG).

Purpose

The objective of this study was to compare the effects of verbal "OM" chanting and listening to "OM" chanting on cortical sources as compared to baseline, as assessed by qEEG.

Method

Twenty adult male subjects with a mean age of 27.5 ± 7.5 years and no past or present history of psychiatric, neurological, or auditory disorders or previous exposure to yoga and meditation were recruited from the undergraduate and postgraduate student population of AIIMS, New Delhi. Subjects were given a paradigm designed using E-prime for both verbal and listening to "OM" chanting of 5 min each and a 5-min relaxation period in between the tasks. Electroencephalography recording was done using a 128-channel geodesic sensor net with band-pass filtered at 1-70 Hz, and 20-sec data of eyes-closed condition, post-verbal "OM", and post-listening to "OM" chanting were segmented and pre-processed. Further, source analysis was performed on the data using standardized low-resolution electromagnetic tomography.

Result

The pre (baseline) versus post-verbal "OM" (p < .05) and post-listening to "OM" (p < .05) chanting showed significant differences in similar cortical areas in both verbal "OM" and listening to "OM" chanting except the three areas, that is, the orbital gyrus, the rectal gyrus, and the sub-callosal gyrus, which were additionally activated post-listening to "OM" chanting. Both verbal and listening to "OM" chanting induced activation of similar cortical areas, which were classified as the nodes/hubs of specific resting-state networks (RSNs) such as the attentional network, frontoparietal control network, and default mode network.

Conclusion

The study results suggest that "OM" chanting could facilitate flexible switching between various RSNs to induce a relaxed state and could improve attention simultaneously.Both verbal and listening to "OM" chanting induced common activated areas that are classified into frontoparietal, dorsal attention, and default mode network areas. And it is hypothesized that flexible switching between these RSNs could induce a relaxed state and improve attention simultaneously with the possible role of the frontoparietal network.

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.

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

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

Report from a Tibetan Monastery: EEG neural correlates of concentrative and analytical meditation

The positive effects of meditation on human wellbeing are indisputable, ranging from emotion regulation improvement to stress reduction and present-moment awareness enhancement. Changes in brain activity regulate and support these phenomena. However, the heterogeneity of meditation practices and their cultural background, as well as their poor categorization limit the generalization of results to all types of meditation. Here, we took advantage of a collaboration with the very singular and precious community of the Monks and Geshes of the Tibetan University of Sera-Jey in India to study the neural correlates of the two main types of meditation recognized in Tibetan Buddhism, namely concentrative and analytical meditation. Twenty-three meditators with different levels of expertise underwent to an ecological (i.e., within the monastery) EEG acquisition consisting of an analytical and/or concentrative meditation session at "their best," and with the only constraint of performing a 5-min-long baseline at the beginning of the session. Time-varying power-spectral-density estimates of each session were compared against the baseline (i.e., within session) and between conditions (i.e., analytical vs. concentrative). Our results showed that concentrative meditation elicited more numerous and marked changes in the EEG power compared to analytical meditation, and mainly in the form of an increase in the theta, alpha and beta frequency ranges. Moreover, the full immersion in the Monastery life allowed to share the results and discuss their interpretation with the best scholars of the Monastic University, ensuring the identification of the most expert meditators, as well as to highlight better the differences between the different types of meditation practiced by each of them.

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.

The potential of 5-methoxy-N,N-dimethyltryptamine in the treatment of alcohol use disorder: A first look at therapeutic mechanisms of action

Alcohol use disorder (AUD) remains one of the most prevalent psychiatric disorders worldwide with high economic costs. Current treatment options show modest efficacy and relapse rates are high. Furthermore, there are increases in the treatment gap and few new medications have been approved in the past 20 years. Recently, psychedelic-assisted therapy with psilocybin and lysergic acid diethylamide has garnered significant attention in the treatment of AUD. Yet, they require significant amounts of therapist input due to prolonged subjective effects (~4-12 h) leading to high costs and impeding implementation. Accordingly, there is an increasing interest in the rapid and short-acting psychedelic 5-methoxy-N,N-dimethyltryptamine (5-MeO-DMT). This paper offers a first look at potential therapeutic mechanisms for AUD by reviewing the current literature on 5-MeO-DMT. Primarily, 5-MeO-DMT is able to induce mystical experiences and ego-dissolution together with increases in psychological flexibility and mindfulness. This could decrease AUD symptoms through the alleviation of psychiatric mood-related comorbidities consistent with the negative reinforcement and self-medication paradigms. In addition, preliminary evidence indicates that 5-MeO-DMT modulates neural oscillations that might subserve ego-dissolution (increases in gamma), psychological flexibility and mindfulness (increases in theta), and the reorganization of executive control networks (increases in coherence across frequencies) that could improve emotion regulation and inhibition. Finally, animal studies show that 5-MeO-DMT is characterized by neuroplasticity, anti-inflammation, 5-HT2A receptor agonism, and downregulation of metabotropic glutamate receptor 5 with clinical implications for AUD and psychiatric mood-related comorbidities. The paper concludes with several recommendations for future research to establish the purported therapeutic mechanisms of action.

Electroencephalography microstates highlight specific mindfulness traits

The present study aimed to investigate the spontaneous dynamics of large-scale brain networks underlying mindfulness as a dispositional trait, through resting-state electroencephalography (EEG) microstates analysis. Eighteen participants had attended a standardized mindfulness-based stress reduction training (MBSR), and 18 matched waitlist individuals (CTRL) were recorded at rest while they were passively exposed to auditory stimuli. Participants' mindfulness traits were assessed with the Five Facet Mindfulness Questionnaire (FFMQ). To further explore the relationship between microstate dynamics at rest and mindfulness traits, participants were also asked to rate their experience according to five phenomenal dimensions. After training, MBSR participants showed a highly significant increase in FFMQ score, as well as higher observing and non-reactivity FFMQ sub-scores than CTRL participants. Microstate analysis revealed four classes of microstates (A-D) in global clustering across all subjects. The MBSR group showed lower duration, occurrence and coverage of microstate C than the control group. Moreover, these microstate C parameters were negatively correlated to non-reactivity sub-scores of FFMQ across participants, whereas the microstate A occurrence was negatively correlated to FFMQ total score. Further analysis of participants' self-reports suggested that MBSR participants showed a better sensory-affective integration of auditory interferences. In line with previous studies, our results suggest that temporal dynamics of microstate C underlie specifically the non-reactivity trait of mindfulness. These findings encourage further research into microstates in the evaluation and monitoring of the impact of mindfulness-based interventions on the mental health and well-being of individuals.

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.

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.

SDA: a data-driven algorithm that detects functional states applied to the EEG of Guhyasamaja meditation

The study presents a novel approach designed to detect time-continuous states in time-series data, called the State-Detecting Algorithm (SDA). The SDA operates on unlabeled data and detects optimal change-points among intrinsic functional states in time-series data based on an ensemble of Ward's hierarchical clustering with time-connectivity constraint. The algorithm chooses the best number of states and optimal state boundaries, maximizing clustering quality metrics. We also introduce a series of methods to estimate the performance and confidence of the SDA when the ground truth annotation is unavailable. These include information value analysis, paired statistical tests, and predictive modeling analysis. The SDA was validated on EEG recordings of Guhyasamaja meditation practice with a strict staged protocol performed by three experienced Buddhist practitioners in an ecological setup. The SDA used neurophysiological descriptors as inputs, including PSD, power indices, coherence, and PLV. Post-hoc analysis of the obtained EEG states revealed significant differences compared to the baseline and neighboring states. The SDA was found to be stable with respect to state order organization and showed poor clustering quality metrics and no statistical significance between states when applied to randomly shuffled epochs (i.e., surrogate subject data used as controls). The SDA can be considered a general data-driven approach that detects hidden functional states associated with the mental processes evolving during meditation or other ongoing mental and cognitive processes.

Modulating Consciousness through Awareness Training Program and Its Impacts on Psychological Stress and Age-Related Gamma Waves

Aging often leads to awareness decline and psychological stress. Meditation, a method of modulating consciousness, may help individuals improve overall awareness and increase emotional resilience toward stress. This study explored the potential influence of the Awareness Training Program (ATP), a form of consciousness modulation, on age-related brain wave changes and psychological stress in middle-aged adults. Eighty-five participants with mild stress were recruited and randomly assigned to ATP (45.00 ± 8.00 yr) or control (46.67 ± 7.80 yr) groups, matched by age and gender. Ten-minute resting-state EEG data, obtained while the participants' eyes were closed, were collected using a 128-channel EEG system (EGI). A strong positive Pearson correlation was found between fast-wave (beta wave, 12-25 Hz; gamma wave, 25-40 Hz) EEG and age. However, after the 7-week ATP intervention, this correlation became insignificant in the ATP group. Furthermore, there was a significant reduction in stress levels, as measured by the Chinese version of the 10 item Perceived Stress Scale (PSS-10), in the ATP group. These results suggest that ATP may help modulate age-related effects on fast brain waves, as evidenced by the reduced correlation magnitude between age and gamma waves, and lower psychological stress. This suggests that ATP, as a form of consciousness modulation, may improve stress resilience and modulate age-related gamma wave changes.

Postural supporting cervical traction workstation to improve resting state brain activity in digital device users: EEG study

Objective

This study aimed to determine the effect of postural support workstation on inducing effective brain activity during rest.

Methods

Thirty-five healthy digital overusers were recruited as participants. We conducted two interventions of head weight support traction (ST) and conventional traction (CT) strength on all participants in random order. Participants' arousal levels and psychological comfort were assessed. In addition, changes in brain activity caused by traction were confirmed by measuring changes in resting state brain activity using an electroencephalogram (EEG).

Results

Under the ST condition, psychological comfort improved while alert levels were maintained. In addition the resting brain activity of EEG was characterized by strong focused attention and relaxed activity, as evidenced by increased alpha waves throughout the brain. By contrast, in the CT condition, no significant improvement in comfort was observed. Furthermore, high-frequency brain activity, such as beta 3 and gamma waves, was observed across the entire brain regions.

Conclusion

In this study, the ST workstation was shown to effectively improve resting attention and psychological comfort in individuals who excessively use digital devices by inducing resting state alpha activity without stimulating high-frequency brain waves, while maintaining an upright posture with appropriate traction.

Rhythms in Speech

Speech can be defined as the human ability to communicate through a sequence of vocal sounds. Consequently, speech requires an emitter (the speaker) capable of generating the acoustic signal and a receiver (the listener) able to successfully decode the sounds produced by the emitter (i.e., the acoustic signal). Time plays a central role at both ends of this interaction. On the one hand, speech production requires precise and rapid coordination, typically within the order of milliseconds, of the upper vocal tract articulators (i.e., tongue, jaw, lips, and velum), their composite movements, and the activation of the vocal folds. On the other hand, the generated acoustic signal unfolds in time, carrying information at different timescales. This information must be parsed and integrated by the receiver for the correct transmission of meaning. This chapter describes the temporal patterns that characterize the speech signal and reviews research that explores the neural mechanisms underlying the generation of these patterns and the role they play in speech comprehension.

Effect of Meditation on Brain Activity during an Attention Task: A Comparison Study of ASL and BOLD Task fMRI

Focused attention meditation (FAM) training has been shown to improve attention, but the neural basis of FAM on attention has not been thoroughly understood. Here, we aim to investigate the neural effect of a 2-month FAM training on novice meditators in a visual oddball task (a frequently adopted task to evaluate attention), evaluated with both ASL and BOLD fMRI. Using ASL, activation was increased in the middle cingulate (part of the salience network, SN) and temporoparietal (part of the frontoparietal network, FPN) regions; the FAM practice time was negatively associated with the longitudinal changes in activation in the medial prefrontal (part of the default mode network, DMN) and middle frontal (part of the FPN) regions. Using BOLD, the FAM practice time was positively associated with the longitudinal changes of activation in the inferior parietal (part of the dorsal attention network, DAN), dorsolateral prefrontal (part of the FPN), and precentral (part of the DAN) regions. The effect sizes for the activation changes and their association with practice time using ASL are significantly larger than those using BOLD. Our study suggests that FAM training may improve attention via modulation of the DMN, DAN, SN, and FPN, and ASL may be a sensitive tool to study the FAM effect on attention.

Investigation of advanced mindfulness meditation "cessation" experiences using EEG spectral analysis in an intensively sampled case study

Mindfulness meditation is a contemplative practice informed by Buddhism that targets the development of present-focused awareness and non-judgment of experience. Interest in mindfulness is burgeoning, and it has been shown to be effective in improving mental and physical health in clinical and non-clinical contexts. In this report, for the first time, we used electroencephalography (EEG) combined with a neurophenomenological approach to examine the neural signature of "cessation" events, which are dramatic experiences of complete discontinuation in awareness similar to the loss of consciousness, which are reported to be experienced by very experienced meditators, and are proposed to be evidence of mastery of mindfulness meditation. We intensively sampled these cessations as experienced by a single advanced meditator (with over 23,000 h of meditation training) and analyzed 37 cessation events collected in 29 EEG sessions between November 12, 2019, and March 11, 2020. Spectral analyses of the EEG data surrounding cessations showed that these events were marked by a large-scale alpha-power decrease starting around 40 s before their onset, and that this alpha-power was lowest immediately following a cessation. Region-of-interest (ROI) based examination of this finding revealed that this alpha-suppression showed a linear decrease in the occipital and parietal regions of the brain during the pre-cessation time period. Additionally, there were modest increases in theta power for the central, parietal, and right temporal ROIs during the pre-cessation timeframe, whereas power in the Delta and Beta frequency bands were not significantly different surrounding cessations. By relating cessations to objective and intrinsic measures of brain activity (i.e., EEG power) that are related to consciousness and high-level psychological functioning, these results provide evidence for the ability of experienced meditators to voluntarily modulate their state of consciousness and lay the foundation for studying these unique states using a neuroscientific approach.

Who Benefits the Most From Different Psychological Chronic Pain Treatments? An Exploratory Analysis of Treatment Moderators

Different psychological chronic pain treatments benefit some individuals more than others. Understanding the factors that are associated with treatment response-especially when those factors differ between treatments-may inform more effective patient-treatment matching. This study aimed to identify variables that moderate treatment response to 4 psychological pain interventions in a sample of adults with low back pain or chronic pain associated with multiple sclerosis, spinal cord injury, acquired amputation, or muscular dystrophy (N = 173). The current study presents the results from secondary exploratory analyses using data from a randomized controlled clinical trial which compared the effects of 4 sessions of cognitive therapy (CT), hypnosis focused on pain reduction (HYP), hypnosis focused on changing pain-related cognitions and beliefs (HYP-CT), and a pain education control condition (ED). The analyses tested the effects of 7 potential treatment moderators. Measures of primary (pain intensity) and secondary (pain interference, depression severity) outcome domains were administered before and after the pain treatments, and potential moderators (catastrophizing, hypnotizability, and electroencephalogram (EEG)-assessed oscillation power across five bandwidths) were assessed at pre-treatment. Moderator effects were tested fitting regression analyses to pre- to post-treatment changes in the three outcome variables. The study findings, while preliminary, support the premise that pre-treatment measures of hypnotizability and EEG brain activity predict who is more (or less) likely to respond to different psychological pain treatments. If additional research replicates the findings, it may be possible to better match patients to their more individually suitable treatment, ultimately improving pain treatment outcomes. PERSPECTIVE: Pre-treatment measures of hypnotizability and EEG-assessed brain activity predicted who was more (or less) likely to respond to different psychological pain treatments. If these findings are replicated in future studies, they could inform the development of patient-treatment matching algorithms.

Be more mindful: Targeting addictive responses by integrating mindfulness with cognitive bias modification or cue exposure interventions

This review provides an overview of the most prominent neurocognitive effects of cognitive bias modification (CBM), cue-exposure therapy and mindfulness interventions for targeting addictive responses. It highlights the key insights that have stemmed from cognitive neuroscience and brain imaging research and combines these with insights from behavioural science in building a conceptual model integrating mindfulness with response-focused CBM or cue-exposure interventions. This furthers our understanding of whether and how mindfulness strategies may i) facilitate or add to the induced response-focused effects decreasing cue-induced craving, and ii) further weaken the link between craving and addictive responses. Specifically, awareness/monitoring may facilitate, and decentering may add to, response-focused effects. Combined awareness acceptance strategies may also diminish the craving-addiction link. The conceptual model presented in this review provides a specific theoretical framework to deepen our understanding of how mindfulness strategies and CBM or cue-exposure interventions can be combined to greatest effect. This is important in both suggesting a roadmap for future research, and for the further development of clinical interventions.

Calming effect of Clinically Designed Improvisatory Music for patients admitted to the epilepsy monitoring unit during the COVID-19 pandemic: a pilot study

Background

Epilepsy monitoring requires simulating seizure-inducing conditions which frequently causes discomfort to epilepsy monitoring unit (EMU) patients. COVID-19 hospital restrictions added another layer of stress during hospital admissions. The purpose of this pilot study was to provide evidence that live virtual Clinically Designed Improvisatory Music (CDIM) brings relief to EMU patients for their psychological distress.

Methods

Five persons with epilepsy (PWEs) in the EMU during the COVID-19 lockdown participated in the study (average age ± SD = 30.2 ± 6 years). Continuous electroencephalogram (EEG) and electrocardiogram (EKG) were obtained before, during, and after live virtual CDIM. CDIM consisted of 40 minutes of calming music played by a certified clinical music practitioner (CMP) on viola. Post-intervention surveys assessed patients' emotional state on a 1-10 Likert scale. Alpha/beta power spectral density ratio was calculated for each subject across the brain and was evaluated using one-way repeated analysis of variance, comparing 20 minutes before, during, and 20 minutes after CDIM. Post-hoc analysis was performed using paired t-test at the whole brain level and regions with peak changes.

Results

Patients reported enhanced emotional state (9 ± 1.26), decrease in tension (9.6 ± 0.49), decreased restlessness (8.6 ± 0.80), increased pleasure (9.2 ± 0.98), and likelihood to recommend (10 ± 0) on a 10-point Likert scale. Based on one-way repeated analysis of variance, alpha/beta ratio increased at whole-brain analysis (F3,12 = 5.01, P = 0.018) with a peak in midline (F3,12 = 6.63, P = 0.0068 for Cz) and anterior medial frontal region (F3,12 = 6.45, P = 0.0076 for Fz) during CDIM and showed a trend to remain increased post-intervention.

Conclusion

In this pilot study, we found positive effects of CDIM as reported by patients, and an increased alpha/beta ratio with meaningful electroencephalographic correlates due to the calming effects in response to CDIM. Our study provides proof of concept that live virtual CDIM offered demonstrable comfort with biologic correlations for patients admitted in the EMU during the COVID-19 pandemic.

EEG-based investigation of effects of mindfulness meditation training on state and trait by deep learning and traditional machine learning

Introduction

This study examines the state and trait effects of short-term mindfulness-based stress reduction (MBSR) training using convolutional neural networks (CNN) based deep learning methods and traditional machine learning methods, including shallow and deep ConvNets as well as support vector machine (SVM) with features extracted from common spatial pattern (CSP) and filter bank CSP (FBCSP).

Methods

We investigated the electroencephalogram (EEG) measurements of 11 novice MBSR practitioners (6 males, 5 females; mean age 35.7 years; 7 Asians and 4 Caucasians) during resting and meditation at early and late training stages. The classifiers are trained and evaluated using inter-subject, mix-subject, intra-subject, and subject-transfer classification strategies, each according to a specific application scenario.

Results

For MBSR state effect recognition, trait effect recognition using meditation EEG, and trait effect recognition using resting EEG, from shallow ConvNet classifier we get mix-subject/intra-subject classification accuracies superior to related previous studies for both novice and expert meditators with a variety of meditation types including yoga, Tibetan, and mindfulness, whereas from FBSCP + SVM classifier we get inter-subject classification accuracies of 68.50, 85.00, and 78.96%, respectively.

Conclusion

Deep learning is superior for state effect recognition of novice meditators and slightly inferior but still comparable for both state and trait effects recognition of expert meditators when compared to the literatures. This study supports previous findings that short-term meditation training has EEG-recognizable state and trait effects.

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.

What happens in the brain when we die? Deciphering the neurophysiology of the final moments in life

When do we die and what happens in the brain when we die? The mystery around these questions has engaged mankind for centuries. Despite the challenges to obtain recordings of the dying brain, recent studies have contributed to better understand the processes occurring during the last moments of life. In this review, we summarize the literature on neurophysiological changes around the time of death. Perhaps the only subjective description of death stems from survivors of near-death experiences (NDEs). Hallmarks of NDEs include memory recall, out-of-body experiences, dreaming, and meditative states. We survey the evidence investigating neurophysiological changes of these experiences in healthy subjects and attempt to incorporate this knowledge into the existing literature investigating the dying brain to provide valuations for the neurophysiological footprint and timeline of death. We aim to identify reasons explaining the variations of data between studies investigating this field and provide suggestions to standardize research and reduce data variability.

The Influence of Focused Attention and Open Monitoring Mindfulness Meditation States on True and False Memory

Previous investigations into the effect of mindfulness meditation on false memory have reported mixed findings. One potential issue is that mindfulness meditation involves different styles that establish distinct cognitive control states. The present work aimed to address this issue by comparing the effects of single-session focused attention (FAM) and open monitoring (OMM) mindfulness meditation styles on true and false memory recall. Strengthened cognitive control states associated with FAM were predicted to increase true memory recall and decrease false memory recall. Conversely, weakened cognitive control established by OMM was predicted to increase false memory recall. Thirty-four meditation-naïve participants (23 females, mean age = 23.4 years, range = 18-33) first completed pre-meditation learning and recall phases of the Deese-Roediger-McDermott (DRM) task. Participants then completed a single session of FAM or OMM prior to a second, post-meditation, round of DRM task learning and recall phases with a novel word list. Finally, participants completed a recognition test with true and false memory, and distractor words. Both FAM and OMM groups demonstrated significant increase in false memory recall between pre- and post-meditation recall tests but these groups did not differ with respect to true and false memory recall and recognition. The present findings are consistent with previous reports of increased false memory arising from mindfulness meditation. Distinct cognitive control states associated with FAM and OMM states do not result in distinct true and false memory formation, at least in meditation-naïve adults.

Resting state dynamics in people with varying degrees of anxiety and mindfulness: A nonlinear and nonstationary perspective

Anxiety and mindfulness are two inversely linked traits shown to be involved in various physiological domains. The current study used resting state electroencephalography (EEG) to explore differences between people with low mindfulness-high anxiety (LMHA) (n = 29) and high mindfulness-low anxiety (HMLA) (n = 27). The resting EEG was collected for a total of 6 min, with a randomized sequence of eyes closed and eyes opened conditions. Two advanced EEG analysis methods, Holo-Hilbert Spectral Analysis and Holo-Hilbert cross-frequency phase clustering (HHCFPC) were employed to estimate the power-based amplitude modulation of carrier frequencies, and cross-frequency coupling between low and high frequencies, respectively. The presence of higher oscillation power across the delta and theta frequencies in the LMHA group than the HMLA group might have been due to the similarity between the resting state and situations of uncertainty, which reportedly triggers motivational and emotional arousal. Although these two groups were formed based on their trait anxiety and trait mindfulness scores, it was anxiety that was found to be significant predictor of the EEG power, not mindfulness. It led us to conclude that it might be anxiety, not mindfulness, which might have contributed to higher electrophysiological arousal. Additionally, a higher δ-β and δ-γ CFC in LMHA suggested greater local-global neural integration, consequently a greater functional association between cortex and limbic system than in the HMLA group. The present cross-sectional study may guide future longitudinal studies on anxiety aiming with interventions such as mindfulness to characterize the individuals based on their resting state physiology.

Brain activity during meditation in first-time meditators

AIM OF THE STUDY

The electrophysiological correlates of meditation states in both short and long-term meditators have been increasingly documented; however, little is known about the brain activity associated with first-time meditation experiences. The goal of this study was to investigate the electrophysiological correlates of a single guided mindfulness meditation session in subjects with no previous meditation experience.

MATERIALS AND METHODS

We analyzed electroencephalogram (EEG) changes in signal power, hemispheric asymmetry, and information flow between EEG channels, in 16 healthy subjects who were new to meditation practice.

RESULTS

Our results show that information flow decreases in the theta (4-8 Hz) and alpha ranges (8-13 Hz) during mindfulness meditation exercise as compared to control: a passive listening condition. These changes are accompanied by a general trend in the decrease of alpha power over the whole scalp. One possible interpretation of these results is that there is an increased level of alertness/vigilance associated with the meditation task rather than reaching the target state.

CONCLUSIONS

Our study expands on the existing body of knowledge concerning neural oscillations during breathing meditation practice by showing that in participants with no previous meditation training, EEG correlates are different from the electrophysiological signatures of mindfulness meditation found in studies of more advanced practitioners.

Study of EEG alpha wave response on the effects of video-guided deep breathing on pain rehabilitation

BACKGROUND

Athletes with chronic ankle pain (CAP) are more inclined to suffer from physical and psychological pain depending on the severity of the injuries, which might trigger the powerless feeling on future sports participation. Therefore, an efficient and simple method is useful to integrate into conventional physiotherapy (CP) for maintaining mental wellness.

OBJECTIVE

This research aimed to verify the effects and progress of video-guided deep breathing (DB) integrated into CP through study on the changes of alpha waves and pain scale.

METHODS

Alpha waves were recorded using an electroencephalogram (EEG) and a visual analogue scale (VAS) to assess pain intensity before and after the intervention (6 weeks). Thirty CAP participants were recruited and randomly assigned to two groups: group A for video-guided DB integration into their CP and group B for CP. The effects of pre and post intervention were analyzed using a paired t-test with statistical significance set at p< 0.05.

RESULTS

Profound results from the research have shown that the participants who received both the DB+CP revealed a significant increase in alpha wave (p< 0.05) at occipital region.

CONCLUSION

The significant result reveals an increase in alpha waves in the occipital region after 6 weeks and indicates that the video-guided DB with a smartphone application is able to produce a change in CAP participants. This supports the DB integration to the CP for altering the pain perception.

The Electroencephalographic Brainwave Spectrum, Mindful Meditation, and Awareness: Hypothesis

It is hypothesized that being mindfully aware is a spontaneous state of being. It is imbued with joy, peace and happiness. Such a state is periodically revealed during restful attentiveness or presence. It is also associated with spontaneous brain alpha activity of 8-13 Hz. In deep nonrapid eye movement sleep, there is synchronous delta activity at a coherent frequency of 0.1 Hz. Both of these brainwave ground states are spontaneous, calm and effortless. When any physical or mental effort is made, the alpha rhythm is desynchronized, and it is superposed by faster brain waves of beta (13-30 Hz) and gamma frequencies (30-150 Hz). This is associated with a stream of dualistic conscious experiences with contents. During deep sleep, delta activity is superposed by beta and gamma activity with microarousals resulting in dream experiences. During effortless, meditative awareness, the whole family of alpha rhythm is synchronized including (a) Occipital-parietal alpha with visual clarity, formless color, and the absence of visual imagery (b) Frontal eye-field alpha with relatively motionless eyes, and the absence of voluntary actions or plans to move the eyes in some direction, along with nonactive working memory, (c) Somatosensory alpha or Mu rhythm from the somatic motor-sensory cortex with the resultant stillness of the body including head, face, larynx, spine, hands and legs, (d) Mid-temporal auditory alpha with vocal quietness and internal verbal silence (Maunam) with a feeling of spontaneous silence and serenity, (e) Cingulate and precuneus alpha resulting in freedom from autobiographical memories and the sense of agency or ego. The insular cortex serves as a gatekeeper, a hierarchical controller to switch between conscious engagement or disengagement from the internal or the external world. It switches between the default mode network and the executive frontoparietal networks, between the sequential and the parallel modes of functioning. Mindful consciousness is local and dualistic, whereas mindful awareness is nonlocal and nondual.

Binaural acoustic stimulation in patients with Parkinson's disease

Acoustic stimulation can improve motor symptoms in Parkinson's disease (PD) and might therefore represent a potential non-invasive treatment option. Scalp electroencephalography studies in healthy subjects indicate that specifically binaural beat stimulation (BBS) in the gamma frequency range is associated with synchronized cortical oscillations at 40 Hertz (Hz). Several studies suggest that oscillations in the gamma-frequency range (>30 Hz) serve a prokinetic function in PD. In this double-blind, randomized study, 25 PD patients were recruited. The study was conducted with (ON) and without dopaminergic medication (OFF). Each drug condition consisted of two phases (no stimulation and acoustic stimulation). The acoustic stimulation phase was divided into two blocks including BBS and conventional acoustic stimulation (CAS) as a control condition. For BBS, a modulated frequency of 35 Hz was used (left: 320 Hz; right: 355 Hz) and for CAS 340 Hz on both sides. We assessed effects on motor performance using Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) and two validated commercially available portable devices (Kinesia ONE™ and Kinesia 360™) measuring motor symptoms such as dyskinesia, bradykinesia, and tremor. Repeated measures ANOVA revealed that BBS improved resting tremor on the side of the more affected limb in the OFF condition, as measured by wearables (F_(2,48) = 3.61, p = 0.035). However, BBS did not exert a general positive effect on motor symptoms as assessed via MDS-UPDRS (F_(2,48) = 1.00, p = 0.327). For CAS, we did not observe an improvement in specific symptoms but rather an overall beneficial effect on motor performance (MDS-UPDRS total score OFF medication: F_(2,48) = 4.17, p = 0.021; wearable scores: F_(2,48) = 2.46, p = 0.097). In this study, we found an improvement of resting tremor when applying BBS in the gamma frequency band OFF medication. Moreover, the positive effects of CAS underline the general positive potential for improvement of motor function by acoustically supported therapeutic approaches. However, more studies are needed to fully characterize the clinical relevance of BBS and to further optimize its ameliorating effects.

Concurrent TMS-EEG and EEG reveal neuroplastic and oscillatory changes associated with self-compassion and negative emotions

Background/Objective

Self-compassion has a consensual relevance for overall mental health, but its mechanisms remain unknown. Using intermittent theta burst stimulation (iTBS) and concurrent transcranial magnetic stimulation-electroencephalography (TMS-EEG), this study investigated the causal relationship of the dorsolateral prefrontal cortex (DLPFC) with self-compassion and explored the changes in neuroplasticity and neural dynamics.

Method

Thirty-two healthy participants received iTBS or sham stimulation over the DLPFC, before and after which they were instructed to either use self-compassionate strategies or to be rejected in the context of social rejection and to report the level of self-compassion or negative affect. TMS-evoked potentials were evaluated as novel neuroplastic techniques with N45, P60, N100, and P180.

Results

iTBS uniquely decreased P180 amplitude measured with TMS-EEG whereby sham stimulation had no effect on neuroplasticity. In line with neuroplasticity changes, iTBS enhanced a widespread gamma band power and coherence, which correlated consistently with increased engagement in self-compassion. Meanwhile, iTBS demonstrated opposite effects on theta activity dependent on the social contexts whereby self-compassion decreased and social rejection enhanced it respectively. This unique effect of iTBS on theta activity was also supplemented by the enhancement of theta band coherence following iTBS.

Conclusions

We found a causal relationship between DLPFC and self-compassion. We also provide evidence to indicate widespread gamma activity and connectivity to correlate with self-compassion as well as the critical role of the DLPFC in modulating theta activity and negative emotions.

The Theta Paradox: 4-8 Hz EEG Oscillations Reflect Both Sleep Pressure and Cognitive Control

Human electroencephalographic (EEG) oscillations characterize specific behavioral and vigilance states. The frequency of these oscillations is typically sufficient to distinguish a given state; however, theta oscillations (4-8 Hz) have instead been found in near-opposite conditions of drowsiness during sleep deprivation and alert cognitive control. While the latter has been extensively studied and is often referred to as "frontal midline theta," (fmTheta) the former has been investigated far less but is considered a marker for sleep pressure during wake. In this study we investigated to what extent theta oscillations differed during cognitive tasks and sleep deprivation. We measured high-density EEG in 18 young healthy adults (nine female) performing six tasks under three levels of sleep deprivation. We found both cognitive load and sleep deprivation increased theta power in medial prefrontal cortical areas; however, sleep deprivation caused additional increases in theta in many other, predominantly frontal, areas. The sources of sleep deprivation theta (sdTheta) were task dependent, with a visual-spatial task and short-term memory (STM) task showing the most widespread effects. Notably, theta was highest in supplementary motor areas during passive music listening, and highest in the inferior temporal cortex (responsible for object recognition) during a spatial game. Furthermore, while changes in task performance were correlated with increases in theta during sleep deprivation, this relationship was not specific to the EEG of the same task and did not survive correction for multiple comparisons. Altogether, these results suggest that both during sleep deprivation and cognition theta oscillations may preferentially occur in cortical areas not involved in ongoing behavior.SIGNIFICANCE STATEMENT Electroencephalographic (EEG) research in sleep has often remained separate from research in cognition. This has led to two incompatible interpretations of the function of theta brain oscillations (4-8 Hz): that they reflect local sleep events during sleep deprivation, or that they reflect cognitive processing during tasks. With this study, we found no fundamental differences between theta oscillations during cognition and theta during sleep deprivation that would suggest different functions. Instead, our results indicate that in both cases, theta oscillations are generated by cortical areas not required for ongoing behavior. Therefore, at least in humans, theta may reflect either cortical disengagement or inhibition.

Mindfulness-induced endogenous theta stimulation occasions self-transcendence and inhibits addictive behavior

Self-regulation is instantiated by theta oscillations (4 to 8 Hz) in neurons of frontal midline brain regions. Frontal midline theta (FMΘ) is inversely associated with default mode network (DMN) activation, which subserves self-referential processing. Addiction involves impaired self-regulation and DMN dysfunction. Mindfulness is an efficacious self-regulatory practice for treating addiction, but little is known about the mechanisms by which mindfulness reduces addictive behavior. In this mechanistic study of long-term opioid users (N = 165), we assessed meditation-induced FMΘ as a mediator of changes in opioid misuse. Relative to a supportive psychotherapy control, participants treated with Mindfulness-Oriented Recovery Enhancement (MORE) exhibited increased FMΘ during a laboratory-based meditation session. FMΘ during meditation was associated with self-transcendent experiences characterized by ego dissolution, nondual awareness, and bliss. MORE's effects on decreasing opioid misuse were mediated by increased FMΘ. Given the role of aberrant self-referential processing in addiction, mindfulness-induced endogenous theta stimulation might "reset" DMN dysfunction to inhibit addictive behavior.