Large effects of brief meditation intervention on EEG spectra in meditation novices

Beyond fight or flight: The protective role of pre-pandemic meditation practice against anxiety and perceived stress

The COVID-19 pandemic generated distinct mental health challenges, characterised by stress and anxiety due to its unpredictable duration and continuous threat. This study examined the role of meditation practice on anxiety symptoms and perceived stress, considering co-variables such as self-compassion, acceptance, awareness, brooding, lockdown duration, and sociodemographic characteristics. The study used a longitudinal design and data were collected through online surveys from April 2020 to January 2021 (at four different time points) and included 238 participants from Portugal (165 had prior experience with meditation practices, 73 were non-meditators) with a mean age of 43.08 years (SD = 10.96). Linear mixed models revealed that over time, during the lockdown, the non-meditators group demonstrated a greater increase of anxiety symptoms (β = -0.226, SE = 0.06, p = 0.006) and perceived stress (β = -0.20, SE = 0.06, p = 0.004), whereas the meditators group showed non-significant (p > 0.05) variations in anxiety and stress symptoms during the same period of time. The effect of meditation on anxiety symptoms was moderated by sex, days of lockdown, self-compassion, and acceptance. The effect of meditation on perceived stress was moderated by sex, years of education, days of lockdown, and levels of awareness. Additionally, the study explored the potential predictive effect of different meditation session lengths, indicating that longer meditation practices offered greater protection against an increase in anxiety symptoms. These findings highlight the importance of cultivating self-regulation skills and investing in preventive mental health strategies to promote well-being and autonomy. Mental health professionals should prioritise educating communities on evidence-based practices like meditation and compassion exercises to enhance overall health.

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

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

Mind and body connection in expert meditators: a computational study based on central and peripheral nervous system

A meditative 'technique' is conceived as a continuum of different affective states involving mind and body jointly. Meditative practices can involve cognitive effort (e.g., focused attention and open-minded techniques), as well as automatic and implicit practices (e.g., transcendental techniques). The NGALSO tantric self-healing meditation technique is a brief, comprehensive meditation technique relying on mind and body connection. In this study, we aimed to investigate the state and the trait neurophysiological correlates of NGALSO meditation practice. First, 19 EEG channels and a 3-lead ECG signal were recorded from 10 expert meditators (more than 7 years of daily meditation) and 10 healthy inexpert participants (controls) who underwent the same meditative procedure. The neuropsychological profiles of experts and controls were compared. Results showed that expert meditators had significantly higher power spectra on alpha, theta and beta, and a higher sympathetic tone with lower parasympathetic tone after meditation. Conversely, the control group had significantly less power spectra on alpha, theta and beta, and a higher parasympathetic tone with lower sympathetic tone after meditation. A machine learning approach also allowed us to classify experts vs. controls correctly by using only EEG Theta bands before or after meditation. ECG results allowed us to show a significantly higher effort by expert meditators vs. controls, thus suggesting that a higher effort is required for this meditation, in line with the principle 'no pain, no gain' in body and mind.

Investigating the Impact of Guided Imagery on Stress, Brain Functions, and Attention: A Randomized Trial

The aim of this study was to investigate the potential impact of guided imagery (GI) on attentional control and cognitive performance and to explore the relationship between guided imagery, stress reduction, alpha brainwave activity, and attentional control using common cognitive performance tests. Executive function was assessed through the use of attentional control tests, including the anti-saccade, Stroop, and Go/No-go tasks. Participants underwent a guided imagery session while their brainwave activity was measured, followed by attentional control tests. The study's outcomes provide fresh insights into the influence of guided imagery on brain wave activity, particularly in terms of attentional control. The findings suggest that guided imagery has the potential to enhance attentional control by augmenting the alpha power and reducing stress levels. Given the limited existing research on the specific impact of guided imagery on attention control, the study's findings carry notable significance.

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.

Outcomes in Patients with Minor Stroke: Diagnosis and Management in the Post-thrombectomy Era

In the era of mechanical thrombectomy and better preventative strategies, a higher number of patients are being discharged home from the hospital with the so-called minor strokes. This has significantly changed the landscape of stroke recovery. Unfortunately, while symptoms may be categorized as mild compared to individuals with higher NIH Stroke Scale scores, the physical, cognitive, and emotional sequelae can be disabling and result in failure to return to work and poor quality of life in a population with significant potential to recover fully. In this review, we discuss the current state of minor stroke, the most common pattern of resulting deficits, what is known about the underlying pathophysiology that leads to a relatively global pattern of impaired cognition following an infarct in any location, and special considerations for treatment based on this population's unique needs. Raising awareness of the current morbidity associated with minor stroke, the need for a uniform definition that allows for comparisons of individuals across studies, and further research focused on this population to optimize outcomes, has the potential to significantly improve recovery.

Complementary and Integrative Medicine for Anxiety in Children, Adolescents, and Young Adults

An integrative approach to treating anxiety in children and adolescents takes a biopsychosocial-spiritual approach. Early life stress may translate into anxiety via epigenetic mechanisms, the adoption of maladaptive coping tendencies (poor eating, sedentary lifestyle, substance use), and dysregulation of central autonomic nervous system function. Each of these mechanisms may increase inflammatory markers. This article will explore the efficacy of CIM interventions that work on these mechanisms through mind-body-medicine, acupuncture, nutrition, and supplements.

Group Coaching Using Energy-Based Practices for Health, Healing, and Personal Growth: Program Design and Training Outcomes

An innovative training curriculum on energy-based practices for group coaching was developed and disseminated to 16 coaching students. This article describes phase 1 curriculum design and initial evaluation of the coaching program. Findings demonstrated the benefits of this course, highlighted areas for refinement, and support progression to phase 2 for wider dissemination.

Virtual Reality as a Moderator of Psychedelic-Assisted Psychotherapy

Psychotherapy with the use of psychedelic substances, including psilocybin, lysergic acid diethylamide (LSD), ketamine, and 3,4-methylenedioxymethamphetamine (MDMA), has demonstrated promise in treatment of post-traumatic stress disorder (PTSD), anxiety, addiction, and treatment-resistant depression. Psychedelic-assisted psychotherapy (PP) represents a unique psychopharmacological model that leverages the profound effects of the psychedelic experience. That experience is characterized by strong dependency on two key factors: participant mindset and the therapeutic environment. As such, therapeutic models that utilize psychedelics reflect the need for careful design that promotes an open, flexible, trusting mindset and a supportive setting. To meet this need, the PP model is increasingly supplemented by auxiliary methods, including meditation, relaxation, visualization or spiritual practices. We suggest virtual reality (VR) as a full-spectrum tool able to capitalize on and catalyze the innately therapeutic aspects of the psychedelic experience, such as detachment from familiar reality, alteration of self-experience, augmentation of sensory perception and induction of mystical-type experiences. This is facilitated by VR’s evidenced capacity to: aid relaxation and reduce anxiety; buffer from external stimuli; promote a mindful presence; train the mind to achieve altered states of consciousness (ASC); evoke mystical states; enhance therapeutic alliance and encourage self-efficacy. While these unique VR features appear promising, VR’s potential role in PP remains speculative due to lack of empirical evidence on the combined use of VR and PP. Given the increased commercial interest in this synergy there is an urgent need to evaluate this approach. We suggest specific VR models and their role within PP protocols to inspire future direction in scientific research, and provide a list of potential disadvantages, side effects and limitations that need to be carefully considered. These include sensory overstimulation, cyber-sickness, triggering memories of past traumatic events as well as distracting from the inner experience or strongly influencing its contents. A balanced, evidence-based approach may provide continuity across all phases of treatment, support transition into and out of an ASC, deepen acute ASC experiences including mystical states and enrich the psychotherapeutic process of integration. We conclude that the potential application of VR in modulating psychedelic-assisted psychotherapy demands further exploration and an evidence-based approach to both design and implementation.

A Single Session of Mindfulness Meditation Expedites Immediate Motor Memory Consolidation to Improve Wakeful Offline Learning

Posttraining meditation has been shown to promote wakeful memory stabilization of explicit motor sequence information in learners who are experienced meditators. We investigated the effect of single-session mindfulness meditation on wakeful and sleep-dependent forms of implicit motor memory consolidation in meditation naïve adults. Immediately after training with a target implicit motor sequence, participants (N = 20, eight females, 23.9 ± 3.3 years) completed either a 10-min mindfulness meditation (N = 10) or a control listening task before exposure to task interference induced by training with a novel implicit sequence. Target sequence performance was tested following 5-hr wakeful and 15-hr postsleep periods. Bayesian inference was applied to group comparisons of mean reaction time (RT) changes across training, interference, wakeful, and postsleep timepoints. Relative to control conditions, posttraining meditation reduced RT slowing between target sequence training and interference sequence introduction (BF10 [Bayes factors] = 6.61) and supported RT performance gains over the wakeful period (BF10 = 8.34). No group differences in postsleep RT performance were evident (BF10 = 0.38). These findings illustrate that posttraining mindfulness meditation expedites wakeful, but not sleep-dependent, offline learning with implicit motor sequences. Previous meditation experience is not required to obtain wakeful consolidation gains from posttraining mindfulness meditation.

Effective Stress Management through Meditation: An Electroencephalograph-Based Study

Introduction

Stress among college students is a common health problem that is directly correlated with poor cognitive health. For instance, cognitive mechanisms required for sustenance can be affected due to stress caused by daily mundane events, not necessarily by chronic events. Thus, it becomes essential to manage stress effectively especially for college students. Meditation is one of the useful techniques that facilitates cognitive flexibility and has consequences at the molecular and endocrinal level to treat stress.

Objectives

The present study attempts to understand the effect of meditation on the brain waves when participants face stressful events.

Methods

A randomized controlled pre-post experimental design was used. Total 18 subjects were randomly assigned to control group and experimental group. Subsequently, Electroencephalograph (EEG) data were recorded during the determination test (DT) before and after the meditation. The Control group underwent relaxation music while the experimental group practiced Sudarshan Kriya Yoga (SKY) (a type of meditation). Non-linear EEG signal processing algorithm was applied to capture dynamics and complexity in brain waves. Results: Results indicated that the efficacy of meditation was reflected with the improved information processing in the brain. Improved performance and reduced errors were reported in DT Scores in the experimental group. Increased complexity of beta band was observed for non-linear features, signifying efficient utilization of cognitive resources while performing the task.

Conclusion

Findings implicated the usefulness of the meditation process for effective stress management.

Resting-State EEG Signal for Major Depressive Disorder Detection: A Systematic Validation on a Large and Diverse Dataset

Major depressive disorder (MDD) is a global healthcare issue and one of the leading causes of disability. Machine learning combined with non-invasive electroencephalography (EEG) has recently been shown to have the potential to diagnose MDD. However, most of these studies analyzed small samples of participants recruited from a single source, raising serious concerns about the generalizability of these results in clinical practice. Thus, it has become critical to re-evaluate the efficacy of various common EEG features for MDD detection across large and diverse datasets. To address this issue, we collected resting-state EEG data from 400 participants across four medical centers and tested classification performance of four common EEG features: band power (BP), coherence, Higuchi's fractal dimension, and Katz's fractal dimension. Then, a sequential backward selection (SBS) method was used to determine the optimal subset. To overcome the large data variability due to an increased data size and multi-site EEG recordings, we introduced the conformal kernel (CK) transformation to further improve the MDD as compared with the healthy control (HC) classification performance of support vector machine (SVM). The results show that (1) coherence features account for 98% of the optimal feature subset; (2) the CK-SVM outperforms other classifiers such as K-nearest neighbors (K-NN), linear discriminant analysis (LDA), and SVM; (3) the combination of the optimal feature subset and CK-SVM achieves a high five-fold cross-validation accuracy of 91.07% on the training set (140 MDD and 140 HC) and 84.16% on the independent test set (60 MDD and 60 HC). The current results suggest that the coherence-based connectivity is a more reliable feature for achieving high and generalizable MDD detection performance in real-life clinical practice.