Brief Mental Training Reorganizes Large-Scale Brain Networks

Contributions of loneliness to cognitive impairment and dementia in older adults are independent of other risk factors and Alzheimer's pathology: a narrative review

Loneliness significantly contributes to cognitive impairment and dementia in older adults. Loneliness is a distressing feeling resulting from a perceived lack of social connection (i.e., a discrepancy between desired and actual social relationships), while social isolation is a related term that can be defined by number and type of social relationships. Importantly, loneliness is distinct from social isolation in that it is associated with a distressing self-perception. The primary focus of this narrative review is the impact of chronic loneliness on cognitive impairment and dementia among older adults. Loneliness has a significant association with many factors that are related to worse cognition, and therefore we include discussion on health, mental health, as well as the physiological effects of loneliness, neuropathology, and potential treatments. Loneliness has been shown to be related to development of dementia with a hazard ratio (HR) risk comparable to having a single APOE4 gene. The relationship of dementia to loneliness appears to be at least partially independent of other known dementia risk factors that are possibly associated with loneliness, such as depression, educational status, social isolation, and physical activity. Episodic memory is not consistently impacted by loneliness, which would be more typically impaired if the mild cognitive impairment (MCI) or dementia was due to Alzheimer's disease (AD) pathology. In addition, the several longitudinal studies that included neuropathology showed no evidence for a relationship between loneliness and AD neuropathology. Loneliness may decrease resilience, or produce greater cognitive change associated with the same level of AD neuropathology. Intervention strategies to decrease loneliness in older adults have been developed but need to consider key treatment targets beyond social isolation. Loneliness needs to be assessed in all studies of cognitive decline in elders, since it significantly contributes to the variance of cognitive function. It will be useful to better define the underlying mechanism of loneliness effects on cognition to determine if it is similar to other psychological factors related to excessive stress reactivity, such as neuroticism or even depression, which are also associated with cognitive decline. It is important from a health perspective to develop better strategies to decrease loneliness in older adults.

Digital mindfulness training and cognitive functions: A preregistered systematic review of neuropsychological findings

Traditional mindfulness interventions have been frequently reported to be effective in improving cognitive functions. In recent years, however, traditional programs are being increasingly replaced by technology-enabled mindfulness training programs. The aim of the present systematic review (PROSPERO ID: CRD42021289480) is to evaluate the research evidence on their effects on cognitive functions. Empirical training studies in the realm of digital mindfulness training that fulfilled the inclusion criteria led to 19 studies and 1654 participants being included in this review from among the papers searched in PubMed, Scopus, and Web of Knowledge. Results support previous assumptions on the potential of digital mindfulness training, with the most robust effect on attention control, followed by executive regulation, memory, cognitive flexibility, and other cognitive functions. However, the number of studies that did not find significant changes at least equaled, if not exceeded, the number of studies that found increases. The heterogeneity of identified studies prompted us to discuss several aspects in order to help the future development of digital applications.

Within-Person Modulation of Neural Networks following Interoceptive Awareness Training through Mindful Awareness in Body-Oriented Therapy (MABT): A Pilot Study

Interoception, the representation of the body's internal state, is increasingly recognized for informing subjective wellbeing and promoting regulatory behavior. However, few empirical reports characterize interoceptive neural networks, and fewer demonstrate changes to these networks in response to an efficacious intervention. Using a two-group randomized controlled trial, this pilot study explored within-participant neural plasticity in interoceptive networks following Mindful Awareness in Body-oriented Therapy (MABT). Participants (N = 22) were assigned to either 8 weeks of MABT or to a no-treatment control and completed baseline and post-intervention assessments that included subjective interoceptive awareness (MAIA) and neuroimaging of an interoceptive awareness task. MABT was uniquely associated with insula deactivation, increased functional connectivity between the dorsal attention network and the somatomotor cortex, and connectivity changes correlated positively with changes in subjective interoception. Within the MABT group, changes in subjective interoception interacted with changes in a predefined anterior cingulate seed region to predict changes in right middle insula activity, a putative primary interoceptive representation region. While the small sample size requires the replication of findings, results suggest that interoceptive training enhances sensory-prefrontal connectivity, and that such changes are commensurate with enhanced interoceptive awareness.

The effects of an 8-week mindful eating intervention on anticipatory reward responses in striatum and midbrain

Introduction

Accumulating evidence suggests that increased neural responses during the anticipation of high-calorie food play an important role in the tendency to overeat. A promising method for counteracting enhanced food anticipation in overeating might be mindfulness-based interventions (MBIs). However, the neural mechanisms by which MBIs can affect food reward anticipation are unclear. In this randomized, actively controlled study, the primary objective was to investigate the effect of an 8-week mindful eating intervention on reward anticipation. We hypothesized that mindful eating would decrease striatal reward anticipation responses. Additionally, responses in the midbrain-from which the reward pathways originate-were explored.

Methods

Using functional magnetic resonance imaging (fMRI), we tested 58 healthy participants with a wide body mass index range (BMI: 19-35 kg/m2), motivated to change their eating behavior. During scanning they performed an incentive delay task, measuring neural reward anticipation responses to caloric and monetary cues before and after 8 weeks of mindful eating or educational cooking (active control).

Results

Compared with the educational cooking intervention, mindful eating affected neural reward anticipation responses, with reduced caloric relative to monetary reward responses. This effect was, however, not seen in the striatum, but only in the midbrain. The secondary objective was to assess temporary and long-lasting (1 year follow-up) intervention effects on self-reported eating behavior and anthropometric measures [BMI, waist circumference, waist-to-hip-ratio (WHR)]. We did not observe effects of the mindful eating intervention on eating behavior. Instead, the control intervention showed temporary beneficial effects on BMI, waist circumference, and diet quality, but not on WHR or self-reported eating behavior, as well as long-lasting increases in knowledge about healthy eating.

Discussion

These results suggest that an 8-week mindful eating intervention may have decreased the relative salience of food cues by affecting midbrain but not striatal reward responses, without necessarily affecting regular eating behavior. However, these exploratory results should be verified in confirmatory research.The primary and secondary objectives of the study were registered in the Dutch Trial Register (NTR): NL4923 (NTR5025).

Long-Term and Meditation-Specific Modulations of Brain Connectivity Revealed Through Multivariate Pattern Analysis

Neuroimaging studies have provided evidence that extensive meditation practice modifies the functional and structural properties of the human brain, such as large-scale brain region interplay. However, it remains unclear how different meditation styles are involved in the modulation of these large-scale brain networks. Here, using machine learning and fMRI functional connectivity, we investigated how focused attention and open monitoring meditation styles impact large-scale brain networks. Specifically, we trained a classifier to predict the meditation style in two groups of subjects: expert Theravada Buddhist monks and novice meditators. We showed that the classifier was able to discriminate the meditation style only in the expert group. Additionally, by inspecting the trained classifier, we observed that the Anterior Salience and the Default Mode networks were relevant for the classification, in line with their theorized involvement in emotion and self-related regulation in meditation. Interestingly, results also highlighted the role of specific couplings between areas crucial for regulating attention and self-awareness as well as areas related to processing and integrating somatosensory information. Finally, we observed a larger involvement of left inter-hemispheric connections in the classification. In conclusion, our work supports the evidence that extensive meditation practice modulates large-scale brain networks, and that the different meditation styles differentially affect connections that subserve style-specific functions.

Beyond the veil of duality-topographic reorganization model of meditation

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

Mindfulness meditation increases default mode, salience, and central executive network connectivity

Recent research has begun to identify the neural mechanisms underlying the beneficial impact of mindfulness meditation training (MMT) on health and cognition. However, little is known about the effects of MMT on the global interplay of large-scale networks (LSNs) in the brain. In the present study, healthy, meditation-naïve adults (N = 46) underwent resting state fMRI prior to and upon completing 31 days of MMT or an active control intervention. Independent component analysis, sliding time window, and seed-based correlation analyses were performed to assess training-related changes in functional connectivity (FC) within and between networks with relevance to mindfulness meditation. Across sliding time window analyses and seed-based correlation analyses, we found increased FC between nodes of the default mode network (DMN) and nodes of the salience network (SN) in participants of the MMT. Seed-based correlation analyses revealed further connectivity increases between the SN and key regions of the central executive network (CEN). These results indicate, that, among multiple LSNs, one month of mindfulness meditation effectively increases interconnectivity between networks of the triple network model (DMN, SN, CEN), hereby introducing a potential mechanistic concept underlying the beneficial impact of MMT.

Clinical trial registration: This study is listed as a clinical trial on the ISRCTN registry with trial ID ISRCTN95197731 (date of first registration: 15/02/2022).

Classification of Rajayoga Meditators Based on the Duration of Practice Using Graph Theoretical Measures of Functional Connectivity from Task-Based Functional Magnetic Resonance Imaging

CONTEXT

Functional magnetic resonance imaging (fMRI) studies on mental training techniques such as meditation have reported benefits like increased attention and concentration, better emotional regulation, as well as reduced stress and anxiety. Although several studies have examined functional activation and connectivity in long-term as well as short-term meditators from different meditation traditions, it is unclear if long-term meditation practice brings about distinct changes in network properties of brain functional connectivity that persist during task performance. Indeed, task-based functional connectivity studies of meditators are rare.

AIMS

This study aimed to differentiate between long-term and short-term Rajayoga meditators based on functional connectivity between regions of interest in the brain. Task-based fMRI was captured as the meditators performed an engaging task. The graph theoretical-based functional connectivity measures of task-based fMRI were calculated using CONN toolbox and were used as features to classify the two groups using Machine Learning models.

SUBJECTS AND METHODS

In this study, we recruited two age and sex-matched groups of Rajayoga meditators from the Brahma Kumaris tradition that differed in the duration of their meditation experience: Long-term practitioners (n = 12, mean 13,596 h) and short-term practitioners (n = 10, mean 1095 h). fMRI data were acquired as they performed an engaging task and functional connectivity metrics were calculated from this data. These metrics were used as features in training machine learning algorithms. Specifically, we used adjacency matrices generated from graph measures, global efficiency, and local efficiency, as features. We computed functional connectivity with 132 ROIs as well as 32 network ROIs.

STATISTICAL ANALYSIS USED

Five machine learning models, such as logistic regression, SVM, decision tree, random forest, and gradient boosted tree, were trained to classify the two groups. Accuracy, precision, sensitivity, selectivity, area under the curve receiver operating characteristics curve were used as performance measures.

RESULTS

The graph measures were effective features, and tree-based algorithms such as decision tree, random forest, and gradient boosted tree yielded the best performance (test accuracy >84% with 132 ROIs) in classifying the two groups of meditators.

CONCLUSIONS

Our results support the hypothesis that long-term meditative practices alter brain functional connectivity networks even in nonmeditative contexts. Further, the use of adjacency matrices from graph theoretical measures of high-dimensional fMRI data yields a promising feature set for machine learning classifiers.

OUP accepted manuscript

Very preterm children are more likely to exhibit difficulties in socio-emotional processing than their term-born peers. Emerging socio-emotional problems may be partly due to alterations in limbic system development associated with infants’ early transition to extrauterine life. The amygdala is a key structure in this system and plays a critical role in various aspects of socio-emotional development, including emotion regulation. The current study tested the hypothesis that amygdala resting-state functional connectivity at term-equivalent age would be associated with socio-emotional outcomes in childhood. Participants were 129 very preterm infants (<33 weeks' gestation) who underwent resting-state functional MRI at term and received a neurodevelopmental assessment at 4–7 years (median = 4.64). Using the left and right amygdalae as seed regions, we investigated associations between whole-brain seed-based functional connectivity and three socio-emotional outcome factors which were derived using exploratory factor analysis (Emotion Moderation, Social Function and Empathy), controlling for sex, neonatal sickness, post-menstrual age at scan and social risk. Childhood Emotion Moderation scores were significantly associated with neonatal resting-state functional connectivity of the right amygdala with right parahippocampal gyrus and right middle occipital gyrus, as well as with functional connectivity of the left amygdala with the right thalamus. No significant associations were found between amygdalar resting-state functional connectivity and either Social Function or Empathy scores. The current findings show that amygdalar functional connectivity assessed at term is associated with later socio-emotional outcomes in very preterm children.

Neuroplasticity within and between Functional Brain Networks in Mental Training Based on Long-Term Meditation

(1) The effects of intensive mental training based on meditation on the functional and structural organization of the human brain have been addressed by several neuroscientific studies. However, how large-scale connectivity patterns are affected by long-term practice of the main forms of meditation, Focused Attention (FA) and Open Monitoring (OM), as well as by aging, has not yet been elucidated. (2) Using functional Magnetic Resonance Imaging (fMRI) and multivariate pattern analysis, we investigated the impact of meditation expertise and age on functional connectivity patterns in large-scale brain networks during different meditation styles in long-term meditators. (3) The results show that fMRI connectivity patterns in multiple key brain networks can differentially predict the meditation expertise and age of long-term meditators. Expertise-predictive patterns are differently affected by FA and OM, while age-predictive patterns are not influenced by the meditation form. The FA meditation connectivity pattern modulated by expertise included nodes and connections implicated in focusing, sustaining and monitoring attention, while OM patterns included nodes associated with cognitive control and emotion regulation. (4) The study highlights a long-term effect of meditation practice on multivariate patterns of functional brain connectivity and suggests that meditation expertise is associated with specific neuroplastic changes in connectivity patterns within and between multiple brain networks.

Value, drug addiction and the brain

Over the years, various models have been proposed to explain the psychology and biology of drug addiction, built primarily around the habit and compulsion models. Recent research indicates drug addiction may be goal-directed, motivated by excessive valuation of drugs. Drug consumption may initially occur for the sake of pleasure but may transition to a means of escaping withdrawal, stress and negative emotions. In this hypothetical paper, we propose a value-based neurobiological model for drug addiction. We posit that during dependency, the value-based decision-making system in the brain is not inactive but has instead prioritized drugs as the reward of choice. In support of this model, we consider the role of valuation in choice, its influence on pleasure and punishment, and how valuation is contrasted in impulsive and compulsive behaviours. We then discuss the neurobiology of value, beginning with the dopaminergic system and its relationship with incentive salience before moving to brain-wide networks involved in valuation, control and prospection. These value-based neurobiological components are then integrated into the cycle of addiction as we consider the development of drug dependency from a valuation perspective. We conclude with a discussion of cognitive interventions utilizing value-based decision-making, highlighting not just advances in recalibrating the valuation system to focus on non-drug rewards, but also areas for improvement in refining this approach.

Spontaneous brain state oscillation is associated with self-reported anxiety in a non-clinical sample

The anti-correlation relationship between the default-mode network (DMN) and task-positive network (TPN) may provide valuable information on cognitive functions and mental disorders. Moreover, maintaining a specific brain state and efficaciously switching between different states are considered important for self-regulation and adaptation to changing environments. However, it is currently unclear whether competitions between the DMN and TPN are associated with negative affect (here, anxiety and depression) in non-clinical samples. We measured the average dwell time of DMN dominance over the TPN (i.e., the average state duration before transition to another state, indicating persistent DMN dominance) with a sample of 302 non-clinical young adults. Subsequently, we explored individual differences in this persistent DMN dominance by examining its correlations with subjective depression and anxiety feelings. Moreover, we linked state transition between DMN/TPN dominance with right fronto-insular cortex (RFIC) blood oxygen-level dependent signal variability. We found that the average dwell time of DMN dominance was positively associated with self-reported anxiety. Furthermore, state transition between DMN or TPN dominance was positively linked to RFIC activity. These findings highlight the importance of investigating the complex and dynamic reciprocal inhibition patterns of the DMN and TPN and the important role of the RFIC in the association between these networks.

Dysregulation of inflammation, neurobiology, and cognitive function in PTSD: an integrative review

Compelling evidence from animal and human research suggest a strong link between inflammation and posttraumatic stress disorder (PTSD). Furthermore, recent findings support compromised neurocognitive function as a key feature of PTSD, particularly with deficits in attention and processing speed, executive function, and memory. These cognitive domains are supported by brain structures and neural pathways that are disrupted in PTSD and which are implicated in fear learning and extinction processes. The disruption of these supporting structures potentially results from their interaction with inflammation. Thus, the converging evidence supports a model of inflammatory dysregulation and cognitive dysfunction as combined mechanisms underpinning PTSD symptomatology. In this review, we summarize evidence of dysregulated inflammation in PTSD and further explore how the neurobiological underpinnings of PTSD, in the context of fear learning and extinction acquisition and recall, may interact with inflammation. We then present evidence for cognitive dysfunction in PTSD, highlighting findings from human work. Potential therapeutic approaches utilizing novel pharmacological and behavioral interventions that target inflammation and cognition also are discussed.

Real-time fMRI neurofeedback reduces auditory hallucinations and modulates resting state connectivity of involved brain regions: Part 2: Default mode network -preliminary evidence

Auditory hallucinations (AHs) are one of the most distressing symptoms of schizophrenia (SZ) and are often resistant to medication. Imaging studies of individuals with SZ show hyperactivation of the default mode network (DMN) and the superior temporal gyrus (STG). Studies in SZ show DMN hyperconnectivity and reduced anticorrelation between DMN and the central executive network (CEN). DMN hyperconnectivity has been associated with positive symptoms such as AHs while reduced DMN anticorrelations with cognitive impairment. Using real-time fMRI neurofeedback (rt-fMRI-NFB) we trained SZ patients to modulate DMN and CEN networks. Meditation is effective in reducing AHs in SZ and to modulate brain network integration and increase DMN anticorrelations. Consequently, patients were provided with meditation strategies to enhance their abilities to modulate DMN/CEN. Results show a reduction of DMN hyperconnectivity and increase in DMNCEN anticorrelation. Furthermore, the change in individual DMN connectivity significantly correlated with reductions in AHs. This is the first time that meditation enhanced through rt-fMRI-NFB is used to reduce AHs in SZ. Moreover, it provides the first empirical evidence for a direct causal relation between meditation enhanced rt-fMRI-NFB modulation of DMNCEN activity and post-intervention modulation of resting state networks ensuing in reductions in frequency and severity of AHs.

Biobehavioral utility of mindfulness-based art therapy: Neurobiological underpinnings and mental health impacts

Mindfulness-based art therapy (MBAT) combines mindfulness practices with art therapy to promote health, wellness, and adaptive responses to stress. Mindfulness-based stress reduction programs have been demonstrated to reduce anxiety symptoms in people with generalized anxiety disorder and serious medical conditions such as cancer. However, the benefits of MBAT specifically—not just in clinical anxiety disorders, but also for routine day-to-day anxiousness—have received little attention until recently. In this mini-review, we summarize how several established mindfulness-based interventions affect mental health with a specific focus on MBAT. We also describe and evaluate data indicating involvement of specific neural circuits and neuroendocrine markers of stress and/or anxiety. Lastly, we suggest areas of focus for future rigorous research on MBAT interventions and propose multiple biobehavioral and physiological mechanisms through which therapeutic benefits may be achieved.

Impact statement

Recent studies demonstrate the therapeutic potential of intensive MBAT and other mindfulness-based interventions for severe health conditions including cancer, heart disease, and anxiety, with effectiveness that rivals and sometimes even exceeds cognitive behavior therapy. MBAT-based approaches appear to be poised to mature into large-scale, cost-effective therapies for mental health disorders and symptoms comorbid with other serious health issues. However, the field currently suffers from inconsistent deployment protocols and needs additional validation data—at the behavioral, neuroendocrine, and neural levels—in order to establish best practices.

Effectiveness of a brief psychological mindfulness-based intervention for the treatment of depression in primary care: study protocol for a randomized controlled clinical trial

BACKGROUND

Depressive symptoms are quite prevalent in Primary Care (PC) settings. The treatment as usual (TAU) in PC is pharmacotherapy, despite the high relapse rates it produces. Many patients would prefer psychotherapy, but specialized services are overloaded. Studies that apply Mindfulness-Based Interventions (MBIs) for the treatment of depression have obtained significant improvements. Brief low-intensity approaches delivered from PC could be a promising approach. This study aims to compare a low-intensity mindfulness intervention for the treatment of depression in PC using different intervention formats - a face-to-face MBI delivered in a group and the same MBI individually applied on the Internet - to a control group that will receive PC medical treatment as usual.

METHODS

A randomized controlled clinical trial will be conducted in PC, with about 120 depressed patients allocated (1:1:1) to three groups: "face-to-face MBI + TAU", "Internet-delivered MBI + TAU", and "TAU alone". The MBI programs will be composed of four modules. The primary outcome will be depressive symptoms, measured through the Beck Depression Inventory, assessed at pre- and post-treatment and 6- and 12-month follow-ups. Other outcomes will be mindfulness, happiness, affectivity, quality of life, and the use of healthcare services. Intention-to-treat analysis using linear mixed models adjusted for baseline scores and routine sociodemographic analysis that could show baseline differences will be conducted. Per-protocol secondary outcome analyses will also be performed.

DISCUSSION

This is the first Spanish RCT to apply a low-intensity face-to-face MBI (plus TAU) to treat depression in PC settings compared to TAU (alone). Moreover, this study will also make it possible to evaluate the same MBI program (plus TAU), but Internet-delivered, considering their cost-effectiveness. Positive results from this RCT might have an important impact on mental health settings, helping to decrease the overload of the system and offering treatment alternatives beyond antidepressant medication through high-quality, flexible PC interventions.

TRIAL REGISTRATION

Clinical Trials.gov NCT03034343 . Trial Registration date 24 January 2017, retrospectively registered.

Lasting connectivity increase and anxiety reduction via transcranial alternating current stimulation

Growing evidence of transcranial alternating current stimulation (tACS) modulating intrinsic neural oscillations has spawned interest in applying tACS to treat psychiatric disorders associated with aberrant neural oscillations. The alpha rhythmic activity is known to dominate neural oscillations at the awake, restful state, while attenuated resting-state alpha activity has been implicated in anxious mood. Administering repeated alpha-frequency tACS (α-tACS; at individual peak alpha frequency; 8–12 Hz) over four consecutive days (in the experiment group, sham stimulation in the control group), we demonstrated immediate and lasting (>24 h) increases in resting-state posterior ➔frontal connectivity in the alpha frequency, quantified by Granger causality. Critically, this connectivity enhancement was accompanied by sustained reductions in both anxious arousal and negative perception of sensory stimuli. Resting-state alpha power also increased, albeit only transiently, reversing to the baseline level within 24 h after tACS. Therefore, the lasting enhancement of long-range alpha connectivity due to α-tACS differs from local alpha activity that is nonetheless conserved, highlighting the adaptability of alpha oscillatory networks. In light of increasing recognition of large-scale network dysfunctions as a transdiagnostic pathophysiology of psychiatric disorders, this enduring connectivity plasticity, along with the behavioral improvements, paves the way for tACS applications in clinical interventions of psychiatric ‘oscillopathies’.

A neurobehavioral account for decentering as the salve for the distressed mind

Distress is commonly characterized by prolonged internal suffering that can range from self-focused processing of negative emotions and stressors, to highly intensely aversive and prolonged emotional states, thereby, worsening or complicating emotional and physical conditions. Decentering represents a metacognitive capacity thought to reflect three interrelated processes: meta-awareness, disidentification from internal experience, and reduced reactivity to thought content-which is reliably increased with mindfulness-based interventions. In this essay, we seek to link the clinical presentation of distress disorders to known or hypothesized disruptions in neural networks that underlie emotion, cognition, and goal directed behavior, and offer a neurobehavioral account for how and why treatments imbued with mindfulness meditation might ameliorate these conditions, in part through increases in decentering.

State-trait influences of Vipassana meditation practice on P3 EEG dynamics

Several studies have demonstrated that meditation naïve subjects can, in just a few weeks, become proficient enough in meditation to show cognitive improvements accompanied with functional and structural changes in the brain. Would long-term exposure to qualitatively different levels of meditative training bring about differences in cognitive processing? Would meditation prior to task performance help separate out these differences? Could the nature of the task influence the findings related to cognitive enhancements? To address these questions, we evaluated cognitive functions in three groups of experienced Vipassana practitioners (Novices: n=22, Mean±SD meditation experience=989±595h; Senior practitioners: 21, 10,510±5313; Teachers: 16, 14,648±9623) who differed in terms of duration and quality of meditative practice. Specifically, we employed "ANGEL" a gamified multilevel oddball paradigm, to assess P3 event-related potentials (ERPs) and associated EEG dynamics-power spectra, event related spectral perturbations (ERSP) and inter-trial coherence (ITC). In order to elicit the state-trait influences of meditation, the cognitive task was performed after the participants had undergone an hour long traditional meditation session. All participants could perform the task well and the gross ERP waveforms were similar for the three groups. As hypothesized, we found distinct state-trait influences of meditation leading to graded differences in P3 EEG dynamics. Specifically, we found reduced theta synchrony, enhanced alpha de-synchrony and lesser theta-alpha coherence in the more proficient meditators. Post hoc analyses revealed several differences between the novice and teacher groups but not as many between novice and seniors suggesting that the senior meditators formed an intermediate group. Our study demonstrates that both quantity and quality of meditation influence EEG dynamics during cognitive processing and that meditation prior to a task can provide additional state-trait effects involved in meeting the specific cognitive demands.

Effects of a Mindfulness Meditation App on Subjective Well-Being: Active Randomized Controlled Trial and Experience Sampling Study

BACKGROUND

Mindfulness training (MT) includes a variety of contemplative practices aimed at promoting intentional awareness of experience, coupled with attitudes of nonjudgment and curiosity. Following the success of 8-week, manualized group interventions, MT has been implemented in a variety of modalities, including smartphone apps that seek to replicate the success of group interventions. However, although smartphone apps are scalable and accessible to a wider swath of population, their benefits remain largely untested.

OBJECTIVE

This study aimed to investigate a newly developed MT app called Wildflowers, which was codeveloped with the laboratory for use in mindfulness research. It was hypothesized that 3 weeks of MT through this app would improve subjective well-being, attentional control, and interoceptive integration, albeit with weaker effects than those published in the 8 week, manualized group intervention literature.

METHODS

Undergraduate students completed 3 weeks of MT with Wildflowers (n=45) or 3 weeks of cognitive training with a game called 2048 (n=41). State training effects were assessed through pre- and postsession ratings of current mood, stress level, and heart rate. Trait training effects were assessed through pre- and postintervention questionnaires canvassing subjective well-being and behavioral task measures of attentional control and interoceptive integration. State and trait training data were analyzed in a multilevel model using emergent latent factors (acceptance, awareness, and openness) to summarize the trait questionnaire battery.

RESULTS

Analyses revealed both state and trait effects specific to MT; participants engaging in MT demonstrated improved mood (r=.14) and a reduction of stress (r=-.13) immediately after each training session compared with before the training session and decreased postsession stress over 3 weeks (r=-.08). In addition, MT relative to cognitive training resulted in greater improvements in attentional control (r=-.24). Interestingly, both groups demonstrated increased subjective ratings of awareness (r=.28) and acceptance (r=.23) from pre- to postintervention, with greater changes in acceptance for the MT group trending (r=.21).

CONCLUSIONS

MT, using a smartphone app, may provide immediate effects on mood and stress while also providing long-term benefits for attentional control. Although further investigation is warranted, there is evidence that with continued usage, MT via a smartphone app may provide long-term benefits in changing how one relates to their inner and outer experiences.

TRIAL REGISTRATION

ClinicalTrials.gov NCT03783793; https://clinicaltrials.gov/ct2/show/NCT03783793 (Archived by WebCite at http://www.webcitation.org/75EF2ehst).

Effects of a 7-Day Meditation Retreat on the Brain Function of Meditators and Non-Meditators During an Attention Task

Meditation as a cognitive enhancement technique is of growing interest in the field of health and research on brain function. The Stroop Word-Color Task (SWCT) has been adapted for neuroimaging studies as an interesting paradigm for the understanding of cognitive control mechanisms. Performance in the SWCT requires both attention and impulse control, which is trained in meditation practices. We presented SWCT inside the MRI equipment to measure the performance of meditators compared with non-meditators before and after a meditation retreat. The aim of this study was to evaluate the effects of a 7-day Zen intensive meditation training (a retreat) on meditators and non-meditators in this task on performance level and neural mechanisms. Nineteen meditators and 14 non-meditators were scanned before and after a 7-day Zen meditation retreat. No significant differences were found between meditators and non-meditators in the number of the correct responses and response time (RT) during SWCT before and after the retreat. Probably, due to meditators training in attention, their brain activity in the contrast incongruent > neutral during the SWCT in the anterior cingulate, ventromedial prefrontal cortex/anterior cingulate, caudate/putamen/pallidum/temporal lobe (center), insula/putamen/temporal lobe (right) and posterior cingulate before the retreat, were reduced compared with non-meditators. After the meditation retreat, non-meditators had reduced activation in these regions, becoming similar to meditators before the retreat. This result could be interpreted as an increase in the brain efficiency of non-meditators (less brain activation in attention-related regions and same behavioral response) promoted by their intensive training in meditation in only 7 days. On the other hand, meditators showed an increase in brain activation in these regions after the same training. Intensive meditation training (retreat) presented distinct effects on the attention-related regions in meditators and non-meditators probably due to differences in expertise, attention processing as well as neuroplasticity.

Dynamic functional connectivity markers of objective trait mindfulness

While mindfulness is commonly viewed as a skill to be cultivated through practice, untrained individuals can also vary widely in dispositional mindfulness. Prior research has identified static neural connectivity correlates of this trait. Here, we use dynamic functional connectivity (DFC) analysis of resting-state fMRI to study time-varying connectivity patterns associated with naturally varying and objectively measured trait mindfulness. Participants were selected from the top and bottom tertiles of performers on a breath-counting task to form high trait mindfulness (HTM; N = 21) and low trait mindfulness (LTM; N = 18) groups. DFC analysis of resting state fMRI data revealed that the HTM group spent significantly more time in a brain state associated with task-readiness - a state characterized by high within-network connectivity and greater anti-correlations between task-positive networks and the default-mode network (DMN). The HTM group transitioned between brain states more frequently, but the dwell time in each episode of the task-ready state was equivalent between groups. These results persisted even after controlling for vigilance. Across individuals, certain connectivity metrics were weakly correlated with self-reported mindfulness as measured by the Five Facet Mindfulness Questionnaire, though these did not survive multiple comparisons correction. In the static connectivity maps, HTM individuals had greater within-network connectivity in the DMN and the salience network, and greater anti-correlations between the DMN and task-positive networks. In sum, DFC features robustly distinguish HTM and LTM individuals, and may be useful biological markers for the measurement of dispositional mindfulness.