Focused attention meditation in healthy adults: A systematic review and meta-analysis of cross-sectional functional MRI studies

Limited Validity of Breath-Counting as a Measure of Mindfulness in Ruminative Adolescents

Objective measurement of mindfulness could help us understand the mechanisms of meditation interventions and how individuals vary in their disposition to be mindful. One proposed measure is the breath-counting task (BCT), which measures how accurately one can count cycles of their breath. Breath counting, which involves sustained attention, meta-awareness, and an internal locus of attention, has been shown in adults to be related to measures of mindfulness even when controlling for established attentional measures. In this study, we test the psychometrics of the BCT in a convenience sample of 78 adolescents with elevated rumination. In preregistered analyses, we related breath-counting measures, including novel objective respiration measures, to a suite of self-report measures as well as the sustained attention to response task (SART). While breath-counting performance showed fair split-half reliability and similar distributions to studies in adults, it did not show the expected positive associations with self-reported mindfulness measures (neither trait nor EMA). Surprisingly, breath-counting accuracy showed negative correlations with a subscale measuring observing of emotions and body sensations, negative correlations with nonreactivity, and performance decrements were larger for individuals scoring more highly on mindfulness in general. The SART showed a small negative correlation with breath-counting resets (an index of mind-wandering). Finally, breath-counting performance was not related to other theoretically relevant clinical, personality, and executive functioning criteria. Our results suggest that, at least in ruminative adolescents, breath-counting may measure a very narrow, contextual form of sustained attention, may not capture other qualities of mindfulness, and may lack predictive validity.

Effects of Tai Chi on executive function, single-leg dynamic balance, and brain functional connectivity in older adults

Although previous studies have confirmed the beneficial effects of Tai Chi Chuan (TCC) on improving balance ability and cognitive function in older adults, the synergistic regulatory mechanisms of TCC on bilateral lower limb muscle activation symmetry, brain functional connectivity(FC) strength, and dynamic balance ability remain unclear. This study aims to investigate the effects of a 9-week TCC training program on the executive function (EF), bilateral lower limb muscle activation symmetry, single-leg dynamic balance ability, and brain FC strength in elderly individuals. It provides valuable new insights into a field that has not been extensively explored before. After 9-week training intervention, (1) The TCC group showed significant improvements in the Y-balance Test (YBTs), with enhanced symmetry in single-leg dynamic balance between the bilateral lower limbs and a significant reduction in the laterality of lower limb muscle activation. (2) TCC training strengthened the FC of related brain regions during YBTs. When performing YBTs with the left and right legs separately, the laterality of the average brain FC strength between the two tasks was significantly reduced. (3) During EF tasks, the reaction time was significantly reduced, and the concentration of oxygenated hemoglobin in the prefrontal cortex increased. Studies have shown that TCC has significantly superior intervention effects compared to brisk walking in improving neuromuscular function in older adults. Through its multisensory integration training model, TCC simultaneously enhances neuromuscular coordination and brain network collaboration efficiency, promoting the adaptive reorganization of dynamic balance control.

Mindfulness as a Way of Reducing Automatic Constraints on Thought

The number of mindfulness-based wellness promotion programs offered by institutions, by governments, and through mobile apps has grown exponentially in the last decade. However, the scientific understanding of what mindfulness is and how it works is still evolving. Here, I focus on 2 common mindfulness practices: focused attention (FA) and open monitoring (OM). First, I summarize what is known about FA and OM meditation at the psychological level. While they share similar emotion regulation goals, they differ in terms of some of their attention regulation goals. Second, I turn to the neuroscientific literature, showing that FA meditation is associated with consistent activations of cortical control network regions and deactivations of cortical default network regions. In contrast, OM meditation seems to be most consistently associated with changes in the functional connectivity patterns of subcortical structures, including the basal ganglia and cerebellum. Finally, I present a novel account of the mental changes that occur during FA and OM meditation as understood from within the Dynamic Framework of Thought-a conceptual framework that distinguishes between deliberate and automatic constraints on thought. Although deliberate self-regulation processes are often emphasized in scientific and public discourse on mindfulness, here I argue that mindfulness may primarily involve changes in automatic constraints on thought. In particular, I argue that mindfulness reduces the occurrence of automatized sequences of mental states or habits of thought. In this way, mindfulness may increase the spontaneity of thought and reduce automatically constrained forms of thought such as rumination and obsessive thought.

Mindfulness Meditation and Network Neuroscience: Review, Synthesis, and Future Directions

Network neuroscience is an interdisciplinary field, which can be used to understand the brain by examining the connections between its constituent elements. In recent years, the application of network neuroscience approaches to study the intricate nature of the structural and functional relationships within the human brain has yielded unique insights into its organization. In this review, we begin by defining network neuroscience and providing an overview of the common metrics that describe the topology of human structural and functional brain networks. Then, we present a detailed overview of a limited but growing body of literature that has leveraged network neuroscience metrics to demonstrate the impact of mindfulness meditation on modulating the fundamental structural and functional network properties of segregation, integration, and influence. Although preliminary, results across studies suggest that mindfulness meditation results in a shift in connector hubs, such as the anterior cingulate cortex, the thalamus, and the mid-insula. Although there is mixed evidence regarding the impact of mindfulness training on global metrics of connectivity, the default mode network exhibits reduced intraconnectivity following mindfulness training. Our review also underscores essential directions for future research, including a more comprehensive examination of mindfulness training and its potential to influence structural and functional connections at the nodal, network, and whole-brain levels. Furthermore, we emphasize the importance of open science, adoption of rigorous study designs to improve the internal validity of studies, and the inclusion of diverse samples in neuroimaging studies to comprehensively characterize the impact of mindfulness on brain organization.

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.

Daily mindfulness practice with and without slow breathing has opposing effects on plasma amyloid beta levels

Prior research suggests that meditation may slow brain aging and reduce the risk of Alzheimer's disease (AD). However, we lack research systematically examining what aspect(s) of meditation may drive such benefits. In particular, it is unknown how breathing patterns during meditation might influence health outcomes associated with AD. In this study, we examined whether two types of mindfulness meditation practices - one with slow breathing and one with normal breathing - differently affect plasma amyloid beta (Aβ) relative to a no-intervention control group. One week of daily mindfulness practice with slow breathing decreased plasma Aβ levels whereas one week of daily mindfulness practice with normal breathing increased them. The no-intervention control group showed no changes in plasma Aβ levels. Slow breathing appears to be a factor through which meditative practices can influence pathways relevant for AD.

Dynamic brain states underlying advanced concentrative absorption meditation: A 7-T fMRI-intensive case study

Advanced meditation consists of states and stages of practice that unfold with mastery and time. Dynamic functional connectivity (DFC) analysis of fMRI could identify brain states underlying advanced meditation. We conducted an intensive DFC case study of a meditator who completed 27 runs of jhāna advanced absorptive concentration meditation (ACAM-J), concurrently with 7-T fMRI and phenomenological reporting. We identified three brain states that marked differences between ACAM-J and nonmeditative control conditions. These states were characterized as a DMN-anticorrelated brain state, a hyperconnected brain state, and a sparsely connected brain state. Our analyses indicate higher prevalence of the DMN-anticorrelated brain state during ACAM-J than control states, and the prevalence increased significantly with deeper ACAM-J states. The hyperconnected brain state was also more common during ACAM-J and was characterized by elevated thalamocortical connectivity and somatomotor network connectivity. The hyperconnected brain state significantly decreased over the course of ACAM-J, associating with self-reports of wider attention and diminished physical sensations. This brain state may be related to sensory awareness. Advanced meditators have developed well-honed abilities to move in and out of different altered states of consciousness, and this study provides initial evidence that functional neuroimaging can objectively track their dynamics.

Dynamic functional connectivity signatures of focused attention on the breath in adolescents

Breathing meditation typically consists of directing attention toward breathing and redirecting attention when the mind wanders. As yet, we do not have a full understanding of the neural mechanisms of breath attention, in particular, how large-scale network interactions may be different between breath attention and rest and how these interactions may be modulated during periods of on-task and off-task attention to the breath. One promising approach may be examining fMRI measures including static connectivity between brain regions as well as dynamic, time-varying brain states. In this study, we analyzed static and dynamic functional connectivity in 72 adolescents during a breath-counting task (BCT), leveraging physiological respiration data to detect objective on-task and off-task periods. During the BCT relative to rest, we identified increases in static connectivity within attention-direction and orienting networks and anticorrelations between attention networks and the DMN. Dynamic connectivity analysis revealed four distinct brain states, including a DMN-anticorrelated brain state, proportionally more present during the BCT than the rest. We found there were distinct brain state markers of (i) breathing tasks vs rest and (ii) momentary on-task vs off-task attention within the BCT, yet in this analysis, no identifiable brain states reflecting between-individual behavioral variability.

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.

Connectome-Based Predictive Modeling of Trait Mindfulness

Trait mindfulness refers to one's disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks. However, it is unclear how generalizable the findings are, how they relate to different components of trait mindfulness, and how other networks and brain areas may be involved. To address these gaps, we conducted the largest resting-state fMRI study of trait mindfulness to-date, consisting of a pre-registered connectome-based predictive modeling analysis in 367 meditation-naïve adults across three samples collected at different sites. In the model-training dataset, we did not find connections that predicted overall trait mindfulness, but we identified neural models of two mindfulness subscales, Acting with Awareness and Non-judging. Models included both positive networks (sets of pairwise connections that positively predicted mindfulness with increasing connectivity) and negative networks, which showed the inverse relationship. The Acting with Awareness and Non-judging positive network models showed distinct network representations involving FPN and DMN, respectively. The negative network models, which overlapped significantly across subscales, involved connections across the whole brain with prominent involvement of somatomotor, visual and DMN networks. Only the negative networks generalized to predict subscale scores out-of-sample, and not across both test datasets. Predictions from both models were also negatively correlated with predictions from a well-established mind-wandering connectome model. We present preliminary neural evidence for a generalizable connectivity models of trait mindfulness based on specific affective and cognitive facets. However, the incomplete generalization of the models across all sites and scanners, limited stability of the models, as well as the substantial overlap between the models, underscores the difficulty of finding robust brain markers of mindfulness facets.

Fears Worth Testing Out: A Systematic Review of the Neural Mechanisms of Treatment Outcome for Anxiety-Related Disorders

With the advent of human neuroimaging, researchers were drawn to the idea that by better understanding the human brain, more effective mental health interventions could be developed. It has been more than 20 years since the first functional magnetic resonance imaging (fMRI) studies were conducted to examine changes in brain activation with anxiety-related treatments and more than 60 studies have since been published in this vein. For the current review, we conduct a systematic review of this literature, focusing on adult studies using task-based fMRI to measure brain activation changes with pharmacologic or psychotherapy interventions for phobia, social anxiety disorder, panic disorder, generalized anxiety disorder, posttraumatic stress disorder, and obsessive-compulsive disorder. Neuroscientific theories of anxiety-related disorders and their treatment have focused on prefrontal-insula-amygdala networks. Treatment-related decreases in amygdala and/or anterior insula activation were identified as the most consistent finding across disorders, with the most consistent results reported for specific phobia. Directionality of change and specific regions implicated in the prefrontal cortex were inconsistent across studies. The potential importance for probing other networks and processes as mechanisms of anxiety treatment was recognized, such as striatal regions underlying inhibitory learning or reward responsivity. Future treatment-fMRI research related to anxiety disorders would benefit from larger sample sizes, use of more nuanced computational approaches, and increased focus on replication. There is continued promise that fMRI research will enhance our understanding of how treatments work and inform the evolution of more effective or personalized mental health treatment.

Effectiveness of meditation for fatigue management: Insight from a comprehensive systematic review and meta-analysis

OBJECTIVE

This systematic review and meta-analysis revealed the effectiveness of meditation in addressing fatigue, given its widespread use as a remedy for sleep disturbances and fatigue.

METHOD

We analyzed 29 randomized controlled trials from MEDLINE and the Cochrane Library, spanning from December 31, 2022. We conducted two metaanalyses using mean difference (MD) with normalized data and standardized mean difference (SMD) with original data.

RESULTS

These trials included various populations, with baseline fatigue severity observed at 52.2 ± 16.0 points among 4104 participants. After an average meditation duration of 9.6 ± 4.7 weeks, fatigue scores decreased significantly by 6.4 points of MD [95% CI, 4.3-8.5] compared to controls. The most significant reduction occurred in the sub-healthy group (MD 8.2 [95% CI, 2.7 to 13.8]), followed by the general group (MD 6.9 [95% CI, 0.4 to 13.4]), and the disease group (MD 5.7 [95% CI, 3.4 to 8.0]). Notably, meditation-based anti-fatigue effects were particularly pronounced for mental fatigue (MD 10.0 [95% CI, 4.3 to 15.6]), especially with expert guidance and supplementary homework.

CONCLUSION

These findings align with meta-analysis results using standardized mean difference (SMD), providing evidence for meditation as an effective nonpharmacological intervention for fatigue management, while also informing effective meditation approaches.

REGISTRATION NUMBER

CRD42023395551 in PROSPERO.

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).

Tai Chi Practice Buffers Aging Effects in Functional Brain Connectivity

Tai Chi (TC) practice has been shown to improve both cognitive and physical function in older adults. However, the neural mechanisms underlying the benefits of TC remain unclear. Our primary aims are to explore whether distinct age-related and TC-practice-related relationships can be identified with respect to either temporal or spatial (within/between-network connectivity) differences. This cross-sectional study examined recurrent neural network dynamics, employing an adaptive, data-driven thresholding approach to source-localized resting-state EEG data in order to identify meaningful connections across time-varying graphs, using both temporal and spatial features derived from a hidden Markov model (HMM). Mann-Whitney U tests assessed between-group differences in temporal and spatial features by age and TC practice using either healthy younger adult controls (YACs, n = 15), healthy older adult controls (OACs, n = 15), or Tai Chi older adult practitioners (TCOAs, n = 15). Our results showed that aging is associated with decreased within-network and between-network functional connectivity (FC) across most brain networks. Conversely, TC practice appears to mitigate these age-related declines, showing increased FC within and between networks in older adults who practice TC compared to non-practicing older adults. These findings suggest that TC practice may abate age-related declines in neural network efficiency and stability, highlighting its potential as a non-pharmacological intervention for promoting healthy brain aging. This study furthers the triple-network model, showing that a balancing and reorientation of attention might be engaged not only through higher-order and top-down mechanisms (i.e., FPN/DAN) but also via the coupling of bottom-up, sensory-motor (i.e., SMN/VIN) networks.

Preventive effect of one-session brief focused attention meditation on state fatigue: Resting state functional magnetic resonance imaging study

INTRODUCTION

The extended practice of meditation may reduce the influence of state fatigue by changing neurocognitive processing. However, little is known about the preventive effects of one-session brief focused attention meditation (FAM) on state fatigue in healthy participants or its potential neural mechanisms. This study examined the preventive effects of one-session brief FAM on state fatigue and its neural correlates using resting-state functional MRI (rsfMRI) measurements.

METHODS

We randomly divided 56 meditation-naïve participants into FAM and control groups. After the first rsfMRI scan, each group performed a 10-minute each condition while wearing a functional near-infrared spectroscopy (fNIRS) device for assessing brain activity. Subsequently, following a second rsfMRI scan, the participants completed a fatigue-inducing task (a Go/NoGo task) for 60 min. We evaluated the temporal changes in the Go/NoGo task performance of participants as an indicator of state fatigue. We then calculated changes in the resting-state functional connectivity (rsFC) of the rsfMRI from before to after each condition and compared them between groups. We also evaluated neural correlates between the changes in rsFC and state fatigue.

RESULTS AND DISCUSSION

The fNIRS measurements indicated differences in brain activity during each condition between the FAM and control groups, showing decreased medial prefrontal cortex activity and decreased functional connectivity between the medial prefrontal cortex and middle frontal gyrus. The control group exhibited a decrement in Go/NoGo task performance over time, whereas the FAM group did not. These results, thus, suggested that FAM could prevent state fatigue. Compared with the control group, the rsFC analysis revealed a significant increase in the connectivity between the left dorsomedial prefrontal cortex and right superior parietal lobule in the FAM group, suggesting a modification of attention regulation by cognitive effort. In the control group, increased connectivity was observed between the bilateral posterior cingulate cortex and left inferior occipital gyrus, which might be associated with poor attention regulation and reduced higher-order cognitive function. Additionally, the change in the rsFC of the control group was related to state fatigue.

CONCLUSION

Our findings suggested that one session of 10-minute FAM could prevent behavioral state fatigue by employing cognitive effort to modify attention regulation as well as suppressing poor attention regulation and reduced higher-order cognitive function.

Connectome predictive modeling of trait mindfulness

Introduction

Trait mindfulness refers to one's disposition or tendency to pay attention to their experiences in the present moment, in a non-judgmental and accepting way. Trait mindfulness has been robustly associated with positive mental health outcomes, but its neural underpinnings are poorly understood. Prior resting-state fMRI studies have associated trait mindfulness with within- and between-network connectivity of the default-mode (DMN), fronto-parietal (FPN), and salience networks. However, it is unclear how generalizable the findings are, how they relate to different components of trait mindfulness, and how other networks and brain areas may be involved.

Methods

To address these gaps, we conducted the largest resting-state fMRI study of trait mindfulness to-date, consisting of a pre-registered connectome predictive modeling analysis in 367 adults across three samples collected at different sites.

Results

In the model-training dataset, we did not find connections that predicted overall trait mindfulness, but we identified neural models of two mindfulness subscales, Acting with Awareness and Non-judging. Models included both positive networks (sets of pairwise connections that positively predicted mindfulness with increasing connectivity) and negative networks, which showed the inverse relationship. The Acting with Awareness and Non-judging positive network models showed distinct network representations involving FPN and DMN, respectively. The negative network models, which overlapped significantly across subscales, involved connections across the whole brain with prominent involvement of somatomotor, visual and DMN networks. Only the negative networks generalized to predict subscale scores out-of-sample, and not across both test datasets. Predictions from both models were also negatively correlated with predictions from a well-established mind-wandering connectome model.

Conclusions

We present preliminary neural evidence for a generalizable connectivity models of trait mindfulness based on specific affective and cognitive facets. However, the incomplete generalization of the models across all sites and scanners, limited stability of the models, as well as the substantial overlap between the models, underscores the difficulty of finding robust brain markers of mindfulness facets.

Event-related prefrontal activations during online video game playing are modulated by game mechanics, physiological arousal and the amount of daily playing

There is a trend to study human brain functions in ecological contexts and in relation to human factors. In this study, functional near-infrared spectroscopy (fNIRS) was used to record real-time prefrontal activities in 42 male university student habitual video game players when they played a round of multiplayer online battle arena game, League of Legends. A content-based event coding approach was used to analyze regional activations in relation to event type, physiological arousal indexed by heart rate (HR) change, and individual characteristics of the player. Game events Slay and Slain were found to be associated with similar HR and prefrontal responses before the event onset, but differential responses after the event onset. Ventrolateral prefrontal cortex (VLPFC) activation preceding the Slay onset correlated positively with HR change, whereas activations in dorsolateral prefrontal cortex (DLPFC) and rostral frontal pole area (FPAr) preceding the Slain onset were predicted by self-reported hours of weekly playing (HoWP). Together, these results provide empirical evidence to support the notion that event-related regional prefrontal activations during online video game playing are shaped by game mechanics, in-game dynamics of physiological arousal and individual characteristics the players.

Inducing a meditative state by artificial perturbations: A mechanistic understanding of brain dynamics underlying meditation

Contemplative neuroscience has increasingly explored meditation using neuroimaging. However, the brain mechanisms underlying meditation remain elusive. Here, we implemented a mechanistic framework to explore the spatiotemporal dynamics of expert meditators during meditation and rest, and controls during rest. We first applied a model-free approach by defining a probabilistic metastable substate (PMS) space for each condition, consisting of different probabilities of occurrence from a repertoire of dynamic patterns. Moreover, we implemented a model-based approach by adjusting the PMS of each condition to a whole-brain model, which enabled us to explore in silico perturbations to transition from resting-state to meditation and vice versa. Consequently, we assessed the sensitivity of different brain areas regarding their perturbability and their mechanistic local-global effects. Overall, our work reveals distinct whole-brain dynamics in meditation compared to rest, and how transitions can be induced with localized artificial perturbations. It motivates future work regarding meditation as a practice in health and as a potential therapy for brain disorders.

Longitudinal neurofunctional changes in medication overuse headache patients after mindfulness practice in a randomized controlled trial (the MIND-CM study)

BACKGROUND

Mindfulness practice has gained interest in the management of Chronic Migraine associated with Medication Overuse Headache (CM-MOH). Mindfulness is characterized by present-moment self-awareness and relies on attention control and emotion regulation, improving headache-related pain management. Mindfulness modulates the Default Mode Network (DMN), Salience Network (SN), and Fronto-Parietal Network (FPN) functional connectivity. However, the neural mechanisms underlying headache-related pain management with mindfulness are still unclear. In this study, we tested neurofunctional changes after mindfulness practice added to pharmacological treatment as usual in CM-MOH patients.

METHODS

The present study is a longitudinal phase-III single-blind Randomized Controlled Trial (MIND-CM study; NCT03671681). Patients had a diagnosis of CM-MOH, no history of neurological and severe psychiatric comorbidities, and were attending our specialty headache centre. Patients were divided in Treatment as Usual (TaU) and mindfulness added to TaU (TaU + MIND) groups. Patients underwent a neuroimaging and clinical assessment before the treatment and after one year. Longitudinal comparisons of DMN, SN, and FPN connectivity were performed between groups and correlated with clinical changes. Vertex-wise analysis was performed to assess cortical thickness changes.

RESULTS

177 CM-MOH patients were randomized to either TaU group or TaU + MIND group. Thirty-four patients, divided in 17 TaU and 17 TaU + MIND, completed the neuroimaging follow-up. At the follow-up, both groups showed an improvement in most clinical variables, whereas only TaU + MIND patients showed a significant headache frequency reduction (p = 0.028). After one year, TaU + MIND patients showed greater SN functional connectivity with the left posterior insula (p-FWE = 0.007) and sensorimotor cortex (p-FWE = 0.026). In TaU + MIND patients only, greater SN-insular connectivity was associated with improved depression scores (r = -0.51, p = 0.038). A longitudinal increase in cortical thickness was observed in the insular cluster in these patients (p = 0.015). Increased anterior cingulate cortex thickness was also reported in TaU + MIND group (p-FWE = 0.02).

CONCLUSIONS

Increased SN-insular connectivity might modulate chronic pain perception and the management of negative emotions. Enhanced SN-sensorimotor connectivity could reflect improved body-awareness of painful sensations. Expanded cingulate cortex thickness might sustain improved cognitive processing of nociceptive information. Our findings unveil the therapeutic potential of mindfulness and the underlying neural mechanisms in CM-MOH patients.

TRIAL REGISTRATION

Name of Registry; MIND-CM study; Registration Number ClinicalTrials.gov identifier: NCT0367168; Registration Date: 14/09/2018.

Functional connectivity changes in meditators and novices during yoga nidra practice

Yoga nidra (YN) practice aims to induce a deeply relaxed state akin to sleep while maintaining heightened awareness. Despite the growing interest in its clinical applications, a comprehensive understanding of the underlying neural correlates of the practice of YN remains largely unexplored. In this fMRI investigation, we aim to discover the differences between wakeful resting states and states attained during YN practice. The study included individuals experienced in meditation and/or yogic practices, referred to as 'meditators' (n = 30), and novice controls (n = 31). The GLM analysis, based on audio instructions, demonstrated activation related to auditory cues without concurrent default mode network (DMN) deactivation. DMN seed based functional connectivity (FC) analysis revealed significant reductions in connectivity among meditators during YN as compared to controls. We did not find differences between the two groups during the pre and post resting state scans. Moreover, when DMN-FC was compared between the YN state and resting state, meditators showed distinct decoupling, whereas controls showed increased DMN-FC. Finally, participants exhibit a remarkable correlation between reduced DMN connectivity during YN and self-reported hours of cumulative meditation and yoga practice. Together, these results suggest a unique neural modulation of the DMN in meditators during YN which results in being restful yet aware, aligned with their subjective experience of the practice. The study deepens our understanding of the neural mechanisms of YN, revealing distinct DMN connectivity decoupling in meditators and its relationship with meditation and yoga experience. These findings have interdisciplinary implications for neuroscience, psychology, and yogic disciplines.

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.

Within-subject reliability of brain networks during advanced meditation: An intensively sampled 7 Tesla MRI case study

Advanced meditation such as jhana meditation can produce various altered states of consciousness (jhanas) and cultivate rewarding psychological qualities including joy, peace, compassion, and attentional stability. Mapping the neurobiological substrates of jhana meditation can inform the development and application of advanced meditation to enhance well-being. Only two prior studies have attempted to investigate the neural correlates of jhana meditation, and the rarity of adept practitioners has largely restricted the size and extent of these studies. Therefore, examining the consistency and reliability of observed brain responses associated with jhana meditation can be valuable. In this study, we aimed to characterize functional magnetic resonance imaging (fMRI) reliability within a single subject over repeated runs in canonical brain networks during jhana meditation performed by an adept practitioner over 5 days (27 fMRI runs) inside an ultra-high field 7 Tesla MRI scanner. We found that thalamus and several cortical networks, that is, the somatomotor, limbic, default-mode, control, and temporo-parietal, demonstrated good within-subject reliability across all jhanas. Additionally, we found that several other relevant brain networks (e.g., attention, salience) showed noticeable increases in reliability when fMRI measurements were adjusted for variability in self-reported phenomenology related to jhana meditation. Overall, we present a preliminary template of reliable brain areas likely underpinning core neurocognitive elements of jhana meditation, and highlight the utility of neurophenomenological experimental designs for better characterizing neuronal variability associated with advanced meditative states.

Strength of spatial correlation between gray matter connectivity and patterns of proto-oncogene and neural network construction gene expression is associated with diffuse glioma survival

Introduction

Like other forms of neuropathology, gliomas appear to spread along neural pathways. Accordingly, our group and others have previously shown that brain network connectivity is highly predictive of glioma survival. In this study, we aimed to examine the molecular mechanisms of this relationship via imaging transcriptomics.

Methods

We retrospectively obtained presurgical, T1-weighted MRI datasets from 669 adult patients, newly diagnosed with diffuse glioma. We measured brain connectivity using gray matter networks and coregistered these data with a transcriptomic brain atlas to determine the spatial co-localization between brain connectivity and expression patterns for 14 proto-oncogenes and 3 neural network construction genes.

Results

We found that all 17 genes were significantly co-localized with brain connectivity (p < 0.03, corrected). The strength of co-localization was highly predictive of overall survival in a cross-validated Cox Proportional Hazards model (mean area under the curve, AUC = 0.68 +/- 0.01) and significantly (p < 0.001) more so for a random forest survival model (mean AUC = 0.97 +/- 0.06). Bayesian network analysis demonstrated direct and indirect causal relationships among gene-brain co-localizations and survival. Gene ontology analysis showed that metabolic processes were overexpressed when spatial co-localization between brain connectivity and gene transcription was highest (p < 0.001). Drug-gene interaction analysis identified 84 potential candidate therapies based on our findings.

Discussion

Our findings provide novel insights regarding how gene-brain connectivity interactions may affect glioma survival.

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.

Psychological and attentional outcomes following acute mindfulness induction among high anxiety individuals: A systematic review and meta-analysis

BACKGROUND

Training outcomes of mindfulness interventions for anxiety have been extensively researched. Less is known about the acute effects of mindfulness induction and associated mechanisms. This systematic review aimed to identify 1) the effect of mindfulness induction on pre-post measures of state anxiety and attention among adults experiencing high levels of anxiety; and 2) the impact of predictors, mediators and moderators on post-induction changes in anxiety and attention. State distress and mindfulness were included as secondary outcomes.

METHODS

A systematic search was conducted in November 2021 in electronic databases using relevant search terms. Five studies (four randomised controlled trials and one non-randomised controlled trial) were included, comprising a total of 277 participants with elevated trait/generalised anxiety. Each study used a brief audio-based mindfulness induction exercise.

RESULTS

The meta-analysis indicated mindfulness induction had medium and large effects on state anxiety (k = 3, n = 100, g = -0.60, 95%CI [-1.04, -0.16]; p = .008) and state mindfulness (k = 2, n = 110, g = 0.91, 95%CI [0.52, 1.30], p < .001), respectively, when compared with non-therapeutic control conditions. Furthermore, two studies showed small and moderate effects of mindfulness on state anxiety when compared to therapeutic active controls, but were not pooled in a meta-analysis. While results could not be pooled for attention, there was limited evidence of behavioural improvements on tasks measuring aspects of attention following mindfulness induction. However, one study found an increase in Low Beta to High Beta ratio and a reduction in Beta activity in the Anterior Cingulate Cortex following mindfulness induction. Moreover, another study found aspects of state mindfulness mediated reductions in state anxiety.

LIMITATIONS

A small number of studies were included in the review, with high risk of bias and low certainty of evidence present.

CONCLUSION

The findings support the use of mindfulness induction to reduce state anxiety in anxious individuals but suggest gains in state mindfulness may be a more realistic expected outcome. Further controlled trials are needed to delineate the relative effects of objectively assessed anxiety outcomes from mindfulness induction in clinically defined samples.

Inside the mindful moment: The effects of brief mindfulness practice on large-scale network organization and intimate partner aggression

Mindfulness can produce neuroplastic changes that support adaptive cognitive and emotional functioning. Recently interest in single-exercise mindfulness instruction has grown considerably because of the advent of mobile health technology. Accordingly, the current study sought to extend neural models of mindfulness by investigating transient states of mindfulness during single-dose exposure to focused attention meditation. Specifically, we examined the ability of a brief mindfulness induction to attenuate intimate partner aggression via adaptive changes to intrinsic functional brain networks. We employed a dual-regression approach to examine a large-scale functional network organization in 50 intimate partner dyads (total n = 100) while they received either mindfulness (n = 50) or relaxation (n = 50) instruction. Mindfulness instruction reduced coherence within the Default Mode Network and increased functional connectivity within the Frontoparietal Control and Salience Networks. Additionally, mindfulness decoupled primary visual and attention-linked networks. Yet, this induction was unable to elicit changes in subsequent intimate partner aggression, and such aggression was broadly unassociated with any of our network indices. These findings suggest that minimal doses of focused attention-based mindfulness can promote transient changes in large-scale brain networks that have uncertain implications for aggressive behavior.

Strength of spatial correlation between structural brain network connectivity and brain-wide patterns of proto-oncogene and neural network construction gene expression is associated with diffuse glioma survival

Like other forms of neuropathology, gliomas appear to spread along neural pathways. Accordingly, our group and others have previously shown that brain network connectivity is highly predictive of glioma survival. In this study, we aimed to examine the molecular mechanisms of this relationship via imaging transcriptomics. We retrospectively obtained presurgical, T1-weighted MRI datasets from 669 adult patients, newly diagnosed with diffuse glioma. We measured brain connectivity using gray matter networks and coregistered these data with a transcriptomic brain atlas to determine the spatial co-localization between brain connectivity and expression patterns for 14 proto-oncogenes and 3 neural network construction genes. We found that all 17 genes were significantly co-localized with brain connectivity (p < 0.03, corrected). The strength of co-localization was highly predictive of overall survival in a cross-validated Cox Proportional Hazards model (mean area under the curve, AUC = 0.68 +/- 0.01) and significantly (p < 0.001) more so for a random forest survival model (mean AUC = 0.97 +/- 0.06). Bayesian network analysis demonstrated direct and indirect causal relationships among gene-brain co-localizations and survival. Gene ontology analysis showed that metabolic processes were overexpressed when spatial co-localization between brain connectivity and gene transcription was highest (p < 0.001). Drug-gene interaction analysis identified 84 potential candidate therapies based on our findings. Our findings provide novel insights regarding how gene-brain connectivity interactions may affect glioma survival.

Meditation attenuates default-mode activity: A pilot study using ultra-high field 7 Tesla MRI

OBJECTIVES

Mapping the neurobiology of meditation has been bolstered by functional MRI (fMRI) research, with advancements in ultra-high field 7 Tesla fMRI further enhancing signal quality and neuroanatomical resolution. Here, we utilize 7 Tesla fMRI to examine the neural substrates of meditation and replicate existing widespread findings, after accounting for relevant physiological confounds.

METHODS

In this feasibility study, we scanned 10 beginner meditators (N = 10) while they either attended to breathing (focused attention meditation) or engaged in restful thinking (non-focused rest). We also measured and adjusted the fMRI signal for key physiological differences between meditation and rest. Finally, we explored changes in state mindfulness, state anxiety and focused attention attributes for up to 2 weeks following the single fMRI meditation session.

RESULTS

Group-level task fMRI analyses revealed significant reductions in activity during meditation relative to rest in default-mode network hubs, i.e., antero-medial prefrontal and posterior cingulate cortices, precuneus, as well as visual and thalamic regions. These findings survived stringent statistical corrections for fluctuations in physiological responses which demonstrated significant differences (p < 0.05/n, Bonferroni controlled) between meditation and rest. Compared to baseline, State Mindfulness Scale (SMS) scores were significantly elevated (F(3,9) = 8.16, p < 0.05/n, Bonferroni controlled) following the fMRI meditation session, and were closely maintained at 2-week follow up.

CONCLUSIONS

This pilot study establishes the feasibility and utility of investigating focused attention meditation using ultra-high field (7 Tesla) fMRI, by supporting widespread evidence that focused attention meditation attenuates default-mode activity responsible for self-referential processing. Future functional neuroimaging studies of meditation should control for physiological confounds and include behavioural assessments.

Neural network of metaphor comprehension: an ALE meta-analysis and MACM analysis

The comprehension of metaphor, a vivid and figurative language, is a complex endeavor requiring cooperation among multiple cognitive systems. There are still many important questions regarding neural mechanisms implicated in specific types of metaphor. To address these questions, we conducted activation likelihood estimation meta-analyses on 30 studies (containing data of 480 participants) and meta-analytic connectivity modeling analyses. First, the results showed that metaphor comprehension engaged the inferior frontal gyrus, middle temporal gyrus, fusiform gyrus, lingual gyrus, and middle occipital gyrus-all in the left hemisphere. In addition to the commonly reported networks of language and attention, metaphor comprehension engaged networks of visual. Second, sub-analysis showed that the contextual complexity can modulate figurativeness, with the convergence on the left fusiform gyrus during metaphor comprehension at discourse-level. Especially, right hemisphere only showed convergence in studies of novel metaphors, suggesting that the right hemisphere is more associated with difficulty than metaphorical. The work here extends knowledge of the neural mechanisms underlying metaphor comprehension in individual brain regions and neural networks.

Do mindfulness-based interventions change brain function in people with substance dependence? A systematic review of the fMRI evidence

BACKGROUND

Substance use disorders (SUDs) affect ~ 35 million people globally and are associated with strong cravings, stress, and brain alterations. Mindfulness-based interventions (MBIs) can mitigate the adverse psychosocial outcomes of SUDs, but the underlying neurobiology is unclear. Emerging findings were systematically synthesised from fMRI studies about MBI-associated changes in brain function in SUDs and their associations with mindfulness, drug quantity, and craving.

METHODS

PsycINFO, Medline, CINAHL, PubMed, Scopus, and Web of Science were searched. Seven studies met inclusion criteria.

RESULTS

Group by time effects indicated that MBIs in SUDs (6 tobacco and 1 opioid) were associated with changes in the function of brain pathways implicated in mindfulness and addiction (e.g., anterior cingulate cortex and striatum), which correlated with greater mindfulness, lower craving and drug quantity.

CONCLUSIONS

The evidence for fMRI-related changes with MBI in SUD is currently limited. More fMRI studies are required to identify how MBIs mitigate and facilitate recovery from aberrant brain functioning in SUDs.

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.