Mindfulness-Based Cognitive Therapy Regulates Brain Connectivity in Patients With Late-Life Depression

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.

Cognitive, psychological, and physiological effects of a web-based mindfulness intervention in older adults during the COVID-19 pandemic: an open study

BACKGROUND

The development of effective strategies to maintain good mental health of older adults is a public health priority. Mindfulness-based interventions have the potential to improve psychological well-being and cognitive functions of older adults, but little is known about the effect of such interventions when delivered through internet. During the COVID-19 pandemic we evaluated short- and long-term cognitive, psychological, and physiological effects of a mindfulness-based intervention (MBI) delivered via web-based videoconference in healthy older adults.

METHODS

Fifty older adults participated in an 8-week MBI, which comprised structured 2-h weekly group sessions. A comprehensive evaluation encompassing cognitive (verbal memory, attention and processing speed, executive functions) and psychological assessments (depression and anxiety symptoms, mindfulness, worries, emotion regulation strategies, well-being, interoceptive awareness and sleep) was conducted. Additionally, electroencephalography (EEG) data were recorded before and after the MBI and at the 6-month follow-up (T6). Data were analyzed using an intention-to-treat approach, using linear mixed models adjusted for age. The effect size for time was computed as omega squared.

RESULTS

We observed significant improvements from pre-MBI to post-MBI and at the T6 across several measures. These improvements were notable in the areas of verbal memory (California Verbal Learning Test, p ≤ .007), attention and executive functions (Trail Making Test A and BA, p < .050), interoceptive awareness (Multidimensional Assessment of Interoceptive Awareness, p = .0002 for self-regulation and p < .05 for noticing, body listening, and trusting dimensions), and rumination (Heidelberg Form for Emotion Regulation Strategies, p = .018). These changes were associated with low to medium effect size. Moreover, we observed significant changes in EEG patterns, with a decrease in alpha1 (p = .004) and an increase in alpha2 (p < .0001) from pre-MBI to T6. Notably, improvements in TMTBA and rumination were correlated with the decrease in alpha1 (p < .050), while improvements in TMTA were linked to the increase in alpha2 (p = .025).

CONCLUSIONS

The results of our study show that a web-based MBI in older adults leads to improvements in cognitive and psychological measures, with associated modulations in specific brain rhythms. While these findings are promising, further controlled studies are required to validate these preliminary results.

TRIAL REGISTRATION

The trial has been registered with the United States National Library of Medicine at the National Institutes of Health Registry of Clinical Trials under the code NCT05941143 on July 12, 2023.

Effects of Mindfulness-Based Cognitive Therapy on Depression and Anxiety in Late Life: A Meta-Analysis

Objective

This study aims to assess the efficacy of mindfulness-based cognitive therapy (MBCT) in alleviating depression in older adults.

Methods

A comprehensive search was conducted in 4 electronic databases and 1 registered database from inception up to July 2021 to identify relevant trials. The meta-analysis employed Hedge's g, along with its 95% CI, and associated z and P-values for the included studies, utilizing Comprehensive Meta-Analysis software.

Results

Qualitative synthesis was performed on 5 eligible studies. Evaluation of methodological quality and bias risk across the papers involved scrutiny of key variables due to the heterogeneous research formats. Our findings indicated a significant moderating effect of MBCT against current depressive symptoms in older adults (g = 0.53, 95% Confidence Intervals (CI) = 0.31-0.75) and a similar effect size for anxiety (g = 0.43, 95% CI = 0.20-0.65). However, caution is warranted due to the limited number of studies and potential publication bias. Further extensive research with longer follow-up measures and larger sample sizes is essential.

Conclusion

This study underscores the effectiveness of MBCT as a treatment for anxiety and despair in older individuals. Mindfulness-based cognitive therapy should be recommended for its positive impact on older adults with depression, and the involvement of authorized psychiatric nurses is crucial for conducting successful MBCT interventions. However, caution is warranted due to the limited number of studies and potential publication bias. Further extensive research with longer follow-up measures and larger sample sizes is essential.

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

Introduction

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

Methods

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

Results

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

Conclusion

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

Three potential neurovascular pathways driving the benefits of mindfulness meditation for older adults

Mindfulness meditation has been shown to be beneficial for a range of different health conditions, impacts brain function and structure relatively quickly, and has shown promise with aging samples. Functional magnetic resonance imaging metrics provide insight into neurovascular health which plays a key role in both normal and pathological aging processes. Experimental mindfulness meditation studies that included functional magnetic resonance metrics as an outcome measure may point to potential neurovascular mechanisms of action relevant for aging adults that have not yet been previously examined. We first review the resting-state magnetic resonance studies conducted in exclusively older adult age samples. Findings from older adult-only samples are then used to frame the findings of task magnetic resonance imaging studies conducted in both clinical and healthy adult samples. Based on the resting-state studies in older adults and the task magnetic resonance studies in adult samples, we propose three potential mechanisms by which mindfulness meditation may offer a neurovascular therapeutic benefit for older adults: (1) a direct neurovascular mechanism via increased resting-state cerebral blood flow; (2) an indirect anti-neuroinflammatory mechanism via increased functional connectivity within the default mode network, and (3) a top-down control mechanism that likely reflects both a direct and an indirect neurovascular pathway.

Increased neurocardiological interplay after mindfulness meditation: a brain oscillation-based approach

Background

Brain oscillations facilitate interaction within the brain network and between the brain and heart activities, and the alpha wave, as a prominent brain oscillation, plays a major role in these coherent activities. We hypothesize that mindfully breathing can make the brain and heart activities more coherent in terms of increased connectivity between the electroencephalogram (EEG) and electrocardiogram (ECG) signals.

Methods

Eleven participants (28-52 years) attended 8 weeks of Mindfulness Based Stress Reduction (MBSR) training. EEG and ECG data of two states of mindful breathing and rest, both eye-closed, were recorded before and after the training. EEGLAB was used to analyze the alpha band (8-12 Hz) power, alpha peak frequency (APF), peak power and coherence. FMRIB toolbox was used to extract the ECG data. Heart coherence (HC) and heartbeat evoked potential (HEP) were calculated for further correlation analysis.

Results

After 8 weeks of MBSR training, the correlation between APF and HC increased significantly in the middle frontal region and bilateral temporal regions. The correlation between alpha coherence and heart coherence had similar changes, while alpha peak power did not reflect such changes. In contrast, spectrum analysis alone did not show difference before and after MBSR training.

Conclusion

The brain works in rhythmic oscillation, and this rhythmic connection becomes more coherent with cardiac activity after 8 weeks of MBSR training. Individual APF is relatively stable and its interplay with cardiac activity may be a more sensitive index than power spectrum by monitoring the brain-heart connection. This preliminary study has important implications for the neuroscientific measurement of meditative practice.

The heterogeneity of late-life depression and its pathobiology: a brain network dysfunction disorder

Depression is frequent in older individuals and is often associated with cognitive impairment and increasing risk of subsequent dementia. Late-life depression (LLD) has a negative impact on quality of life, yet the underlying pathobiology is still poorly understood. It is characterized by considerable heterogeneity in clinical manifestation, genetics, brain morphology, and function. Although its diagnosis is based on standard criteria, due to overlap with other age-related pathologies, the relationship between depression and dementia and the relevant structural and functional cerebral lesions are still controversial. LLD has been related to a variety of pathogenic mechanisms associated with the underlying age-related neurodegenerative and cerebrovascular processes. In addition to biochemical abnormalities, involving serotonergic and GABAergic systems, widespread disturbances of cortico-limbic, cortico-subcortical, and other essential brain networks, with disruption in the topological organization of mood- and cognition-related or other global connections are involved. Most recent lesion mapping has identified an altered network architecture with "depressive circuits" and "resilience tracts", thus confirming that depression is a brain network dysfunction disorder. Further pathogenic mechanisms including neuroinflammation, neuroimmune dysregulation, oxidative stress, neurotrophic and other pathogenic factors, such as β-amyloid (and tau) deposition are in discussion. Antidepressant therapies induce various changes in brain structure and function. Better insights into the complex pathobiology of LLD and new biomarkers will allow earlier and better diagnosis of this frequent and disabling psychopathological disorder, and further elucidation of its complex pathobiological basis is warranted in order to provide better prevention and treatment of depression in older individuals.

Nonpharmacologic and Pharmacologic Treatments of Adult Patients With Major Depressive Disorder: A Systematic Review and Network Meta-analysis for a Clinical Guideline by the American College of Physicians

BACKGROUND

Primary care patients and clinicians may prefer alternative options to second-generation antidepressants for major depressive disorder (MDD).

PURPOSE

To compare the benefits and harms of nonpharmacologic treatments with second-generation antidepressants as first-step interventions for acute MDD, and to compare second-step treatment strategies for patients who did not achieve remission after an initial attempt with antidepressants.

DATA SOURCES

English-language studies from several electronic databases from 1 January 1990 to 8 August 2022, trial registries, gray literature databases, and reference lists to identify unpublished research.

STUDY SELECTION

2 investigators independently selected randomized trials of at least 6 weeks' duration.

DATA EXTRACTION

Reviewers abstracted data about study design and conduct, participants, interventions, and outcomes. They dually rated the risk of bias of studies and the certainty of evidence for outcomes of interest.

DATA SYNTHESIS

65 randomized trials met the inclusion criteria; eligible data from nonrandomized studies were not found. Meta-analyses and network meta-analyses indicated similar benefits of most nonpharmacologic treatments and antidepressants as first-step treatments. Antidepressants had higher risks for discontinuation because of adverse events than most other treatments. For second-step therapies, different switching and augmentation strategies provided similar symptomatic relief. The certainty of evidence for most comparisons is low; findings should be interpreted cautiously.

LIMITATIONS

Many studies had methodological limitations or dosing inequalities; publication bias might have affected some comparisons. In some cases, conclusions could not be drawn because of insufficient evidence.

CONCLUSION

Although benefits seem to be similar among first- and second-step MDD treatments, the certainty of evidence is low for most comparisons. Clinicians and patients should focus on options with the most reliable evidence and take adverse event profiles and patient preferences into consideration.

PRIMARY FUNDING SOURCE

American College of Physicians. (PROSPERO: CRD42020204703).

Blunted superior temporal gyrus activity to negative emotional expression after mindfulness-based cognitive therapy for late-life depression

Facial emotion recognition plays an important role in social functioning. Patients with late-life depression (LLD) often have abnormal facial emotion recognition. Mindfulness-based cognitive therapy (MBCT) is beneficial in treating depression. This study examined whether MBCT can act as an effective augmentation of antidepressants and improve facial emotion recognition in patients with LLD and its underlying neural mechanism. Patients with LLD were randomized into two groups (n = 30 per group). The MBCT group received an eight-week MBCT in conjunction with stable medication treatment. The other group was treated as usual (TAU group) with stable medication treatment. The positive affect (PA) scale, negative affect (NA) scale, and facial emotion recognition task with an fMRI scan were performed before and after the trial. After eight weeks of treatment, the repeated ANOVA showed that the PA score in the MBCT group significantly increased [F_(1,54) = 13.31, p = 0.001], but did not change significantly [F_(1,54) = 0.58, p = 0.449] in the TAU group. The NA scores decreased significantly in both the MBCT group [F_(1,54) = 19.01, p < 0.001] and the TAU group [F_(1,54) = 16.16, p < 0.001]. Patients showed an increase in recognition accuracy and speed of angry and sad faces after 8 weeks of MBCT. No improvement was detected in the TAU group after treatment. A significant interaction effect was found in the change of activation of the left superior temporal gyrus (L-STG) to negative emotional expression between time and groups. Furthermore, a decrease in activation of L-STG to negative emotional expression was positively correlated with the increase in PA score. The MBCT is beneficial for improving affect status and facial emotion recognition in patients with LLD, and the L-STG is involved in this process.