Multi-dimensional modulations of α and γ cortical dynamics following mindfulness-based cognitive therapy in Major Depressive Disorder

The Role of Alpha Oscillations among the Main Neuropsychiatric Disorders in the Adult and Developing Human Brain: Evidence from the Last 10 Years of Research

Alpha oscillations (7-13 Hz) are the dominant rhythm in both the resting and active brain. Accordingly, translational research has provided evidence for the involvement of aberrant alpha activity in the onset of symptomatological features underlying syndromes such as autism, schizophrenia, major depression, and Attention Deficit and Hyperactivity Disorder (ADHD). However, findings on the matter are difficult to reconcile due to the variety of paradigms, analyses, and clinical phenotypes at play, not to mention recent technical and methodological advances in this domain. Herein, we seek to address this issue by reviewing the literature gathered on this topic over the last ten years. For each neuropsychiatric disorder, a dedicated section will be provided, containing a concise account of the current models proposing characteristic alterations of alpha rhythms as a core mechanism to trigger the associated symptomatology, as well as a summary of the most relevant studies and scientific contributions issued throughout the last decade. We conclude with some advice and recommendations that might improve future inquiries within this field.

Self-compassion and related factors in severe mental illness: A scoping review

PURPOSE

To clarify what is known and identify research gaps on the role of self-compassion (SC) and potential interventions for individuals with severe mental illness (SMI).

DESIGN AND METHODS

We analyzed 24 studies of SC in schizophrenia spectrum disorder, bipolar disorder (BD), and major depressive disorder (MDD).

FINDINGS

Mindfulness-based cognitive therapy (MBCT) was the most common intervention. Predicting depression by SC was common in MDD and BD; however, relationships between demographics/clinical variables and SC in BD and schizophrenia spectrum disorder remain unclear.

PRACTICE IMPLICATIONS

MBCT increases SC in SMI. Data regarding predictors of SC are limited, especially in schizophrenia.

Mindfulness-Based Stress Reduction and Mindfulness-Based Cognitive Therapy for Depression: a Systematic Review of Cognitive Outcomes

Objectives

Summarize existing literature on cognitive outcomes of MBSR and MBCT for individuals with depression.

Methods

Following PRISMA (2021) guidance, we conducted a systematic review. We searched databases for studies published from 2000 to 2020 which examined cognitive outcomes of MBSR and MBCT in individuals with at least mild depressive symptoms. The search result in 10 studies (11 articles) meeting inclusion criteria.

Results

We identified five single armed trials and five randomized controlled trials. Results indicated that three studies did not show any improvements on cognitive outcomes, and seven studies showed at least one improvement in cognitive outcomes.

Conclusions

Overall, the review highlighted several inconsistencies in the literature including inconsistent use of terminology, disparate samples, and inconsistent use of methodology. These inconsistencies may help to explain the mixed results of MBSR and MBCT on cognitive outcomes. Recommendations include a more streamlined approach to studying cognitive outcomes in depressed individuals in the context of MBSR and MBCT.

A Review of Neurofeedback Training for Improving Sport Performance From the Perspective of User Experience

Neurofeedback training (NFT) is a non-invasive, safe, and effective method of regulating the nerve state of the brain. Presently, NFT is widely used to prevent and rehabilitate brain diseases and improve an individual's external performance. Among the various NFT methods, NFT to improve sport performance (SP-NFT) has become an important research and application focus worldwide. Several studies have shown that the method is effective in improving brain function and motor control performance. However, appropriate reviews and prospective directions for this technology are lacking. This paper proposes an SP-NFT classification method based on user experience, classifies and discusses various SP-NFT research schemes reported in the existing literature, and reviews the technical principles, application scenarios, and usage characteristics of different SP-NFT schemes. Several key issues in SP-NFT development, including the factors involved in neural mechanisms, scheme selection, learning basis, and experimental implementation, are discussed. Finally, directions for the future development of SP-NFT, including SP-NFT based on other electroencephalograph characteristics, SP-NFT integrated with other technologies, and SP-NFT commercialization, are suggested. These discussions are expected to provide some valuable ideas to researchers in related fields.

Mindfulness Meditation Intervention Alters Neurophysiological Symptoms of Anxiety and Depression in Preadolescents

Abstract. Mindfulness meditation interventions (MMIs) are formal training programs which utilize mindfulness techniques to improve attentional control and reduce stress and anxiety. Past investigations have shown that mindfulness-based interventions are effective in improving symptoms of anxiety and depression in both adolescents and adults, making this a promising natural approach to treating mood disorders. The current study sought to examine the neurophysiological effects of a 10-week MMI, in a relatively unexplored age-range (7–10 years). The non-clinical participants demonstrated increases in interhemispheric alpha coherence, as well as increased theta, alpha, and beta power particularly in frontal and central areas; reflecting a lower neurological risk for anxiety development. However, two common measures linked to anxiety, frontal and posterior alpha asymmetry remained largely unchanged following the training period. Still, these preliminary results exemplify the potentially positive effects of mindfulness meditation on preadolescents; this time on neurophysiological functioning.

Linear and Nonlinear EEG-Based Functional Networks in Anxiety Disorders

Electrocortical network dynamics are integral to brain function. Linear and nonlinear connectivity applications enrich neurophysiological investigations into anxiety disorders. Discrete EEG-based connectivity networks are unfolding with some homogeneity for anxiety disorder subtypes. Attenuated delta/theta/beta connectivity networks, pertaining to anterior-posterior nodes, characterize panic disorder. Nonlinear measures suggest reduced connectivity of ACC as an executive neuro-regulator in germane "fear circuitry networks" might be more central than considered. Enhanced network complexity and theta network efficiency at rest define generalized anxiety disorder, with similar tonic hyperexcitability apparent in social anxiety disorder further extending to task-related/state functioning. Dysregulated alpha connectivity and integration of mPFC-ACC/mPFC-PCC relays implicated with attentional flexibility and choice execution/congruence neurocircuitry are observed in trait anxiety. Conversely, state anxiety appears to recruit converging delta and beta connectivity networks as panic, suggesting trait and state anxiety are modulated by discrete neurobiological mechanisms. Furthermore, EEG connectivity dynamics distinguish anxiety from depression, despite prevalent clinical comorbidity. Rethinking mechanisms implicated in the etiology, maintenance, and treatment of anxiety from the perspective of EEG network science across micro- and macroscales serves to shed light and move the field forward.

Mindfulness-Based Blood Pressure Reduction (MB-BP): Stage 1 single-arm clinical trial

BACKGROUND AND OBJECTIVES

Impacts of mindfulness-based programs on blood pressure remain equivocal, possibly because the programs are not adapted to engage with determinants of hypertension, or due to floor effects. Primary objectives were to create a customized Mindfulness-Based Blood Pressure Reduction (MB-BP) program, and to evaluate acceptability, feasibility, and effects on hypothesized proximal self-regulation mechanisms. Secondary outcomes included modifiable determinants of blood pressure (BP), and clinic-assessed systolic blood pressure (SBP).

METHODS

This was a Stage 1 single-arm trial with one year follow-up. Focus groups and in-depth interviews were performed to evaluate acceptability and feasibility. Self-regulation outcomes, and determinants of BP, were assessed using validated questionnaires or objective assessments. The MB-BP curriculum was adapted from Mindfulness-Based Stress Reduction to direct participants' mindfulness skills towards modifiable determinants of blood pressure.

RESULTS

Acceptability and feasibility findings showed that of 53 eligible participants, 48 enrolled (91%). Of these, 43 (90%) attended at least 7 of the 10 MB-BP classes; 43 were followed to one year (90%). Focus groups (n = 19) and semi-structured interviews (n = 10) showed all participants viewed the delivery modality favorably, and identified logistic considerations concerning program access as barriers. A priori selected primary self-regulation outcomes showed improvements at one-year follow-up vs. baseline, including attention control (Sustained Attention to Response Task correct no-go score, p<0.001), emotion regulation (Difficulties in Emotion Regulation Score, p = 0.02), and self-awareness (Multidimensional Assessment of Interoceptive Awareness, p<0.001). Several determinants of hypertension were improved in participants not adhering to American Heart Association guidelines at baseline, including physical activity (p = 0.02), Dietary Approaches to Stop Hypertension-consistent diet (p<0.001), and alcohol consumption (p<0.001). Findings demonstrated mean 6.1 mmHg reduction in SBP (p = 0.008) at one year follow-up; effects were most pronounced in Stage 2 uncontrolled hypertensives (SBP≥140 mmHg), showing 15.1 mmHg reduction (p<0.001).

CONCLUSION

MB-BP has good acceptability and feasibility, and may engage with self-regulation and behavioral determinants of hypertension.

Mindfulness meditators show altered distributions of early and late neural activity markers of attention in a response inhibition task

Attention is vital for optimal behavioural performance in every-day life. Mindfulness meditation has been shown to enhance attention. However, the components of attention altered by meditation and the related neural activities are underexplored. In particular, the contributions of inhibitory processes and sustained attention are not well understood. To address these points, 34 meditators were compared to 28 age and gender matched controls during electroencephalography (EEG) recordings of neural activity during a Go/Nogo response inhibition task. This task generates a P3 event related potential, which is related to response inhibition processes in Nogo trials, and attention processes across both trial types. Compared with controls, meditators were more accurate at responding to Go and Nogo trials. Meditators showed a more frontally distributed P3 to both Go and Nogo trials, suggesting more frontal involvement in sustained attention rather than activity specific to response inhibition. Unexpectedly, meditators also showed increased positivity over the right parietal cortex prior to visual information reaching the occipital cortex (during the pre-C1 window). Both results were positively related to increased accuracy across both groups. The results suggest that meditators show altered engagement of neural regions related to attention, including both higher order processes generated by frontal regions, and sensory anticipation processes generated by poster regions. This activity may reflect an increased capacity to modulate a range of neural processes in order to meet task requirements. This increased capacity may underlie the improved attentional function observed in mindfulness meditators.

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.

EEG classification of driver mental states by deep learning

Driver fatigue is attracting more and more attention, as it is the main cause of traffic accidents, which bring great harm to society and families. This paper proposes to use deep convolutional neural networks, and deep residual learning, to predict the mental states of drivers from electroencephalography (EEG) signals. Accordingly we have developed two mental state classification models called EEG-Conv and EEG-Conv-R. Tested on intra- and inter-subject, our results show that both models outperform the traditional LSTM- and SVM-based classifiers. Our major findings include (1) Both EEG-Conv and EEG-Conv-R yield very good classification performance for mental state prediction; (2) EEG-Conv-R is more suitable for inter-subject mental state prediction; (3) EEG-Conv-R converges more quickly than EEG-Conv. In summary, our proposed classifiers have better predictive power and are promising for application in practical brain-computer interaction .

Gamma oscillations as a biomarker for major depression: an emerging topic

Identifying biomarkers for major depression is of high importance for improving diagnosis and treatment of this common and debilitating neuropsychiatric disorder, as the field seeks to move toward both personalized and more effective treatments. Here we focus on electroencephalography (EEG) or direct scalp voltage recordings as such a biomarker, with an emphasis on gamma and high gamma oscillations (or "rhythms"). In the last several decades, alpha and theta band rhythms have been found to provide information on depressive state as well as recovery, but the gamma band is less well characterized with respect to depression. We summarize some key findings on gamma rhythms (especially their amplitude) as a biomarker or endophenotype for major depression. These studies suggest: (1) under certain conditions gamma rhythms can distinguish subjects with major depression from healthy controls, (2) gamma may distinguish bipolar disorder from unipolar depression, (3) various pharmacological and non-pharmacological treatments that counteract depression also alter gamma, (4) animal models of depression-like behavior show gamma abnormalities, with changes in gamma associated with therapeutic recovery. The most informative approaches in the future may combine profiles of gamma band power across the brain to assess ratios of activity across regions. Overall we have good evidence to suggest that gamma rhythms may provide objective information on major depressive disease status, but we will need further work to better define the precise measures to follow.

Spontaneous analogising caused by text stimuli in design thinking: differences between higher- and lower-creativity groups

Understanding the cognitive processes used in creative practices is essential to design research. In this study, electroencephalography was applied to investigate the brain activations of visual designers when they responded to various types of word stimuli during design thinking. Thirty visual designers were recruited, with the top third and bottom third of the participants divided into high-creativity (HC) and low-creativity (LC) groups. The word stimuli used in this study were two short poems, adjectives with similar meanings, and adjectives with opposing meanings. The derived results are outlined as follows: (1) the brain activations of the designers increased in the frontal and right temporal regions and decreased in the right prefrontal region; (2) the negative association between the right temporal and middle frontal regions was notable; (3) the differences in activations caused by distinct word stimuli varied between HC and LC designers; (4) the spectral power in the middle frontal region of HC designers was lower than that of LC designers during the short love poem task; (5) the spectral power in the bilateral temporal regions of HC designers was higher than that of LC designers during the short autumn poem task; (6) the spectral power in the frontoparietal region of HC designers was lower than that of LC designers during the similar concept task; and (7) the spectral power in the frontoparietal and left frontotemporal regions of HC designers was higher than that of LC designers during the opposing concept task.

Analysis of functional brain connections for positive-negative emotions using phase locking value

In this study, we investigate the brain networks during positive and negative emotions for different types of stimulus (audio only, video only and audio + video) in [Formula: see text], and [Formula: see text] bands in terms of phase locking value, a nonlinear method to study functional connectivity. Results show notable hemispheric lateralization as phase synchronization values between channels are significant and high in right hemisphere for all emotions. Left frontal electrodes are also found to have control over emotion in terms of functional connectivity. Besides significant inter-hemisphere phase locking values are observed between left and right frontal regions, specifically between left anterior frontal and right mid-frontal, inferior-frontal and anterior frontal regions; and also between left and right mid frontal regions. ANOVA analysis for stimulus types show that stimulus types are not separable for emotions having high valence. PLV values are significantly different only for negative emotions or neutral emotions between audio only/video only and audio only/audio + video stimuli. Finding no significant difference between video only and audio + video stimuli is interesting and might be interpreted as that video content is the most effective part of a stimulus.

Multiple characteristics analysis of Alzheimer's electroencephalogram by power spectral density and Lempel-Ziv complexity

To investigate the electroencephalograph (EEG) background activity in patients with Alzheimer's disease (AD), power spectrum density (PSD) and Lempel-Ziv (LZ) complexity analysis are proposed to extract multiple effective features of EEG signals from AD patients and further applied to distinguish AD patients from the normal controls. Spectral analysis based on autoregressive Burg method is first used to quantify the power distribution of EEG series in the frequency domain. Compared with the control group, the relative PSD of AD group is significantly higher in the theta frequency band while lower in the alpha frequency bands. In order to explore the nonlinear information, Lempel-Ziv complexity (LZC) and multi-scale LZC is further applied to all electrodes for the four frequency bands. Analysis results demonstrate that the group difference is significant in the alpha frequency band by LZC and multi-scale LZC analysis. However, the group difference of multi-scale LZC is much more remarkable, manifesting as more channels undergo notable changes, particularly in electrodes O1 and O2 in the occipital area. Moreover, the multi-scale LZC value provided a better classification between the two groups with an accuracy of 85.7 %. In addition, we combine both features of the relative PSD and multi-scale LZC to discriminate AD patients from the normal controls by applying a support vector machine model in the alpha frequency band. It is indicated that the two groups can be clearly classified by the combined feature. Importantly, the accuracy of the classification is higher than that of any one feature, reaching 91.4 %. The obtained results show that analysis of PSD and multi-scale LZC can be taken as a potential comprehensive measure to distinguish AD patients from the normal controls, which may benefit our understanding of the disease.

Towards a fourth spatial dimension of brain activity

Current advances in neurosciences deal with the functional architecture of the central nervous system, paving the way for general theories that improve our understanding of brain activity. From topology, a strong concept comes into play in understanding brain functions, namely, the 4D space of a "hypersphere's torus", undetectable by observers living in a 3D world. The torus may be compared with a video game with biplanes in aerial combat: when a biplane flies off one edge of gaming display, it does not crash but rather it comes back from the opposite edge of the screen. Our thoughts exhibit similar behaviour, i.e. the unique ability to connect past, present and future events in a single, coherent picture as if we were allowed to watch the three screens of past-present-future "glued" together in a mental kaleidoscope. Here we hypothesize that brain functions are embedded in a imperceptible fourth spatial dimension and propose a method to empirically assess its presence. Neuroimaging fMRI series can be evaluated, looking for the topological hallmark of the presence of a fourth dimension. Indeed, there is a typical feature which reveal the existence of a functional hypersphere: the simultaneous activation of areas opposite each other on the 3D cortical surface. Our suggestion-substantiated by recent findings-that brain activity takes place on a closed, donut-like trajectory helps to solve long-standing mysteries concerning our psychological activities, such as mind-wandering, memory retrieval, consciousness and dreaming state.

Hemispheric asymmetry non-linear analysis of EEG during emotional responses from idiopathic Parkinson's disease patients

Recent studies show right hemisphere has a unique contribution to emotion processing. The present study investigated EEG using non-linear measures during emotional processing in PD patients with respect to motor symptom asymmetry (i.e., most affected body side). We recorded 14-channel wireless EEGs from 20 PD patients and 10 healthy age-matched controls (HC) by eliciting emotions such as happiness, sadness, fear, anger, surprise and disgust. PD patients were divided into two groups, based on most affected body side and unilateral motor symptom severity: left side-affected (LPD, n = 10) or right side-affected PD patients (RPD, n = 10). Nonlinear analysis of these emotional EEGs were performed by using approximate entropy, correlation dimension, detrended fluctuation analysis, fractal dimension, higher order spectra, hurst exponent (HE), largest Lyapunov exponent and sample entropy. The extracted features were ranked using analysis of variance based on F value. The ranked features were then fed into classifiers namely fuzzy K-nearest neighbor and support vector machine to obtain optimal performance using minimum number of features. From the experimental results, we found that (a) classification performance across all frequency bands performed well in recognizing emotional states of LPD, RPD, and HC; (b) the emotion-specific features were mainly related to higher frequency bands; and (c) predominantly LPD patients (inferred right-hemisphere pathology) were more impaired in emotion processing compared to RPD, as showed by a poorer classification performance. The results suggest that asymmetric neuronal degeneration in PD patients may contribute to the impairment of emotional communication.

Localization of neural efficiency of the mathematically gifted brain through a feature subset selection method

Based on the neural efficiency hypothesis and task-induced EEG gamma-band response (GBR), this study investigated the brain regions where neural resource could be most efficiently recruited by the math-gifted adolescents in response to varying cognitive demands. In this experiment, various GBR-based mental states were generated with three factors (level of mathematical ability, task complexity, and short-term learning) modulating the level of neural activation. A feature subset selection method based on the sequential forward floating search algorithm was used to identify an "optimal" combination of EEG channel locations, where the corresponding GBR feature subset could obtain the highest accuracy in discriminating pairwise mental states influenced by each experiment factor. The integrative results from multi-factor selections suggest that the right-lateral fronto-parietal system is highly involved in neural efficiency of the math-gifted brain, primarily including the bilateral superior frontal, right inferior frontal, right-lateral central and right temporal regions. By means of the localization method based on single-trial classification of mental states, new GBR features and EEG channel-based brain regions related to mathematical giftedness were identified, which could be useful for the brain function improvement of children/adolescents in mathematical learning through brain-computer interface systems.

The electrocortical modulation effects of different emotion regulation strategies

The current event-related potential study investigated the modulation effects of different emotion regulation strategies on electrocortical responses. When watching negative or neutral pictures, participants were instructed to perform three tasks: cognitive reappraisal, expressive suppression and passive viewing. We found that negative pictures elicited a larger late positive potential (LPP) than neutral pictures. Moreover, processes involved in strategy also had an effect on LPP amplitude, which was indicated by a larger LPP in reappraisal compared with suppression and viewing tasks when neutral pictures were presented. After the influence of processes on LPP was excluded, results showed that reappraisal effectively decreased the emotion-enhanced LPP than suppression and viewing. The difference in regulatory effect may be determined by the underlying processing mechanism. A larger frontal-central component, N2, was observed in suppression than reappraisal and viewing, which suggested that it involved the processes focusing on behavioral response. While the larger LPP found in reappraisal implicated that it recruited cognitive processes focusing on the picture meaning.