Frontal EEG alpha asymmetry and emotion: From neural underpinnings and methodological considerations to psychopathology and social cognition

Mindfulness-Based Intervention Effects on EEG and Executive Functions: A Systematic Review

Background. Mindfulness-based interventions (MBIs) have emerged as an alternative intervention for symptoms of psychological and psychiatric conditions, such as depression, anxiety, and emotional discomfort. Over the last ten years, MBIs have established a growing body of evidence that shows cognitive and neurophysiological benefits. Depression and anxiety are conditions with a high prevalence in the world population. In developing countries, it is reported that, given the conditions of being at a social disadvantage, anxiety and depression are higher, resulting in compromised psychological well-being and mental health. Objectives. This systematic review aims to quantitatively and qualitatively assess changes in the neuropsychological, particularly executive functioning and social cognition domains, and electroencephalographical (EEG) effects of MBIs. Methods. A systematic review was conducted using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) in three databases, Web of Science, Scopus, and EBSCO MedLine complete; 14,464 articles were found, 141 articles evaluated the effects of MBI on executive functioning, and 16 included both as in qualitative and quantitative variables. Results. The qualitative results show that the research on the effects of MBI on behavior and cognitive skills, including executive function, social cognition, and EEG analysis, is very scarce but consistent in suggesting strong correlations on cognitive and electrophysiological alpha-beta proportions asymmetry on frontal areas. Undoubtedly, executive functions, as a behavioral regulatory and self-monitoring system, are the most popular study of interest in the literature, including emotional regulation, awareness, planning, social skills, and focused attention. Although there are fewer studies assessing the effects of MBIs on social cognition skills. The funnel plot showed a symmetrical distribution but ranked out of significant correlation. Most estimates of treatment effects are positive (58%); however, the average outcome observed did not significantly differ from zero. Conclusions. This study concludes that the research integrating the analysis of the electrophysiological and executive function effects of MBI shows important methodological variations and clinical conditions, which explains the significant results reported individually. Even when most of the literature reports positive effects of MBIs on several behavioral and neurophysiological domains, there are still confounding factors that must be taken into consideration by researchers and clinicians before attributing possible inaccurate or generalizable benefits.

Brain-computer-interface-driven artistic expression: real-time cognitive visualization in the pangolin scales animatronic dress and screen dress

This paper explores the intersection of brain-computer interfaces (BCIs) and artistic expression, showcasing two innovative projects that merge neuroscience with interactive wearable technology. BCIs, traditionally applied in clinical settings, have expanded into creative domains, enabling real-time monitoring and representation of cognitive states. The first project showcases a low-channel BCI Screen Dress, utilizing a 4-channel electroencephalography (EEG) headband to extract an engagement biomarker. The engagement is visualized through animated eyes on small screens embedded in a 3D-printed dress, which dynamically responds to the wearer's cognitive state. This system offers an accessible approach to cognitive visualization, leveraging real-time engagement estimation and demonstrating the effectiveness of low-channel BCIs in artistic applications. In contrast, the second project involves an ultra-high-density EEG (uHD EEG) system integrated into an animatronic dress inspired by pangolin scales. The uHD EEG system drives physical movements and lighting, visually and kinetically expressing different EEG frequency bands. Results show that both projects have successfully transformed brain signals into interactive, wearable art, offering a multisensory experience for both wearers and audiences. These projects highlight the vast potential of BCIs beyond traditional clinical applications, extending into fields such as entertainment, fashion, and education. These innovative wearable systems underscore the ability of BCIs to expand the boundaries of creative expression, turning the wearer's cognitive processes into art. The combination of neuroscience and fashion tech, from simplified EEG headsets to uHD EEG systems, demonstrates the scalability of BCI applications in artistic domains.

The Effect of Evaluating Self's Emotions on Frontal Alpha Asymmetry

PURPOSE

In research to assess emotions from biometric signals, participants are asked to evaluate the emotions they subjectively experienced to confirm whether the assumed emotions were actually elicited. However, the evaluation of emotion may influence the biometric signals related to the emotion itself. While such evaluative processes may function as a form of emotion regulation, which is known to modulate emotional experiences, the neural mechanisms and effects of evaluation itself remain unclear. Specifically, the temporal dynamics of how these evaluations affect emotion-related brain activity in electroencephalography (EEG) have not been investigated. Based on theories of emotional processing and self-focused attention, we hypothesized that emotion evaluations would enhance emotional processing as reflected in frontal alpha asymmetry (FAA) through both immediate attentional effects and sustained self-focused attention.

METHOD

We measured a 29-channel EEG in 40 healthy participants who were presented with unpleasant and highly arousing images. Participants were assigned to either an experimental group that performed the task with subjective evaluation followed by without subjective evaluation, or a control group that performed the task without subjective evaluation twice. This design allowed us to examine both immediate effects of evaluation and its lasting influence on subsequent emotional processing.

FINDING

The results revealed that FAA was significantly lower during emotional evaluation compared to conditions without subjective evaluation, particularly during stimulus processing (300-500 ms). This early modulation suggests that evaluation automatically engages attentional processes, may reflect enhanced negative emotional processing as well as the activation of behavioral inhibition system through self-focused attention.

CONCLUSION

This study demonstrates that the emotional evaluation procedure itself can significantly alter early emotion-related brain activity, providing insights into how self-focused emotional evaluation engages both emotional and motivational processes. These findings suggest the need for methodological reconsiderations in EEG emotion estimation studies.

Develop an emotion recognition system using jointly connectivity between electroencephalogram and electrocardiogram signals

This study pioneers an innovative approach to improve the accuracy and dependability of emotion recognition (ER) systems by integrating electroencephalogram (EEG) with electrocardiogram (ECG) data. We propose a novel method of estimating effective connectivity (EC) to capture the dynamic interplay between the heart and brain during emotions of happiness, disgust, fear, and sadness. Leveraging three EC estimation techniques (Granger causality (GC), partial directed coherence (PDC) and directed transfer function (DTF)), we feed the resulting EC representations as inputs into convolutional neural networks (CNNs), namely ResNet-18 and MobileNetV2, known for their swift and superior performance. To evaluate this approach, we have used EEG and ECG data from the public MAHNOB-HCI database through 5-fold cross-validation criterion. Remarkably, our approach achieves an average accuracy of 97.34 ± 1.19 and 96.53 ± 3.54 for DTF images within the alpha frequency band using ResNet-18 and MobileNetV2, respectively. Comparative analyses in comparison to cutting-edge research unequivocally prove the efficacy of augmenting ECG with EEG, showcasing substantial improvements in ER performance across the spectrum of emotions studied.

EEG Signal Processing Techniques and Applications-2nd Edition

Electroencephalography (EEG), as a well-established, non-invasive tool, has been successfully applied to a wide range of conditions due to its many evident advantages, such as economy, portability, easy operation, easy accessibility, and widespread availability in hospitals [...].

Music therapy improves engagement and initiation for autistic children with mild intellectual disabilities: A randomized controlled study

This study aimed to evaluate the effectiveness of music therapy (MT) for children with co-occurring autism spectrum disorder (ASD) and intellectual disabilities (ID) and explore whether pre-intervention quantitative electroencephalogram (qEEG) responses can predict outcomes. A randomized controlled trial was conducted with 33 children receiving MT and 34 receiving an active control therapy. Participants received either MT or a non-musical social skills intervention for 45 min weekly over 12 weeks. Primary outcomes were measured using the Childhood Autism Rating Scale (CARS-2), along with the parent-rated Social Responsiveness Scale (SRS-2) and video coding of social behaviors. Both conditions significantly improved in CARS-2 scores at 2 weeks and 4 months post-intervention, with no differences between MT and control conditions. No changes were found in SRS-2 scores. While both conditions showed reduced disengagement after intervention, only the MT condition showed increased engagement and initiation. Strong qEEG responses to social scenes and music predicted increased initiation, indicating its potential to help tailor interventions. These results support incorporating MT into standard services and further research on qEEG predictors.

Frontal alpha asymmetry dynamics: A window into active self-regulatory processes

Frontal Alpha Asymmetry (FAA) has been studied since the late 1970s as a neural correlate of emotion regulation and motivational processes. FAA is often viewed through a dispositional lens reflecting individual differences in positive or negative emotionality and biases toward approach or avoidance motivational processes. However, FAA also shifts in response to context-specific conditions that elicit approach or avoidance responses, indicating FAA reflects active, ongoing self-regulatory processes. Moreover, FAA changes over time, and how it changes over time is affected by context, experience, and development. We propose FAA evolves over four different time scales including the (1) second-to-second, (2) laboratory task, (3) intervention or intensive learning experience, and (4) developmental time scales. We present evidence showing FAA evolves over each of these time scales and highlight influences of individual differences and the developmental context on how FAA changes over time. We emphasize the insights gained by studying change in FAA over each time scale. We concluded with recommendations about future directions and speculate about the nested, bidirectional nature of the four timescales.

Neurophysiological approaches to exploring emotional responses to cosmetics: a systematic review of the literature

Introduction

This systematic review explores the use of neurophysiological measurements to study emotional responses to cosmetic products. The aim is to evaluate existing literature on these measurements in cosmetics, identify the main findings, highlight methodological challenges, and propose new guidelines for future research.

Method

A systematic search focusing on neurophysiological measures to determine emotions induced by different cosmetic products was carried out in accordance with PRISMA guidelines.

Results

A total of 33 articles identified with the EBSCO database met the inclusion criteria. In all, 10 different measurement tools were used in these articles to assess the emotional effects of cosmetic products.

Discussion

This review emphasizes the complexity of interactions between cosmetics and emotional responses. It underscores the importance of future research with a more holistic approach that couples several physiological measurements. Among them, electrophysiological brain activity shows potential for enhancing understanding of emotional responses related to cosmetic products. Frontal asymmetry, particularly in the alpha frequency band, was often use and frequently linked to positive emotional states, although conflicting evidence exists. Additionally, cardiac activity, specifically the LF/HF ratio, emerges as a promising marker for differentiating between different cosmetic products. However, methodological heterogeneity, present challenges for replicability, generalizability, and complicate data interpretation.

HASTF: a hybrid attention spatio-temporal feature fusion network for EEG emotion recognition

Introduction

EEG-based emotion recognition has gradually become a new research direction, known as affective Brain-Computer Interface (aBCI), which has huge application potential in human-computer interaction and neuroscience. However, how to extract spatio-temporal fusion features from complex EEG signals and build learning method with high recognition accuracy and strong interpretability is still challenging.

Methods

In this paper, we propose a hybrid attention spatio-temporal feature fusion network for EEG-based emotion recognition. First, we designed a spatial attention feature extractor capable of merging shallow and deep features to extract spatial information and adaptively select crucial features under different emotional states. Then, the temporal feature extractor based on the multi-head attention mechanism is integrated to perform spatio-temporal feature fusion to achieve emotion recognition. Finally, we visualize the extracted spatial attention features using feature maps, further analyzing key channels corresponding to different emotions and subjects.

Results

Our method outperforms the current state-of-the-art methods on two public datasets, SEED and DEAP. The recognition accuracy are 99.12% ± 1.25% (SEED), 98.93% ± 1.45% (DEAP-arousal), and 98.57% ± 2.60% (DEAP-valence). We also conduct ablation experiments, using statistical methods to analyze the impact of each module on the final result. The spatial attention features reveal that emotion-related neural patterns indeed exist, which is consistent with conclusions in the field of neurology.

Discussion

The experimental results show that our method can effectively extract and fuse spatial and temporal information. It has excellent recognition performance, and also possesses strong robustness, performing stably across different datasets and experimental environments for emotion recognition.

The association between social rewards and anxiety: Links from neurophysiological analysis in virtual reality and social interaction game

Individuals' affective experience can be intricate, influenced by various factors including monetary rewards and social factors during social interaction. However, within this array of factors, divergent evidence has been considered as potential contributors to social anxiety. To gain a better understanding of the specific factors associated with anxiety during social interaction, we combined a social interaction task with neurophysiological recordings obtained through an anxiety-elicitation task conducted in a Virtual Reality (VR) environment. Employing inter-subject representational similarity analysis (ISRSA), we explored the potential linkage between individuals' anxiety neural patterns and their affective experiences during social interaction. Our findings suggest that, after controlling for other factors, the influence of the partner's emotional cues on individuals' affective experiences is specifically linked to their neural pattern of anxiety. This indicates that the emergence of anxiety during social interaction may be particularly associated with the emotional cues provided by the social partner, rather than individuals' own reward or prediction errors during social interaction. These results provide further support for the cognitive theory of social anxiety and extend the application of VR in future cognitive and affective studies.

Greater weekly physical activity linked to left resting frontal alpha asymmetry in women: A study on gender differences in highly active young adults

Physical activity, beneficial for physical and psychological health, may facilitate affective mechanisms of positive emotion and approach-motivation. Greater resting frontal alpha asymmetry (FAA), an index of greater relative left than right frontal cortical activity, is a neural correlate of affective mechanisms possibly associated with active lifestyles. This study sought to amplify limited literature on the relationship between physical (in)activity, FAA, and gender differences. College students (n = 70) self-reported physical activity (Total PA) and sedentary activity (Total Sitting) via the International Physical Activity Questionnaire-Short Form (IPAQ-SF), followed by a resting electroencephalography session to record FAA. A Total PA × gender interaction (β = 0.462, t = 3.163, p = 0.002) identified a positive relationship between Total PA and FAA in women (β = 0.434, t = 2.221, p = 0.030) and a negative relationship for men (β = -0.338, t = -2.300, p = 0.025). Total Sitting was positively linked to FAA (β = 0.288, t = 2.228, p = 0.029; no gender effect). Results suggest affective mechanisms reflected by FAA (e.g., positive emotion, approach-motivation) are associated with physical activity for women, indicating a possible mechanism of the psychological benefits linked with physically active lifestyles. A positive relationship between sedentary behavior and greater left FAA may also reflect motivated mechanisms of behavior that aid in minimizing energy expenditure, particularly within the context of our highly active sample.

How Did We Get So Bored? A Bioecological Model of the Development of Boredom

Boredom is a negative emotion that most people experience on occasion. However, boredom is also present on a trait level. People high in trait boredom experience boredom more frequently or have difficulty tolerating it. Individuals high in trait boredom are more likely to experience depression or anxiety or engage in risk behaviors. Little is known about the development of trait boredom. We propose a bioecological model of the development of trait boredom in which it originates from early individual differences in temperament and executive control. Trait boredom is shaped over time through interactions between the child and their developmental context, such as parents, teachers, and neighborhoods. Boredom can also spur creativity. Capitalizing on the creative side of boredom may help promote low levels of trait boredom and healthy coping. We provide a roadmap to study the development of trait boredom to advance our understanding of how it emerges and develops.

A historical approach to models of emotional laterality

In this paper I discuss the main models that have tried to explain brain asymmetries for emotions. The first models, based on clinical observations, proposed either a general right hemisphere dominance for emotions (the'right hemisphere') model or a different specialization of the right hemisphere for negative and of the left hemisphere for positive emotions (the'valence' model). In more recent times new models, based on partly modified versions of the previous ones have been proposed. The revised version of the 'valence' model, labeled the 'approach-avoidance' model maintained that hemispheric asymmetries are not related to the valence of the emotional stimulus but to the motivational (approach vs avoidance) system that is engaged by that stimulus. On the contrary, revised versions of the 'right hemisphere' hypothesis proposed graded versions of this model, maintaining that only some kinds or some levels of emotions are clearly right lateralized. One version of these models (the'emotion type hypothesis') assumed that only elementary basic emotions should be subsumed by the right hemisphere, wheres more complex social emotions should be subtended by the left hemisphere. The other version (the 'schematic level of emotion hypothesis') assumed that the right hemisphere should subsume only the basic 'schematic' level of emotions, characterized by an automatic and unconscious processing, whereas the more propositional and conscious 'conceptual' level could be less lateralized or subsumed by the left hemisphere. This last model is supported by the obsevation that the right hemisphere reveals a modus operandi (i.e. a prevalence of the 'automatic' over the 'intentional' and of the 'unconscious' over the 'conscious' functional processing) that is typical of the 'schematic level of emotions.

LGGNet: Learning From Local-Global-Graph Representations for Brain-Computer Interface

Neuropsychological studies suggest that co-operative activities among different brain functional areas drive high-level cognitive processes. To learn the brain activities within and among different functional areas of the brain, we propose local-global-graph network (LGGNet), a novel neurologically inspired graph neural network (GNN), to learn local-global-graph (LGG) representations of electroencephalography (EEG) for brain-computer interface (BCI). The input layer of LGGNet comprises a series of temporal convolutions with multiscale 1-D convolutional kernels and kernel-level attentive fusion. It captures temporal dynamics of EEG which then serves as input to the proposed local- and global-graph-filtering layers. Using a defined neurophysiologically meaningful set of local and global graphs, LGGNet models the complex relations within and among functional areas of the brain. Under the robust nested cross-validation settings, the proposed method is evaluated on three publicly available datasets for four types of cognitive classification tasks, namely the attention, fatigue, emotion, and preference classification tasks. LGGNet is compared with state-of-the-art (SOTA) methods, such as DeepConvNet, EEGNet, R2G-STNN, TSception, regularized graph neural network (RGNN), attention-based multiscale convolutional neural network-dynamical graph convolutional network (AMCNN-DGCN), hierarchical recurrent neural network (HRNN), and GraphNet. The results show that LGGNet outperforms these methods, and the improvements are statistically significant ( ) in most cases. The results show that bringing neuroscience prior knowledge into neural network design yields an improvement of classification performance. The source code can be found at https://github.com/yi-ding-cs/LGG.

How Society Anxiety Influences Attention Control in College Students: The Moderated Mediation Effect of Cognitive Flexibility and Resting-state Electroencephalography Activity

Social anxiety is a prevalent issue among college students, adversely affecting their overall well-being. Drawing from the cognitive model of social anxiety and attention control theory, heightened levels of social anxiety may correspond to poorer attention control ability. However, little is known about the underlying cognitive mechanisms of the relationship between social anxiety and attention control. To address this research gap, the current study recruited a sample of 156 college students (56 women) who underwent self-report measures of social anxiety, cognitive flexibility, and attention control, followed by a resting-state EEG recording. The results revealed a significant negative predictive effect of social anxiety on attention control, with cognitive flexibility partially mediating this relationship. Furthermore, resting-state theta power emerged as a significant moderator, accentuating the negative impact of social anxiety on cognitive flexibility among individuals with lower theta power. In addition, frontal alpha asymmetry (FAA) demonstrated a moderating effect, with lower FAA intensifying the predictive influence of cognitive flexibility on attention control. Taken together, these results suggested that social anxiety can predict attention control either directly or indirectly via the mediating role of cognitive flexibility, and lower theta power and FAA has a risk amplification effect, which provide novel insights into the treatment and prevention of social anxiety and its negative impact on college students.

Electroencephalography findings in menstrually-related mood disorders: A critical review

The female reproductive years are characterized by fluctuations in ovarian hormones across the menstrual cycle, which have the potential to modulate neurophysiological and behavioral dynamics. Menstrually-related mood disorders (MRMDs) comprise cognitive-affective or somatic symptoms that are thought to be triggered by the rapid fluctuations in ovarian hormones in the luteal phase of the menstrual cycle. MRMDs include premenstrual syndrome (PMS), premenstrual dysphoric disorder (PMDD), and premenstrual exacerbation (PME) of other psychiatric disorders. Electroencephalography (EEG) non-invasively records in vivo synchronous activity from populations of neurons with high temporal resolution. The present overview sought to systematically review the current state of task-related and resting-state EEG investigations on MRMDs. Preliminary evidence indicates lower alpha asymmetry at rest being associated with MRMDs, while one study points to the effect being luteal-phase specific. Moreover, higher luteal spontaneous frontal brain activity (slow/fast wave ratio as measured by the delta/beta power ratio) has been observed in persons with MRMDs, while sleep architecture results point to potential circadian rhythm disturbances. In this review, we discuss the quality of study designs as well as future perspectives and challenges of supplementing the diagnostic and scientific toolbox for MRMDs with EEG.

Intra- and inter-brain coupling and activity dynamics during improvisational music therapy with a person with dementia: an explorative EEG-hyperscanning single case study

Objective

Real-life research into the underlying neural dynamics of improvisational music therapy, used with various clinical populations, is largely lacking. This single case study explored within-session differences in musical features and in within- and between-brain coupling between a Person with Dementia (PwD) and a music therapist during a music therapy session.

Methods

Dual-EEG from a music therapist and a PwD (male, 31 years) was recorded. Note density, pulse clarity and synchronicity were extracted from audio-visual data. Three music therapists identified moments of interest and no interest (MOI/MONI) in two drum improvisations. The Integrative Coupling Index, reflecting time-lagged neural synchronization, and musical features were compared between the MOI and MONI.

Results

Between-brain coupling of 2 Hz activity was increased during the MOI, showing anteriority of the therapist's neural activity. Within-brain coupling for the PwD was stronger from frontal and central areas during the MOI, but within-brain coupling for the therapist was stronger during MONI. Differences in musical features indicated that both acted musically more similar to one another during the MOI.

Conclusion

Within-session differences in neural synchronization and musical features highlight the dynamic nature of music therapy.

Significance

The findings contribute to a better understanding of social and affective processes in the brain and (interactive) musical behaviors during specific moments in a real-life music therapy session. This may provide insights into the role of such moments for relational-therapeutic processes.

The Link between Suicidality and Electroencephalography Asymmetry: A Systematic Review and Meta-analysis

As one of the leading causes of death globally, suicide has been researched extensively to better understand factors that confer risk or resilience for suicidality. Promising areas of the literature have focused on brain-based factors that might indicate susceptibility to suicide. Some studies have investigated the link between electroencephalography (EEG) asymmetry, referring to differences in electrical activity in the brain from the left to right hemisphere, and suicidality. The present study is a comprehensive review and meta-analysis of the literature to see if certain patterns in EEG asymmetry serve as a diathesis for suicidal thoughts and behaviors. The results of the current investigation found that EEG asymmetry was not systematically related to suicide based on the literature reviewed. While the present review does not rule out all brain-based factors, the findings suggest that EEG asymmetry may not be a biomarker for suicidality.

From Coaching to Neurocoaching: A Neuroscientific Approach during a Coaching Session to Assess the Relational Dynamics between Coach and Coachee-A Pilot Study

Life transitions represent moments characterized by changes that can profoundly influence individual life trajectories and subjective well-being. Recently, career coaching has become an important method of helping people expand their self-awareness, facilitate personal development, and increase their performance in the school-to-work transition. Although previous studies have confirmed that one of the most important keys to the success of a coaching program is the quality of the relationship between coach and coachee, there is a lack of knowledge regarding how to objectively measure it. In this pilot study, we adopted a neuroscientific approach to introduce objective measures of the relationship between coach and coachee through the phases of a coaching session. A sample of 14 university students and a professional coach participated in career-coaching sessions while their affective states were measured by recording brain (EEG) and physiological (Skin conductance) activity. Electroencephalographic indicators of valence, arousal, and engagement showed differences between session phases, highlighting the possibility of a neurophysiological measurement of relational dynamics. Our results provide initial evidence that neurophysiological activity can be considered a way to understand differences in the coach-coachee relationship, thereby providing information on the effectiveness of coaching interventions and facilitating a better life transition from school to work.

MTDN: Learning Multiple Temporal Dynamics Representation for Emotional Valence Classification with EEG

Emotion recognition from electroencephalogram (EEG) requires computational models to capture the crucial features of the emotional response to external stimulation. Spatial, spectral, and temporal information are relevant features for emotion recognition. However, learning temporal dynamics is a challenging task, and there is a lack of efficient approaches to capture such information. In this work, we present a deep learning framework called MTDN that is designed to capture spectral features with a filterbank module and to learn spatial features with a spatial convolution block. Multiple temporal dynamics are jointly learned with parallel long short-term memory (LSTM) embedding and self-attention modules. The LSTM module is used to embed the time segments, and then the self-attention is utilized to learn the temporal dynamics by intercorrelating every embedded time segment. Multiple temporal dynamics representations are then aggregated to form the final extracted features for classification. We experiment on a publicly available dataset, DEAP, to evaluate the performance of our proposed framework and compare MTDN with existing published results. The results demonstrate improvement over the current state-of-the-art methods on the valence dimension of the DEAP dataset.

Older and Wiser? Age-related Change in State and Trait Boredom During Adolescence and Associations with Neural Correlates of Self-regulation

Purpose

The purpose of the current study was to examine age-related change in state and trait boredom in 12- to 17-year-old adolescents and test whether neurophysiological correlates of self-regulation relate to boredom during adolescence in the same way that has been found in adults.

Methods

Eighty-nine 12- to 17-year-old adolescents participated. Three types of trait boredom were measured: boredom proneness, leisure boredom, and boredom susceptibility. State boredom was also measured after completing a boredom induction task while EEG was recorded. Slopes in frontal alpha asymmetry (FAA) were extracted from the EEG as a measure of approach (leftward shifts) or avoidance (rightward shifts).

Results

A curvilinear relationship between age and boredom proneness and age and boredom susceptibility was observed, indicating trait boredom rises and falls across adolescence. State boredom, by contrast, increased linearly with age. Slopes in FAA inversely related only to boredom proneness, indicating higher levels of this type of trait boredom related to an avoidant response as a state of boredom ensues.

Conclusion

We suggest the rise and fall of trait boredom across adolescence may be due to changes in person-environment fit during middle adolescence, whereas state boredom may increase with age due to improvements in attentional processes that mundane lab tasks do not satisfactorily engage. The link between FAA and only one type of trait boredom indicates self-regulatory processes and boredom are not yet strongly coupled in adolescence. Implications for prevention of negative behavioral health outcomes associated with high levels of trait boredom are discussed.

Resting-state frontal, frontlateral, and parietal alpha asymmetry:A pilot study examining relations with depressive disorder type and severity

Introduction

The search for biomarkers has been central to efforts of improving clinical diagnosis and prognosis in psychopathology in the last decades. The main approach has been to validate biomarkers that could accurately discriminate between clinical diagnoses of very prevalent forms of psychopathology. One of the most popular electrophysiological markers proposed for discrimination in depressive disorders is the electroencephalography (EEG)-derived frontal alpha asymmetry. However, the validity, reliability and predictive value of this biomarker have been questioned in recent years, mainly due to conceptual and methodological heterogeneity.

Methods

In the current non-experimental, correlational study we investigated relationship of resting-state EEG alpha asymmetry from multiple sites (frontal, frontolateral, and parietal) with different forms of depressive disorders (varying in type or severity), in a clinical sample.

Results

Results showed that alpha asymmetry in the parietal (P3-P4) was significantly higher than in the frontal (F3-F4) and frontolateral sites (F7-F8). However, we did not find significant relations between alpha asymmetry indices and our depressive disorder measures, except for a moderate positive association between frontolateral alpha asymmetry (eyes-closed only) and depressive disorder severity (determined through clinical structured interview). We also found no significant differences in alpha asymmetry between participants, depending on their depression type.

Discussion

Based on results, we propose the parietal and frontolateral asymmetry indices to form hypotheses that should not be abandoned in the depression markers research, but worth for further experimental research. Methodological and clinical implications of the current findings are discussed.

Heart and brain traumatic stress biomarker analysis with and without machine learning: A scoping review

The enigma of post-traumatic stress disorder (PTSD) is embedded in a complex array of physiological responses to stressful situations that result in disruptions in arousal and cognitions that characterise the psychological disorder. Deciphering these physiological patterns is complex, which has seen the use of machine learning (ML) grow in popularity. However, it is unclear to what extent ML has been used with physiological data, specifically, the electroencephalogram (EEG) and electrocardiogram (ECG) to further understand the physiological responses associated with PTSD. To better understand the use of EEG and ECG biomarkers, with and without ML, a scoping review was undertaken. A total of 124 papers based on adult samples were identified comprising 19 ML studies involving EEG and ECG. A further 21 studies using EEG data, and 84 studies employing ECG meeting all other criteria but not employing ML were included for comparison. Identified studies indicate classical ML methodologies currently dominate EEG and ECG biomarkers research, with derived biomarkers holding clinically relevant diagnostic implications for PTSD. Discussion of the emerging trends, algorithms used and their success is provided, along with areas for future research.

Links between social avoidance and frontal alpha asymmetry during processing emotional facial stimuli: An exploratory study

Individuals who are socially avoidant actively remove themselves from opportunities for social interaction and have a strong desire for solitude. Although social avoidance is associated with a host of adjustment difficulties, its neural substrates remain under-explored. To address this gap, we conducted an exploratory study to compare electroencephalography (EEG) frontal alpha asymmetry (FAA) scores during processing emotional facial stimuli in socially avoidant and non-withdrawn comparison individuals. From an original sample of N = 384 undergraduate students, 25 avoidant and 27 comparison individuals were identified. For this subset of participants, EEG modulations and self-reported experience ratings during a picture processing task were assessed. Among the results, the socially avoidant group's ratings of positive stimuli were significantly lower than the non-withdrawn comparison group. The socially avoidant group also had significantly lower FAA scores in response to positive stimuli than the comparison group. Further, asymmetry scores of the comparison group in the positive conditions were higher than in the negative and neutral conditions. However, there were no significant differences between these three conditions in the socially avoidant group. Our results suggest that socially avoidant individuals may eschew interpersonal relationships because of a relatively greater right hemisphere cortical activity, which may contribute to a withdrawal motivation when confronted with negative emotional stimuli in social contexts.

Predicting individual differences in behavioral activation and behavioral inhibition from functional networks in the resting EEG

The behavioral activation system (BAS) and behavioral inhibition system (BIS) are thought to underly affective dispositions and self-regulatory processes. The BAS is sensitive to reward and involved in approach behaviors, and the BIS is sensitive to punishment and involved in avoidance behaviors. Trait BAS and BIS relate to distinct behavioral profiles and neural activity, but little is known about how trait BAS and BIS relate to functional networks in EEG. We applied a data-driven method called connectome predictive modeling (CPM) to identify networks relating to trait BAS and BIS and tested whether the strength of those networks predicted trait BAS and BIS in novel subjects using a leave-one-out cross-validation procedure. Adult participants (N = 107) completed a resting state task with eyes closed and eyes open, and trait BAS and BIS were measured via Carver and White's (1994) BIS and BAS scales. We hypothesized distinct positive (more synchronization) and negative (less synchronization) networks would relate to trait BAS and BIS. For eyes closed, we identified two negative networks, one in theta and one in alpha predicted BIS. We identified three positive networks, one in theta and one in beta predicted Fun Seeking and one in theta predicted Drive. For eyes open, negative theta and alpha networks predicted BIS, a positive theta network predicted Fun Seeking, and a negative gamma network predicted mean BAS. Visualization of the networks are presented. Discussion centers on the observed networks and how to advance application of CPM to EEG, including with clinical implications.

Facial thermal and blood perfusion patterns of human emotions: Proof-of-Concept

In this work, a preliminary study of proof-of-concept was conducted to evaluate the performance of the thermographic and blood perfusion data when emotions of positive and negative valence are applied, where the blood perfusion data are obtained from the thermographic data. The images were obtained for baseline, positive, and negative valence according to the protocol of the Geneva Affective Picture Database. Absolute and percentage differences of average values of the data between the valences and the baseline were calculated for different regions of interest (forehead, periorbital eyes, cheeks, nose and upper lips). For negative valence, a decrease in temperature and blood perfusion was observed in the regions of interest, and the effect was greater on the left side than on the right side. In positive valence, the temperature and blood perfusion increased in some cases, showing a complex pattern. The temperature and perfusion of the nose was reduced for both valences, which is indicative of the arousal dimension. The blood perfusion images were found to be greater contrast; the percentage differences in the blood perfusion images are greater than those obtained in thermographic images. Moreover, the blood perfusion images, and vasomotor answer are consistent, therefore, they can be a better biomarker than thermographic analysis in identifying emotions.

Probing fMRI brain connectivity and activity changes during emotion regulation by EEG neurofeedback

Despite the existence of several emotion regulation studies using neurofeedback, interactions among a small number of regions were evaluated, and therefore, further investigation is needed to understand the interactions of the brain regions involved in emotion regulation. We implemented electroencephalography (EEG) neurofeedback with simultaneous functional magnetic resonance imaging (fMRI) using a modified happiness-inducing task through autobiographical memories to upregulate positive emotion. Then, an explorative analysis of whole brain regions was done to understand the effect of neurofeedback on brain activity and the interaction of whole brain regions involved in emotion regulation. The participants in the control and experimental groups were asked to do emotion regulation while viewing positive images of autobiographical memories and getting sham or real (based on alpha asymmetry) EEG neurofeedback, respectively. The proposed multimodal approach quantified the effects of EEG neurofeedback in changing EEG alpha power, fMRI blood oxygenation level-dependent (BOLD) activity of prefrontal, occipital, parietal, and limbic regions (up to 1.9% increase), and functional connectivity in/between prefrontal, parietal, limbic system, and insula in the experimental group. New connectivity links were identified by comparing the brain functional connectivity between experimental conditions (Upregulation and View blocks) and also by comparing the brain connectivity of the experimental and control groups. Psychometric assessments confirmed significant changes in positive and negative mood states in the experimental group by neurofeedback. Based on the exploratory analysis of activity and connectivity among all brain regions involved in emotion regions, we found significant BOLD and functional connectivity increases due to EEG neurofeedback in the experimental group, but no learning effect was observed in the control group. The results reveal several new connections among brain regions as a result of EEG neurofeedback which can be justified according to emotion regulation models and the role of those regions in emotion regulation and recalling positive autobiographical memories.

Hemispheric Utilization of Alpha Oscillatory Dynamics as a Unique Biomarker of Neural Compensation in Females with Fragile X Syndrome

Fragile X syndrome (FXS) is a neurodevelopmental disorder caused by a trinucleotide expansion on the FMR1 gene and characterized by intellectual disability, sensory hypersensitivity, executive function difficulties, and social anxiety. Recently, efforts to define neural biomarkers for FXS have highlighted disruptions to power in the alpha frequency band; however the dynamic mechanisms supporting these findings are poorly understood. The current study aimed to explore the temporal and hemispheric dynamics supporting alpha phenotypes in FXS and their relationship with neural phenotypes related to auditory processing using electroencephalography during an auditory evoked task. Adolescents and adults (N = 36) with FXS and age/sex matched typically developing controls (N = 40) completed an auditory chirp task. Frontal alpha power in the prestimulus period was decomposed into "bursts" using percentile thresholding, then assessed for number of bursts per second (burst count) and burst length. Data were compared across left and right hemispheres to assess lateralization of neural activity. Individuals with FXS showed more differences in alpha power compared to TDC primarily in the right hemisphere. Notably, alpha hemisphere outcomes in males with FXS were driven by the number of times they entered a dynamically relevant period of alpha (burst count) rather than length of time spent in alpha. Females with FXS showed reduced burst counts but remained in sustained high alpha states for longer periods of time. Length of time spent in alpha may reflect a modulatory or compensatory mechanism capable of recovering sensory processing abilities in females with FXS resulting in a less severe clinical presentation. Right hemisphere abnormalities may impact sensory processing differences between males and females with FXS. The relationship between alpha burst length, count, sex, and hemisphere may shed light on underlying mechanisms for previously observed alpha power abnormalities in FXS and their variation by sex.

Emotion recognition using effective connectivity and pre-trained convolutional neural networks in EEG signals

Convolutional Neural Networks (CNN) have recently made considerable advances in the field of biomedical signal processing. These methodologies can assist in emotion recognition for affective brain computer interface. In this paper, a novel emotion recognition system based on the effective connectivity and the fine-tuned CNNs from multichannel Electroencephalogram (EEG) signal is presented. After preprocessing EEG signals, the relationships among 32 channels of EEG in the form of effective brain connectivity analysis which represents information flow between regions are computed by direct Directed Transfer Function (dDTF) method which yields a 32*32 image. Then, these constructed images from EEG signals for each subject were fed as input to four versions of pre-trained CNN models, AlexNet, ResNet-50, Inception-v3 and VGG-19 and the parameters of these models are fine-tuned, independently. The proposed deep learning architectures automatically learn patterns in the constructed image of the EEG signals in frequency bands. The efficiency of the proposed approach is evaluated on MAHNOB-HCI and DEAP databases. The experiments for classifying five emotional states show that the ResNet-50 applied on dDTF images in alpha band achieves best results due to specific architecture which captures the brain connectivity, efficiently. The accuracy and F1-score values for MAHNOB-HCI were obtained 99.41, 99.42 and for DEAP databases, 98.17, and 98.23. Newly proposed model is capable of effectively analyzing the brain function using information flow from multichannel EEG signals using effective connectivity measure of dDTF and ResNet-50.

Hemispheric asymmetries for emotions in non-human primates: A systematic review

A systematic review of investigations evaluating hemispheric asymmetries for emotions in primates was undertaken to individuate the most consistent lines of research allowing to check the hypothesis of a continuum in emotional lateralization across vertebrates. We reviewed studies on the lateralization of emotional expression (N = 31) and perception (N = 32) and of markers of emotional activation (N = 9), trying to distinguish those which had given respectively more consistent or more conflicting outcomes. Furthermore, we tried to identify the most strongly supported model of emotional lateralization. The most consistent results were obtained in studies investigating asymmetries in emotional expression at the facial level and in the perception of emotional facial expressions, whereas the most disappointing data were obtained in investigations evaluating possible neurophysiological markers of lateralized emotional activation. These results supported more the hypothesis of a continuity between humans and non-human primates than the more general hypothesis of a continuum between humans and all vertebrates. Furthermore, results supported more the 'right hemisphere' than the 'valence' model of emotional lateralization.

Exposure to Depression Memes on Social Media Increases Depressive Mood and It Is Moderated by Self-Regulation: Evidence From Self-Report and Resting EEG Assessments

This study aimed to investigate the effects of depression memes, spread mainly on social media, on depressive mood, and the moderating role of self-regulation based on self-report and electrophysiological (resting EEG frontal alpha asymmetry) assessments. We conducted a semi-online crossover study; first, we collected brain activity data from healthy young adults (n = 32) who were subsequently provided a link to the online experiment. Each participant participated in both the neutral and meme conditions. We also evaluated their level of depressive mood immediately before and after exposure to the stimuli. We further conducted a series of linear mixed effects model analyses and found that depression memes contributed to an increase in depressive symptoms. Specifically, lack of emotional clarity, difficulties in goal-directed behaviors in emotional distress, and impulse control difficulties were linked to greater depressive mood in the case of exposure to depression memes compared with neutral images. However, time interactions were insignificant. These results mainly indicate the centrality of behavioral problems during times of emotional distress caused by depression memes. Lastly, although frontal alpha asymmetry did not predict a change in depressive mood or significantly differ across conditions, lower inhibitory control may result in increased processing of depression memes as negative stimuli. This result is consistent with our self-report results (e.g., impulsivity) as well as other related studies in the literature. However, further research is needed to verify these frontal alpha asymmetry results.

Brains in Sync: Practical Guideline for Parent-Infant EEG During Natural Interaction

Parent-infant EEG is a novel hyperscanning paradigm to measure social interaction simultaneously in the brains of parents and infants. The number of studies using parent-infant dual-EEG as a theoretical framework to measure brain-to-brain synchrony during interaction is rapidly growing, while the methodology for measuring synchrony is not yet uniform. While adult dual-EEG methodology is quickly improving, open databases, tutorials, and methodological validations for dual-EEG with infants are largely missing. In this practical guide, we provide a step-by-step manual on how to implement and run parent-infant EEG paradigms in a neurodevelopmental laboratory in naturalistic settings (e.g., free interactions). Next, we highlight insights on the variety of choices that can be made during (pre)processing dual-EEG data, including recommendations on interpersonal neural coupling metrics and interpretations of the results. Moreover, we provide an exemplar dataset of two mother-infant dyads during free interactions ("free play") that may serve as practice material. Instead of providing a critical note, we would like to move the field of parent-infant EEG forward and be transparent about the challenges that come along with the exciting opportunity to study the development of our social brain within the naturalistic context of dual-EEG.

EEG Hyperscanning and Qualitative Analysis of Moments of Interest in Music Therapy for Stroke Rehabilitation—A Feasibility Study

Interdisciplinary research into the underlying neural processes of music therapy (MT) and subjective experiences of patients and therapists are largely lacking. The aim of the current study was to assess the feasibility of newly developed procedures (including electroencephalography/electrocardiography hyperscanning, synchronous audio–video monitoring, and qualitative interviews) to study the personal experiences and neuronal dynamics of moments of interest during MT with stroke survivors. The feasibility of our mobile setup and procedures as well as their clinical implementation in a rehabilitation centre and an acute hospital ward were tested with four phase C patients. Protocols and interviews were used for the documentation and analysis of the feasibility. Recruiting patients for MT sessions was feasible, although data collection on three consecutive weeks was not always possible due to organisational constraints, especially in the hospital with acute ward routines. Research procedures were successfully implemented, and according to interviews, none of the patients reported any burden, tiredness, or increased stress due to the research procedures, which lasted approx. 3 h (ranging from 135 min to 209 min) for each patient. Implementing the research procedures in a rehabilitation unit with stroke patients was feasible, and only small adaptations were made for further research.

Investigate the Neuro Mechanisms of Stereoscopic Visual Fatigue

Stereoscopic visual fatigue (SVF) due to prolonged immersion in the virtual environment can lead to negative user experience, thus hindering the development of virtual reality (VR) industry. Previous studies have focused on investigating the evaluation indicators associated with SVF, while few studies have been conducted to reveal the underlying neural mechanism, especially in VR applications. In this paper, a modified Go/NoGo paradigm was adopted to induce SVF in VR environment with Go trials for maintaining participants' attention to experimental viewing tasks and NoGo trials for investigating the neural effects under SVF. Random dot stereograms (RDSs) with 11 disparities and 2 types of shapes (arrow and rectangle) were presented to evoke the depth-related visual evoked potentials (DVEPs) during 64-channel EEG recordings. EEG datasets collected from 15 participants in NoGo trials were selected to conduct individual processing and group analysis, in which the characteristics of the DVEPs components for various fatigue degrees were compared with one-way repeated-measurement ANOVA and independent components were clustered to explore the original cortex areas related to SVF. Point-by-point permutation statistics revealed that DVEPs sample points from 230ms to 280ms in most brain areas changed significantly with SVF. More specifically, we found that amplitudes of component P2 changed significantly when SVF increased. Additionally, independent component analysis (ICA) identified that component P2 which originated from posterior cingulate cortex and precuneus, was associated statistically with SVF. We believe that SVF is rather a conscious status concerning the changes of self-awareness or self-location awareness than the performance reduction of retinal image processing. Moreover, we suggest that indicators representing higher conscious state may be a better indicator for SVF evaluation in VR environments.

Perceptive and Affective Impairments In Emotive Eye-Region Processing in Alexithymia

Alexithymia is characterized by impairments in emotion processing, frequently linked to facial expressions of emotion. The eye-region conveys information necessary for emotion processing. It has been demonstrated that alexithymia is associated with reduced attention to the eyes, but little is known regarding the cognitive and electrophysiological mechanisms underlying emotive eye-region processing in alexithymia. Here, we recorded behavioral and electrophysiological responses of individuals with alexithymia (ALEX; n = 25) and individuals without alexithymia (NonALEX; n = 23) while they viewed intact and eyeless faces with angry and sad expressions during a dual-target rapid serial visual presentation task. Results showed different eye-region focuses and differentiating N1 responses between intact and eyeless faces to anger and sadness in NonALEX, but not in ALEX, suggesting deficient perceptual processing of the eye-region in alexithymia. Reduced eye-region focus and smaller differences in frontal alpha asymmetry in response to sadness between intact and eyeless faces were observed in ALEX than NonALEX, indicative of impaired affective processing of the eye-region in alexithymia. These findings highlight perceptual and affective abnormalities of emotive eye-region processing in alexithymia. Our results contribute to understanding the neuropsychopathology of alexithymia and alexithymia-related disorders.

Frontal and parietal EEG alpha asymmetry: a large-scale investigation of short-term reliability on distinct EEG systems

EEG resting-state alpha asymmetry is one of the most widely investigated forms of functional hemispheric asymmetries in both basic and clinical neuroscience. However, studies yield inconsistent results. One crucial prerequisite to obtain reproducible results is the reliability of the index of interest. There is a body of research suggesting a moderate-to-good reliability of EEG resting-state alpha asymmetry, but unfortunately sample sizes in these studies are typically small. This study presents the first large-scale short-term reliability study of frontal and parietal EEG resting-state alpha asymmetry. We used the Dortmund Vital Study data set containing 370 participants. In each participant, EEG resting state was recorded eight times, twice with their eyes opened, twice with their eyes-closed, each on two different EEG systems. We found good reliability of EEG alpha power and alpha asymmetry on both systems for electrode pairs. We also found that alpha power asymmetry reliability is higher in the eyes-closed condition than in the eyes-open condition. The frontomedial electrode pair showed weaker reliability than the frontolateral and parietal electrode pairs. Interestingly, we found no population-level alpha asymmetry in frontal electrodes, one of the most investigated electrode sites in alpha asymmetry research. In conclusion, our results suggest that while EEG alpha asymmetry is an overall reliable measure, frontal alpha asymmetry should be assessed using multiple electrode pairs.

Replicating Cortical Signatures May Open the Possibility for "Transplanting" Brain States via Brain Entrainment

Brain states, which correlate with specific motor, cognitive, and emotional states, may be monitored with noninvasive techniques such as electroencephalography (EEG) and magnetoencephalography (MEG) that measure macroscopic cortical activity manifested as oscillatory network dynamics. These rhythmic cortical signatures provide insight into the neuronal activity used to identify pathological cortical function in numerous neurological and psychiatric conditions. Sensory and transcranial stimulation, entraining the brain with specific brain rhythms, can effectively induce desired brain states (such as state of sleep or state of attention) correlated with such cortical rhythms. Because brain states have distinct neural correlates, it may be possible to induce a desired brain state by replicating these neural correlates through stimulation. To do so, we propose recording brain waves from a "donor" in a particular brain state using EEG/MEG to extract cortical signatures of the brain state. These cortical signatures would then be inverted and used to entrain the brain of a "recipient" via sensory or transcranial stimulation. We propose that brain states may thus be transferred between people by acquiring an associated cortical signature from a donor, which, following processing, may be applied to a recipient through sensory or transcranial stimulation. This technique may provide a novel and effective neuromodulation approach to the noninvasive, non-pharmacological treatment of a variety of psychiatric and neurological disorders for which current treatments are mostly limited to pharmacotherapeutic interventions.

The Difficult Integration between Human and Animal Studies on Emotional Lateralization: A Perspective Article

Even if for many years hemispheric asymmetries have been considered as a uniquely human feature, an increasing number of studies have described hemispheric asymmetries for various behavioral functions in several nonhuman species. An aspect of animal lateralization that has attracted particular attention has concerned the hemispheric asymmetries for emotions, but human and animal studies on this subject have been developed as independent lines of investigation, without attempts for their integration. In this perspective article, after an illustration of factors that have hampered the integration between human and animal studies on emotional lateralization, I will pass to analyze components and stages of the processing of emotions to distinguish those which point to a continuum between humans and many animal species, from those which suggest a similarity only between humans and great apes. The right lateralization of sympathetic functions (involved in brain and bodily activities necessary in emergency situations) seems consistent across many animal species, whereas asymmetries in emotional communication and in structures involved in emotional experience, similar to those observed in humans, have been documented only in primates.

A Literature Review of EEG-Based Affective Computing in Marketing

Affect plays an important role in the consumer decision-making process and there is growing interest in the development of new technologies and computational approaches that can interpret and recognize the affects of consumers, with benefits for marketing described in relation to both academia and industry. From an interdisciplinary perspective, this paper aims to review past studies focused on electroencephalography (EEG)-based affective computing (AC) in marketing, which provides a promising avenue for studying the mechanisms underlying affective states and developing recognition computational models to predict the psychological responses of customers. This review offers an introduction to EEG technology and an overview of EEG-based AC; provides a snapshot of the current state of the literature. It briefly presents the themes, challenges, and trends in studies of affect evaluation, recognition, and classification; and further proposes potential guidelines for researchers and marketers.

Frontal Asymmetry in an approach-avoidance conflict paradigm

The frontal cortex appears to be asymmetrically related to approach motivation, avoidance motivation, and motivational conflict. Much past work has investigated approach and avoidance motivation, but little work has investigated frontal asymmetry in the face of motivational conflict in part because of the inherent conflict between avoidance motivation and motivational conflict. The current study sought to disentangle the existing confound between avoidance motivation and motivational conflict. In the study, participants selected the likelihood of viewing negative (vs. positive) images for zero reward points (avoidance only condition), or negative (vs. positive) images for the chance to win reward points (approach-avoidance conflict conditions). Participants exhibited greater relative right frontal asymmetry while making percent likelihood selections in the approach-avoidance conflict conditions relative to the avoidance only conditions. Additionally, participants exhibited greater relative right frontal asymmetry while viewing disgust images during trials with the greatest approach-avoidance conflict relative to trials with the lowest approach-avoidance conflict. Together, these results suggest that motivational conflict, and not avoidance motivation, is associated with greater relative right frontal activity.

Investigating real-life emotions in romantic couples: a mobile EEG study

The neural basis of emotional processing has been largely investigated in constrained spatial environments such as stationary EEGs or fMRI scanners using highly artificial stimuli like standardized pictures depicting emotional scenes. Typically, such standardized experiments have low ecological validity and it remains unclear whether their results reflect neuronal processing in real-life affective situations at all. Critically, emotional situations do not only encompass the perception of emotions, but also behavioral components associated with them. In this study, we aimed to investigate real-life emotions by recording couples in their homes using mobile EEG technology during embracing, kissing and emotional speech. We focused on asymmetries in affective processing as emotions have been demonstrated to be strongly lateralized in the brain. We found higher alpha and beta power asymmetry during kissing and embracing on frontal electrodes during emotional kisses and speech compared to a neutral control condition indicative of stronger left-hemispheric activation. In contrast, we found lower alpha power asymmetry at parieto-occipital electrode sites in the emotional compared to the neutral condition indicative of stronger right-hemispheric activation. Our findings for alpha power asymmetries are in line with models of emotional lateralization that postulate a valence-specific processing over frontal cortices and right-hemispheric dominance in emotional processing in parieto-occipital regions. In contrast, beta power asymmetries pointed more towards valence-specific processing indicating that, while alpha and beta frequencies seem to be functionally associated, they are not reflecting identical cognitive processing.

Individual Differences in Hemodynamic Responses Measured on the Head Due to a Long-Term Stimulation Involving Colored Light Exposure and a Cognitive Task: A SPA-fNIRS Study

When brain activity is measured by neuroimaging, the canonical hemodynamic response (increase in oxygenated hemoglobin ([O2Hb]) and decrease in deoxygenated hemoglobin ([HHb]) is not always seen in every subject. The reason for this intersubject-variability of the responses is still not completely understood. This study is performed with 32 healthy subjects, using the systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS) approach. We investigate the intersubject variability of hemodynamic and systemic physiological responses, due to a verbal fluency task (VFT) under colored light exposure (CLE; blue and red). Five and seven different hemodynamic response patterns were detected in the subgroup analysis of the blue and red light exposure, respectively. We also found that arterial oxygen saturation and mean arterial pressure were positively correlated with [O2Hb] at the prefrontal cortex during the CLE-VFT independent of the color of light and classification of the subjects. Our study finds that there is substantial intersubject-variability of cerebral hemodynamic responses, which is partially explained by subject-specific systemic physiological changes induced by the CLE-VFT. This means that both subgroup analyses and the additional assessment of systemic physiology are of crucial importance to achieve a comprehensive understanding of the effects of a CLE-VFT on human subjects.

It is all relative: Contextual influences on boredom and neural correlates of regulatory processes

Interest in the influences on and strategies to mitigate boredom has grown immensely. Boredom emerges in contexts in which people have difficulty paying attention, such as underchallenging relative to optimally challenging conditions. The current study probed contextual influences on peoples' experience of boredom by manipulating the order with which people performed easy and optimally challenging conditions of a task (N = 113). We measured frontal alpha asymmetry (FAA) and theta/beta as neural correlates of self-regulatory and attentional control processes, respectively. Results showed self-reported boredom was higher in the easy condition when the optimal condition was completed before it. Similarly, participant's FAA shifted rightward from the first to the second task when the optimal condition was completed prior to the easy condition, indicating that self-regulatory processes were strongly engaged under these context-specific conditions. Theta/beta was lower during the easy relative to the optimal condition, regardless of the task order, indicating that maintaining attention in the easy condition was more difficult. No relations between perceptions of the task and neural correlates were observed. Exploratory analyses revealed higher levels of variability in FAA and theta/beta were associated with less enjoyment and more boredom, respectively. We speculate these observations reflect the less consistent engagement of self-regulatory and attentional control and, in turn, might play a role in peoples' subjective experience. We discuss the implications of our findings for our understanding of influences on and strategies to mitigate boredom, as well as how attentional and self-regulatory processes operate under conditions boredom typically emerges.

Music therapy as social skill intervention for children with comorbid ASD and ID: study protocol for a randomized controlled trial

BACKGROUND

Autism spectrum disorder (ASD) is a developmental impairment characterized by persistent deficits in social communication and interactions, and over half of children with ASD possess below average intellectual ability (IQ < 85). The social development and response to social skill interventions among children with ASD and comorbid intellectual disability (ID) is not well understood. Music therapy is a systematic process of intervention, wherein a therapist may help clients promote their social skills by using musical experience. The proposed study will address limited research evidence on music therapy as an intervention for social functioning in children with ASD with mild to borderline ID.

METHOD

A randomized controlled trial (RCT) with two parallel groups of 40 children each (1:1 allocation ratio) is planned. Participants will receive 45 min of music therapy or non-musical intervention targeting social skills once a week for 12 weeks. Primary outcome measures will be independent ratings on the Childhood Autism Rating Scale and parent ratings on the Social Responsiveness Scale-2. Linear mixed-effects models for these two outcome measures will be created for data collected at 2-week pre-intervention, 2-week post-intervention, and 4-month post-intervention sessions. In-session behaviors at the first and last intervention will be videotaped and coded offline and compared. Pretreatment neural response of quantitative electroencephalograms (qEEG) to social scenes will be used to predict the outcomes of musical and non-musical social skill interventions, whereas qEEG responses to music will be used to predict the effectiveness of musical social skill intervention.

DISCUSSION

If neural markers of social skill development are found, then the long-term goal is to develop individualized intervention based on pre-treatment markers to maximize treatment efficacy. The proposed study's results may also suggest directions to development and provision of music therapy services in Hong Kong.

TRIAL REGISTRATION

ClinicalTrials.gov ( NCT04557488 ). Registered September 21, 2020.

Differentiating Responders and Non-responders to rTMS Treatment for Disorder of Consciousness Using EEG After-Effects

Background: It is controversial whether repetitive transcranial magnetic stimulation (rTMS) has potential benefits in improving the awareness of patients with disorder of consciousness (DOC). We hypothesized that rTMS could improve consciousness only in DOC patients who have measurable brain responses to rTMS.

Objective: In this study, we aimed to investigate the EEG after-effects induced by rTMS in DOC patients and attempted to propose a prediction algorithm to discriminate between DOC patients who would respond to rTMS treatment from those who would not.

Methods: Twenty-five DOC patients were enrolled in this study. Over 4 weeks, each patient received 20 sessions of 20 Hz rTMS that was applied over the left dorsolateral prefrontal cortex (DLPFC). For each patient, resting-state EEG was recorded before and immediately after one session of rTMS to assess the neurophysiologic modification induced by rTMS. The coma recovery scale revised (CRS-R) was used to define responders with improved consciousness.

Results: Of the 25 DOC patients, 10 patients regained improved consciousness and were classified as responders. The responders were characterized by more preserved alpha power and a significant reduction of delta power induced by rTMS. The analysis of receiver operating characteristic (ROC) curves showed that the algorithm calculated from the relative alpha power and the relative delta power had a high accuracy in identifying DOC patients who were responders.

Conclusions: DOC patients who had more preserved alpha power and a significant reduction in the delta band that was induced by rTMS are likely to regain improved consciousness, which provides a tool to identify DOC patients who may benefit in terms of therapeutic consciousness.

A conceptual critique of brain lateralization models in emotional face perception: Toward a hemispheric functional-equivalence (HFE) model

The present review proposes a novel dynamic model of brain lateralization of emotional (happy, surprised, fearful, sad, angry, and disgusted) and neutral face perception. Evidence to date suggests that emotional face perception is lateralized in the brain. At least five prominent hypotheses of the lateralization of emotional face perception have been previously proposed; the right-hemisphere hypothesis; the valence-specific hypothesis; the modified valence-specific hypothesis; the motivational hypothesis; and behavioral activation/inhibition system hypothesis. However, a growing number of recent replication studies exploring those hypotheses frequently provide inconsistent or even contradictory results. The latest neuroimaging and behavioral studies strongly demonstrate the functional capacity of both hemispheres to process emotions relatively successfully. Moreover, the flexibility of emotional brain-networks in both hemispheres is functionally high even to the extent of a possible reversed asymmetry of the left and the right hemisphere performance under altered neurophysiological and psychological conditions. The present review aims to a) provide a critical conceptual analysis of prior and current hypotheses of brain lateralization of emotional and neutral face perception; b) propose an integrative introduction of a novel hemispheric functional-equivalence (HFE) model in emotional and neutral face perception based on the evaluation of theoretical considerations, behavioral and neuroimaging studies: the brain is initially right-biased in emotional and neutral face perception by default; however, altered psychophysiological conditions (e.g., acute stress, a demanding emotional task) activate a distributed brain-network of both hemispheres toward functional equivalence that results in relatively equalized behavioral performance in emotional and neutral face perception. The proposed novel model may provide a practical tool in further experimental investigation of brain lateralization of emotional face perception.

Dynamics of frontal alpha asymmetry in mother-infant dyads: Insights from the Still Face Paradigm

The parent-infant dynamic has a foundational role in emotion regulation development. Electroencephalography (EEG) hyperscanning from mother-infant dyads can provide an unprecedented window into inter-brain dynamics during the parent-infant exchange. This potential depends on the feasibility of hyperscanning with dyads in emotionally taxing contexts. We sought to demonstrate feasibility of hyperscanning from 10 mother-infant dyads during the Still Face Procedure (SFP). We measured frontal alpha asymmetry (FAA) to elucidate ongoing regulatory dynamics and considered maternal caregiving quality as a window into dyads' history. Results showed dyads exhibited a rightward shift in FAA over the course of SFP, indicating growing negative emotionality and desire to withdraw. Results also showed growing variability in FAA for infants over the course of SFP, indicating less active emotional control as stress ensued. Variability was especially low for mothers during periods when asked to be emotionally unavailable, suggesting active control to match the task demands. Dyads with a more responsive mother exhibited higher (more left) FAA relative to dyads with a less responsive mother, which might reflect a more positive emotional experience overall. We raise important methodological and theoretical questions that hyperscanning during SFP can address, such as the developmental origins of trait-like self-regulatory dispositions.

Neurocoaching: exploring the relationship between coach and coachee by means of bioelectrical signal similarities

Coaching aims to unlock the human's potential, self-awareness and responsibility, improving the professional performances and the personal satisfaction. Its effectiveness is known to depend on the degree of bonding and mutual engagement of the coaching relationship. In this exploratory study we recorded synchronised EEG and SC data from both coach and coachee during 36 individual sessions, performed following 2 different coaching methods. Our principal aim was to investigate the temporal evolution of the bonding and the mutual engagement along the different steps of a session, by means of a "similarity" metric based on the DTW distance between signals (namely, S-TVM). We found significant differences between session phases for the EEG-related S-TVMs (BAR, BATR and AWI), with maximum values (defined as "tuning") all in the same phase, but differentiated between the two experiments. The results suggest a temporal concurrency of the engagement and emotional tunings, whose specific location seems to be a function of the coaching approach.

Exploring EEG microstates for affective computing: decoding valence and arousal experiences during video watching

Investigating the electroencephalography (EEG) correlates of human emotional experiences has attracted increasing interest in the field of affective computing. Substantial progress has been made during the past decades, mainly by using EEG features extracted from localized brain activities. The present study explored a brain network-based feature defined by EEG microstates for a possible representation of emotional experiences. A publicly available and widely used benchmarking EEG dataset called DEAP was used, in which 32 participants watched 40 one-minute music videos with their 32channel EEG recorded. Four quasi-stable prototypical microstates were obtained, and their temporal parameters were extracted as features. In random forest regression, the microstate features showed better performances for decoding valence (model fitting mean squared error (MSE) = 3.85±0.28 and 4.07 ± 0.30, respectively, p = 0.022) and comparable performances for decoding arousal (MSE = 3.30±0.30 and 3.41 ±0.31, respectively, p = 0.169), as compared to conventional spectral power features. As microstate features describe neural activities from a global spatiotemporal dynamical perspective, our findings demonstrate a possible new mechanism for understanding human emotion and provide a promising type of EEG feature for affective computing.