EEG coherence in theta, alpha, and beta bands in frontal regions and executive functions

The influence of empathic concern on evaluative processing in self and charity outcomes

Empathy plays a crucial role in determining how one understands others' emotional experiences and behavioral decisions. This study aimed to explore whether empathic concern affects the processing of self-related and charity-related outcome evaluations. In this study, participants performed gambling tasks for themselves and low- and high-empathy charities. The behavioral results showed that low-empathy charities had a significantly higher risk rate than the self, whereas there was no significant difference between low-and high-empathy charities. The event-related potential (ERP) results showed that the P300 valence difference (d-P300) of the self was significantly higher for high-empathy charitable activities than for low-empathy charitable activities, and the d-P300 of high-empathy charitable activities was significantly higher than that of low-empathy charitable activities. The P300 valence differences primarily originated from activation difference in the posterior mid-cingulate cortex (pMCC) and medial prefrontal cortex (mPFC). The time-frequency analysis showed that positive outcomes induced greater β2 event-related desynchronization (ERD) amplitudes for high-empathy charitable activities compared to negative outcomes. These findings suggest that empathic concern increased the distinction between good and bad outcomes for charities and promoted greater cognitive effort allocation toward prosocial rewards. The d-P300 is closely linked to activations in the pMCC and mPFC.

Dynamic Cortical Connectivity During Propofol Sedation in Glioma Patients

BACKGROUND

The behavioral manifestations and neurophysiological responses to sedation can assist in understanding brain function after neurological damage, and can be described by cortical functional connectivity. Glioma patients may experience neurological deficits that are not clinically detectable before sedation. We hypothesized that patients with gliomas exhibit distinct cortical connectivity patterns compared to non-neurosurgical patients during sedation.

METHODS

This is a secondary analysis of a previously published prospective observational study. Patients scheduled for resection of supratentorial glioma (n=21) or a non-neurosurgical procedure (n=21) under general anesthesia were included in this study. Frontal electroencephalography (EEG) signals were recorded at different sedation levels as assessed by the Observer Assessment of Alertness/Sedation (OAA/S) score. Kernel principal component analysis and k -means clustering were used to determine possible temporal dynamics from the weighted phase lag index characteristics.

RESULTS

Ten EEG connectivity states were identified by clustering (76% consistency), each with unique properties. At OAA/S 3, the median (Q1, Q3) occurrence rates of state 6 (glioma group, 0.110 [0.083, 0.155] vs. control group, 0.070 [0.030, 0.110]; P =0.008) and state 7 (glioma group, 0.105 [0.083, 0.148] vs. control group: 0.065 [0.038, 0.090]; P =0.001), which are dominated by beta connectivity, were significantly different between the 2 groups, reflecting differential conversion of the beta band between the left and right brain regions. In addition, the temporal dynamics of the brain's functional connectivity was also reflected in the transition relationships between metastable states.

CONCLUSIONS

There were differences in EEG functional connectivity, which is dynamic, between the glioma and nonglioma groups during sedation.

Parietal alpha and theta power predict cognitive training gains in middle-aged adults

Research on executive functions training shows inconsistent outcomes, with factors like age, baseline cognitive abilities, and personality traits implicated as predictive of training gains, while limited attention has been given to neurophysiological markers. Theta and alpha band power are linked to cognitive performance, suggesting a potential area for further study. This study aimed to determine whether relative theta and alpha power and their ratio could predict gains in updating and inhibition training beyond the practice effects (the order of training session). Forty healthy middle-aged adults (aged 49-65) were randomly assigned to either the cognitive training group (n = 20), or the communication skills (control) group (n = 20). Both groups completed the self-administered training sessions twice a week for 10 weeks, totaling to 20 sessions. Resting-state EEG data were recorded before the first session. Mixed-effects model analyses revealed that higher relative parietal alpha power positively predicted training performance, while theta power negatively predicted performance. Additionally, higher parietal alpha/theta ratio was associated with better training outcomes, while the frontal alpha/theta ratio did not demonstrate significant predictive value. Other EEG measures did not show additional predictive power beyond what was accounted for by the session effects. The findings imply that individuals with specific EEG pattern may change with cognitive training, making resting-state EEG a useful tool in tailoring interventions.

Functional connectivity in burnout syndrome: a resting-state EEG study

Chronic occupational stress is associated with a pronounced decline in emotional and cognitive functioning. Studies on neural mechanisms indicate significant changes in brain activity and changed patterns of event-related potentials in burnout subjects. This study presents an analysis of brain functional connectivity in a resting state, thus providing a deeper understanding of the mechanisms accompanying burnout syndrome. The sample consists of 49 burnout employees and 49 controls, matched by age, gender and occupation (Mage = 36.15, SD = 8.10; 59 women, 39 men). Continuous dense-array EEG data were collected from a 256-channel EEG system. The difference in functional connectivity between burnout and control subjects was tested in the eyes-closed (EC) and eyes-open (EO) conditions using the resting-state paradigm. The results indicate significant differences in brain activity between the burnout and the control groups. The resting-state network of the burnout group is characterized by decreased functional connectivity in frontal and midline areas in the alpha3 sub-band (11-13 Hz) in an eyes-open condition. The most significant effect of decreased connectivity was observed in the right frontal brain area. For the first time, these analyses point to distinctive aspects of functional connectivity within the alpha3 sub-band in burnout syndrome. These findings provide insights into the neurobiological underpinnings of burnout syndrome and its associations with changed resting-state networks. The data on neural characteristics in burnout subjects may help to understand the mechanisms of decline in cognitive function and emotion regulation and to search for adequate methods of treatment.

The Brain Waves During Reaching Tasks in People with Subacute Low Back Pain: A Cross-Sectional Study

Subacute low back pain (sLBP) is a critical transitional phase between acute and chronic stages and is key in determining the progression to chronic pain. While persistent pain has been linked to changes in brain activity, studies have focused mainly on acute and chronic phases, leaving neural changes during the subacute phase-especially during movement-under-researched. This cross-sectional study aimed to investigate changes in brain activity and the impact of pain intensity in individuals with sLBP during rest and reaching movements. Using a 28-electrode EEG, we measured motor-related brain waves, including theta, alpha, beta, and gamma oscillations. Transitioning from rest to movement phases resulted in significant reductions (> 80%) in mean power across all frequency bands, indicating dynamic brain activation in response to movement. Furthermore, pain intensity was significantly correlated with brain wave activity. During rest, pain intensity was positively correlated with alpha oscillation activity in the central brain area (r = 0.40, p < 0.05). In contrast, during movement, pain intensity was negatively correlated with changes in brain activity (r = -0.36 to -0.40, p < 0.05). These findings suggest that pain influences brain activity differently during rest and movement, underscoring the impact of pain levels on neural networks related to the sensorimotor system in sLBP and highlighting the importance of understanding neural changes during this critical transitional phase.

Advances in brain-computer interface for decoding speech imagery from EEG signals: a systematic review

Numerous individuals encounter challenges in verbal communication due to various factors, including physical disabilities, neurological disorders, and strokes. In response to this pressing need, technology has actively pursued solutions to bridge the communication gap, recognizing the inherent difficulties faced in verbal communication, particularly in contexts where traditional methods may be inadequate. Electroencephalogram (EEG) has emerged as a primary non-invasive method for measuring brain activity, offering valuable insights from a cognitive neurodevelopmental perspective. It forms the basis for Brain-Computer Interfaces (BCIs) that provide a communication channel for individuals with neurological impairments, thereby empowering them to express themselves effectively. EEG-based BCIs, especially those adapted to decode imagined speech from EEG signals, represent a significant advancement in enabling individuals with speech disabilities to communicate through text or synthesized speech. By utilizing cognitive neurodevelopmental insights, researchers have been able to develop innovative approaches for interpreting EEG signals and translating them into meaningful communication outputs. To aid researchers in effectively addressing this complex challenge, this review article synthesizes key findings from state-of-the-art significant studies. It investigates into the methodologies employed by various researchers, including preprocessing techniques, feature extraction methods, and classification algorithms utilizing Deep Learning and Machine Learning approaches and their integration. Furthermore, the review outlines the potential avenues for future research, with the goal of advancing the practical implementation of EEG-based BCI systems for decoding imagined speech from a cognitive neurodevelopmental perspective.

Neurocognitive effects of 3 mA prefrontal electrical stimulation in schizophrenia: A randomized sham-controlled tDCS-fMRI study protocol

BACKGROUND

Schizophrenia (SCZ) is characterized by cognitive deficits that are linked to prefrontal cortex dysfunction. While transcranial direct current stimulation (tDCS) shows promise for improving cognition, the effects of intensified 3mA tDCS protocols on brain physiology are unknown. This project aims to elucidate the neurophysiological and cognitive effects of an intensified prefrontal tDCS protocol in SCZ.

METHODS

The study is designed as a randomized, double-blind, 2-arm parallel-group, sham-controlled, trial. Forty-eight participants with SCZ and cognitive impairment (measured via a set of executive functions tests) will be randomly allocated to receive either a single session of active (n = 24) or sham (n = 24) tDCS (20-min, 3-mA). The anodal and cathodal electrodes are positioned over the left and right DLPFC respectively. The stimulation occurs concurrently with the working memory task, which is initiated precisely 5 minutes after the onset of tDCS. Structural and resting-state (rs-fMRI) scans are conducted immediately before and after both active and sham tDCS using a 3 Tesla scanner (Siemens Prisma model) equipped with a 64-channel head coil. The primary outcome will be changes in brain activation (measures vis BOLD response) and working memory performance (accuracy, reaction time).

DISCUSSION

The results of this study are helpful in optimizing tDCS protocols in SCZ and inform us of neurocognitive mechanisms underlying 3 mA stimulation. This study will additionally provide initial safety and efficacy data on a 3 mA tDCS protocol to support larger clinical trials. Positive results could lead to rapid and broader testing of a promising tool for debilitating symptoms that affect the majority of patients with SCZ. The results will be made available through publications in peer-reviewed journals and presentations at national and international conferences.

Neurophysiological and Autonomic Correlates of Metacognitive Control of and Resistance to Distractors in Ecological Setting: A Pilot Study

In organisational contexts, professionals are required to decide dynamically and prioritise unexpected external inputs deriving from multiple sources. In the present study, we applied a multimethodological neuroscientific approach to investigate the ability to resist and control ecological distractors during decision-making and to explore whether a specific behavioural, neurophysiological (i.e., delta, theta, alpha and beta EEG band), or autonomic (i.e., heart rate-HR, and skin conductance response-SCR) pattern is correlated with specific personality profiles, collected with the 10-item Big Five Inventory. Twenty-four participants performed a novel Resistance to Ecological Distractors (RED) task aimed at exploring the ability to resist and control distractors and the level of coherence and awareness of behaviour (metacognition ability), while neurophysiological and autonomic measures were collected. The behavioural results highlighted that effectiveness in performance did not require self-control and metacognition behaviour and that being proficient in metacognition can have an impact on performance. Moreover, it was shown that the ability to resist ecological distractors is related to a specific autonomic profile (HR and SCR decrease) and that the neurophysiological and autonomic activations during task execution correlate with specific personality profiles. The agreeableness profile was negatively correlated with the EEG theta band and positively with the EEG beta band, the conscientiousness profile was negatively correlated with the EEG alpha band, and the extroversion profile was positively correlated with the EEG beta band. Taken together, these findings describe and disentangle the hidden relationship that lies beneath individuals' decision to inhibit or activate intentionally a specific behaviour, such as responding, or not, to an external stimulus, in ecological conditions.

The impact of internal-generated contextual clues on EFL vocabulary learning: insights from EEG

With the popularity of learning vocabulary online among English as a Foreign Language (EFL) learners today, educators and researchers have been considering ways to enhance the effectiveness of this approach. Prior research has underscored the significance of contextual clues in vocabulary acquisition. However, few studies have compared the context provided by instructional materials and that generated by learners themselves. Hence, this present study sought to explore the impact of internal-generated contextual clues in comparison to those provided by instructional materials on EFL learners' online vocabulary acquisition. A total of 26 university students were enrolled and underwent electroencephalography (EEG). Based on a within-subjects design, all participants learned two groups of vocabulary words through a series of video clips under two conditions: one where the contexts were externally provided and the other where participants themselves generated the contexts. In this regard, participants were tasked with either viewing contextual clues presented on the screen or creating their own contextual clues for word comprehension. EEG signals were recorded during the learning process to explore neural activities, and post-tests were conducted to assess learning performance after each vocabulary learning session. Our behavioral results indicated that comprehending words with internal-generated contextual clues resulted in superior learning performance compared to using context provided by instructional materials. Furthermore, EEG data revealed that learners expended greater cognitive resources and mental effort in semantically integrating the meaning of words when they self-created contextual clues, as evidenced by stronger alpha and beta-band oscillations. Moreover, the stronger alpha-band oscillations and lower inter-subject correlation (ISC) among learners suggested that the generative task of creating context enhanced their top-down attentional control mechanisms and selective visual processing when learning vocabulary from videos. These findings underscored the positive effects of internal-generated contextual clues, indicating that instructors should encourage learners to construct their own contexts in online EFL vocabulary instruction rather than providing pre-defined contexts. Future research should aim to explore the limits and conditions of employing these two types of contextual clues in online EFL vocabulary learning. This could be achieved by manipulating the quality and understandability of contexts and considering learners' language proficiency levels.

Temporal and Spatial Information Elicit Different Power and Connectivity Profiles during Working Memory Maintenance

Working memory (WM) is the cognitive ability to store and manipulate information necessary for ongoing tasks. Although frontoparietal areas are involved in the retention of visually presented information, oscillatory neural activity differs for temporal and spatial WM processing. In this study, we corroborated previous findings describing the modulation of neural oscillations and expanded our investigation to the network organization underlying the cognitive processing of temporal and spatial information. We utilized MEG recordings during a Sternberg visual WM task. The spectral oscillatory activity in the maintenance phase revealed increased frontal theta (4-8 Hz) and parietal beta (13-30 Hz) in the temporal condition. Source level coherence analysis delineated the prominent role of parietal areas in all frequency bands during the maintenance of temporal information, whereas frontal and central areas showed major contributions in theta and beta ranges during the maintenance of spatial information. Our study revealed distinct spectral profiles of neural oscillations for separate cognitive subdomains of WM processing. The delineation of specific functional networks might have important implications for clinical applications, enabling the development of stimulation protocols targeting cognitive disabilities associated with WM impairments.

Cognitive flexibility impairment in temporal lobe epilepsy: The impact of epileptic foci lateralization on executive functions

INTRODUCTION

Temporal Lobe Epilepsy (TLE) has been associated with memory impairments, which are typically linked to hippocampal and mesial temporal cortex lesions. Considering the presence of extensive bidirectional frontotemporal connections, it can be hypothesized that executive dysfunction in TLE is modulated by the lateralization of the epileptic foci.

MATERIAL AND METHODS

A comprehensive neuropsychological executive functions protocol was administered to 63 participants, including 42 individuals with temporal lobe epilepsy (20 with right-TLE and 22 with left-TLE) and 21 healthy controls aged 20-49.

RESULTS

The results indicate that TLE patients exhibit poorer executive performance compared to healthy controls in working memory (F(2,60) = 4.18, p <.01), planning (F(2,60) = 4.71, p <.05), set shifting (F(2,60) = 10.1, p <.001), phonetic verbal fluency (F(2,60) = 11.71, p <.01) and semantic verbal fluency (F(2,60) = 9.61, p <.001. No significant differences were found in cognitive inhibition. Furthermore, right-TLE patients showed lower performance than left-TLE in set shifting (F(1,61) = 6.45, p <.05), while no significant differences were observed in working memory, planning, inhibition, and verbal fluency.

CONCLUSIONS

This research emphasize the importance of considering the lateralization of the temporal lobe focus to achieve a more accurate neuropsychological characterization. The cognitive differences between left and right TLE patients highlight the need for individualized approaches in their treatment and care.

Predicting Tacit Coordination Success Using Electroencephalogram Trajectories: The Impact of Task Difficulty

In this study, we aim to develop a machine learning model to predict the level of coordination between two players in tacit coordination games by analyzing the similarity of their spatial EEG features. We present an analysis, demonstrating the model's sensitivity, which was assessed through three conventional measures (precision, recall, and f1 score) based on the EEG patterns. These measures are evaluated in relation to the coordination task difficulty, as determined by the coordination index (CI). Tacit coordination games are games in which two individuals are requested to select the same option out of a closed set without the ability to communicate. This study aims to examine the effect of the difficulty of a semantic coordination task on the ability to predict a successful coordination between two players based on the compatibility between their EEG signals. The difficulty of each of the coordination tasks was estimated based on the degree of dispersion of the different answers given by the players reflected by the CI. The classification of the spatial distance between each pair of individual brain patterns, analyzed using the random walk algorithm, was used to predict whether successful coordination occurred or not. The classification performance was obtained for each game individually, i.e., for each different complexity level, via recall and precision indices. The results showed that the classifier performance depended on the CI, that is, on the level of coordination difficulty. These results, along with possibilities for future research, are discussed.

Cerebral dominance representation of directed connectivity within and between left-right hemispheres and frontal-posterior lobes in mild cognitive impairment

Electroencephalography can assess connectivity between brain hemispheres, potentially influencing cognitive functions. Much of the existing electroencephalography research primarily focuses on undirected connectivity, leaving uncertainties about directed connectivity alterations between left-right brain hemispheres or frontal-posterior lobes in mild cognitive impairment. We analyzed resting-state electroencephalography data from 34 mild cognitive impairment individuals and 23 normal controls using directed transfer function and graph theory for directed network analysis. Concerning the dominance within left-right hemispheres or frontal-posterior lobes, the mild cognitive impairment group exhibited decreased connectivity within the frontal compared with posterior brain regions in the delta and theta bands. Regarding the dominance between the brain hemispheres or lobes, the mild cognitive impairment group showed reduced connectivity from the posterior to the frontal regions versus the reverse direction in the same bands. Among all participants, the intra-lobe frontal-posterior dominance correlated positively with executive function in the delta and alpha bands. Inter-lobe dominance between frontal and posterior regions also positively correlated with executive function, attention, and language in the delta band. Additionally, interhemispheric dominance between the left and right hemispheres positively correlated with attention in delta and theta bands. These findings suggest altered cerebral dominance in mild cognitive impairment, potentially serving as electrophysiological markers for neurocognitive disorders.

Offline EEG hyper-scanning using anonymous walk embeddings in tacit coordination games

In this paper we present a method to examine the synchrony between brains without the need to carry out simultaneous recordings of EEG signals from two people which is the essence of hyper-scanning studies. We used anonymous random walks to spatially encode the entire graph structure without relying on data at the level of individual nodes. Anonymous random walks enabled us to encapsulate the structure of a graph regardless of the specific node labels. That is, random walks that visited different nodes in the same sequence resulted in the same anonymous walk encoding. We have analyzed the EEG data offline and matched each possible pair of players from the entire pool of players that performed a series of tacit coordination games. Specifically, we compared between two network patterns associated with each possible pair of players. By using classification performed on the spatial distance between each pair of individual brain patterns, analyzed by the random walk algorithm, we tried to predict whether each possible pair of players has managed to converge on the same solution in each tacit coordination game. Specifically, the distance between a pair of vector embeddings, each associated with one of the players, was used as input for a classification model for the purpose of predicting whether the two corresponding players have managed to achieve successful coordination. Our model reached a classification accuracy of ~85%.

Scientific Problem Solving and Brain Symmetry Index: An exploratory EEG study

Scientific problem solving has recently attracted fixation in the field of cognitive neuroscience and science education. Until now, there is very little evidence on the brain dynamics of scientific problem-solving processes. In this study, we were interested in exploring whether Brain Symmetry Index (BSI) would be an EEG index to reveal neural information. The present EEG study used two levels of complexity physics problems to research the neural mechanism of problem solving. Results indicated that relatively greater BSI found during difficult problem solving on the prefrontal theta and beta band. However, smaller BSI on the occipital alpha was found when solving difficult problems. There was no significant relationship between BSI and self-effort evaluation. The current study proposes an EEG index - BSI to reflect underlying brain functional characteristic.

Comparing executive functions in children with attention deficit hyperactivity disorder with or without reading disability: A resting-state EEG study

INTRODUCTION

As numerous studies have shown, executive dysfunction is the main impairment in attention-deficit/hyperactivity disorder. According to recent neuroimaging studies, the frontoparietal coherence plays a key role in overall cognitive functions. Therefore, the aim of this study was to compare executive functions during resting-state EEG by monitoring brain connectivity (coherence) patterns in children with attention deficit hyperactivity disorder (ADHD) with or without reading disability (RD).

METHODS

The statistical sample of the study consisted of 32 children with ADHD aged between 8 and 12 years old with or without specific RD. Each group consisted of 11 boys and 5 girls that were matched on chronological age and gender. EEG was recorded during eyes-opened condition and brain connectivity within and between frontal and parietal regions was analyzed within theta, alpha, and beta bands.

RESULTS

The results revealed that across the frontal regions, the comorbid group showed a significant reduction in the left intrahemispheric coherence in the alpha and beta bands. The ADHD-alone group exhibited increased theta and decreased alpha and beta coherence in frontal regions. In the frontoparietal regions, children in the comorbid group showed lower coherence between frontal and parietal networks compared to children without comorbid RD.

CONCLUSION

The findings indicate that brain connectivity (coherence) patterns of children with ADHD with comorbid RD were more abnormal and lend support to more disrupted cortical connectivity in the comorbid group. Thus, these findings can be a useful marker for better recognizing ADHD and comorbid disabilities.

Frontocentral delta-beta amplitude coupling in endometriosis-related chronic pelvic pain

OBJECTIVE

Endometriosis is associated with neuroplastic changes in cognitive control and pain processing networks. This was the first study to assess eyes-closed resting electroencephalogram (EEG) oscillatory amplitudes in women with endometriosis compared to healthy controls, and explore the relationship with chronic pelvic pain.

METHODS

Women with endometriosis-related chronic pelvic pain and individually age-matched pain-free controls (N = 20 per group) documented pelvic pain for 28 days before having continuous EEG recorded during a 2 min eyes closed resting state. Natural frequency components were extracted for each group using frequency principal components analysis. Corresponding components were assessed for group differences and correlated with pain scores.

RESULTS

Relative to controls, the endometriosis group had greater component amplitudes in delta (0.5 Hz) and beta (∼28 Hz), and reduced alpha (∼10 Hz). Delta and beta amplitudes were positively associated with pain severity, but only beta maintained this association after delta-beta amplitude coupling was controlled.

CONCLUSIONS

Enhanced resting delta and beta amplitudes were seen in women with endometriosis experiencing chronic pelvic pain. This delta-beta coupling varied with pelvic pain severity, perhaps reflecting altered cholinergic tone and/or stress reactivity.

SIGNIFICANCE

Endometriosis-related changes in central pain processing demonstrate a distinct neuronal oscillatory signature detectable at rest.

Prognostic Role of Hemispherical Functional Connectivity in Stroke: A Study via Graph Theory Versus Coherence of Electroencephalography Rhythms

BACKGROUND

The objective of the present study is to explore whether acute stroke may result in changes in brain network architecture by electroencephalography functional coupling analysis and graph theory.

METHODS

Ninety acute stroke patients and 110 healthy subjects were enrolled in different clinical centers in Rome, Italy, starting from 2013, and for each one electroencephalographies were recorded within <15 days from stroke onset. All patients were clinically evaluated through National Institutes of Health Stroke Scale, Barthel Index, and Action Research Arm Test in the acute stage and during the follow-up. Functional connectivity was assessed using Total Coherence and Small World (SW) by comparing the affected and the unaffected hemisphere between groups (Stroke versus Healthy). Correlations between connectivity and poststroke recovery scores have been carried out.

RESULTS

In stroke patients, network hemispheric asymmetry, in terms of Total Coherence, was mainly detected in the affected hemisphere with lower values in Delta, Theta, Alpha1, and Alpha2 (P=0.000001), whereas the unaffected hemisphere showed lower Total Coherence only in Delta and Theta (P=0.000001). SW revealed a significant difference only in the affected hemisphere in all electroencephalography bands (lower SW in Delta (P=0.000003), Theta (P=0.000003), Alpha1 (P=0.000203), and Alpha2 (P=0.028) and higher SW in Beta2 (P=0.000002) and Gamma (P=0.000002)). We also found significant correlations between SW and improvement in National Institutes of Health Stroke Scale (Theta SW: r=-0.2808), Barthel Index (Delta SW: r=0.3692; Theta SW: r=0.3844, Beta2 SW: r=-0.3589; Gamma SW: r=-04948), and Action Research Arm Test (Beta2 SW: r=-0.4274; Gamma SW: r=-0.4370).

CONCLUSIONS

These findings demonstrated changes in global functional connectivity and in the balance of network segregation and integration induced by acute stroke. The findings on the correlations between clinical outcome(s) and poststroke network architecture indicate the possibility to identify a predictive index of recovery useful to address and personalize the rehabilitation program.

The neural mechanism of non-phase-locked EEG activity in task switching

Flexible switching between different tasks is an important cognitive ability for humans and it is often studied using the task-switching paradigm. Although the neural mechanisms of task switching have been extensively explored in previous studies using event-related potentials techniques, the activity and process mechanisms of non-phase-locked electroencephalography (EEG) have rarely been revealed. For this reason, this paper discusses the processing of non-phase-locked EEG oscillations in task switching based on frequency-band delineation. First, the roles of each frequency band in local brain regions were summarized. In particular, during the proactive control process (the cue-stimulus interval), delta, theta, and alpha oscillations played more roles in the switch condition while beta played more roles in repeat task. In the reactive control process (post-target), delta, alpha, and beta are all related to sensorimotor function. Then, utilizing the functional connectivity (FC) method, delta connections in the frontotemporal regions and theta connections located in the parietal-to-occipital sites are involved in the preparatory period before task switching, while alpha connections located in the sensorimotor areas and beta connections located in the frontal-parietal cortex are involved in response inhibition. Finally, cross-frequency coupling (CFC) play an important role in working memory among different band oscillation. The present study shows that in addition to the processing mechanisms specific to each frequency band, there are some shared and interactive neural mechanism in task switching by using different analysis techniques.

Heartfulness Meditation Alters Electroencephalogram Oscillations: An Electroencephalogram Study

Background

Heartfulness meditation (HM) has been shown to have positive impacts on cognition and well-being, which makes it important to look into the neurophysiological mechanisms underlying the phenomenon.

Aim

A cross-sectional study was conducted on HM meditators and nonmeditators to assess frontal electrical activities of the brain and self-reported anxiety and mindfulness.

Settings and Design

The present study employed a cross-sectional design.

Methods

Sixty-one participants were recruited, 28 heartfulness meditators (average age male: 31.54 ± 4.2 years and female: 30.04 ± 7.1 years) and 33 nonmeditators (average age male: 25 ± 8.5 years and female: 23.45 ± 6.5 years). An electroencephalogram (EEG) was employed to assess brain activity during baseline (5 min), meditation (10 min), transmission (10 min) and post (5 min). Self-reported mindfulness and anxiety were also collected in the present study. The EEG power spectral density (PSD) and coherence were processed using MATLAB. The statistical analysis was performed using an independent sample t-test for trait mindfulness and anxiety, repeated measures analysis of variance (ANOVA) for state mindfulness and anxiety, and Two-way multivariate ANOVA for EEG spectral frequency and coherence.

Results

The results showed higher state and trait mindfulness, P < 0.05 and P < 0.01, respectively, and lower state and trait anxiety, P < 0.05 and P < 0.05, respectively. The PSD outcomes showed higher theta (P < 0.001) and alpha (P < 0.01); lower beta (P < 0.001) and delta (P < 0.05) power in HM meditators compared to nonmeditators. Similarly, higher coherence was found in the theta (P < 0.01), alpha (P < 0.05), and beta (P < 0.01) bands in HM meditators.

Conclusions

These findings suggest that HM practice may result in wakeful relaxation and internalized attention that can influence cognition and behavior.

Detrending Moving Average, Power Spectral Density, and Coherence: Three EEG-Based Methods to Assess Emotion Irradiation during Facial Perception

Understanding brain reactions to facial expressions can help in explaining emotion-processing and memory mechanisms. The purpose of this research is to examine the dynamics of electrical brain activity caused by visual emotional stimuli. The focus is on detecting changes in cognitive mechanisms produced by negative, positive, and neutral expressions on human faces. Three methods were used to study brain reactions: power spectral density, detrending moving average (DMA), and coherence analysis. Using electroencephalogram (EEG) recordings from 48 subjects while presenting facial image stimuli from the International Affective Picture System, the topographic representation of the evoked responses was acquired and evaluated to disclose the specific EEG-based activity patterns in the cortex. The theta and beta systems are two key cognitive systems of the brain that are activated differently on the basis of gender. The obtained results also demonstrate that the DMA method can provide information about the cortical networks’ functioning stability, so it can be coupled with more prevalent methods of EEG analysis.

Alpha Oscillations in Parietal and Parietooccipital Explaining How Boredom Matters Prospective Memory

Intelligent interaction alters previous human–machine task allocation patterns. Human workers will suffer from boredom and inattention, posing a significant challenge for the human–machine interaction loop. This study aims to investigate the relationship between boredom and prospective memory, which is a memory form including the detecting, identifying, and executing functions. Thus, the attention and memory mechanisms are critical to complete prospective memory tasks when bored. This study recruited twenty-eight participants and used electroencephalography to measure the alpha power in brain regions. The results indicated that parietal oscillations had a mediation effect on prospective memory, which could be associated with the frequent unstable attention. In addition, this study found that parietooccipital oscillations linked boredom and prospective memory, and the default mode network (DMN) and visual processing during boredom could better explain this finding. The findings of this study suggested that attention management and influences of processing visual information were starting points to cope with boredom because they could help prepare for prospective memory and make optimal decisions accordingly.

EEG Pattern Classification of Picking and Coordination Using Anonymous Random Walks

Tacit coordination games are games where players are trying to select the same solution without any communication between them. Various theories have attempted to predict behavior in tacit coordination games. Until now, research combining tacit coordination games with electrophysiological measures was mainly based on spectral analysis. In contrast, EEG coherence enables the examination of functional and morphological connections between brain regions. Hence, we aimed to differentiate between different cognitive conditions using coherence patterns. Specifically, we have designed a method that predicts the class label of coherence graph patterns extracted out of multi-channel EEG epochs taken from three conditions: a no-task condition and two cognitive tasks, picking and coordination. The classification process was based on a coherence graph extracted out of the EEG record. To assign each graph into its appropriate label, we have constructed a hierarchical classifier. First, we have distinguished between the resting-state condition and the other two cognitive tasks by using a bag of node degrees. Next, to distinguish between the two cognitive tasks, we have implemented an anonymous random walk. Our classification model achieved a total accuracy value of 96.55%.

Functional (un-)Coupling: Impairment, Compensation, and Future Progression in Alzheimer's Disease

Background: Functional (un-)coupling (task-related change of functional connectivity) between different sites of the brain is a mechanism of general importance for cognitive processes. In Alzheimer's disease (AD), prior research identified diminished cortical connectivity as a hallmark of the disease. However, little is known about the relation between the amount of functional (un-)coupling and cognitive performance and decline in AD. Method: Cognitive performance (based on CERAD-Plus scores) and electroencephalogram (EEG)-based functional (un-)coupling measures (connectivity changes from rest to a Face-Name-Encoding task) were assessed in 135 AD patients (age: M = 73.8 years; SD = 9.0). Of these, 68 patients (M = 73.9 years; SD = 8.9) participated in a follow-up assessment of their cognitive performance 1.5 years later. Results: The amounts of functional (un-)coupling in left anterior-posterior and homotopic interhemispheric connections in beta1-band were related to cognitive performance at baseline (β = .340; p < .001; β = .274; P = .001, respectively). For both markers, a higher amount of functional coupling was associated with better cognitive performance. Both markers also were significant predictors for cognitive decline. However, while patients with greater functional coupling in left anterior-posterior connections declined less in cognitive performance (β = .329; P = .035) those with greater functional coupling in interhemispheric connections declined more (β = -.402; P = .010). Conclusion: These findings suggest an important role of functional coupling mechanisms in left anterior-posterior and interhemispheric connections in AD. Especially the complex relationship with cognitive decline in AD patients might be an interesting aspect for future studies.

Drinking coffee enhances neurocognitive function by reorganizing brain functional connectivity

The purpose of this study was to identify the mechanisms underlying effects of coffee on cognition in the context of brain networks. Here we investigated functional connectivity before and after drinking coffee using graph-theoretic analysis of electroencephalography (EEG). Twenty-one healthy adults voluntarily participated in this study. The resting-state EEG data and results of neuropsychological tests were consecutively acquired before and 30 min after coffee consumption. Graph analyses were performed and compared before and after coffee consumption. Correlation analyses were conducted to assess the relationship between changes in graph measures and those in cognitive function tests. Functional connectivity (FC) was reorganized toward more efficient network properties after coffee consumption. Performance in Digit Span tests and Trail Making Test Part B improved after coffee consumption, and the improved performance in executive function was correlated with changes in graph measures, reflecting a shift toward efficient network properties. The beneficial effects of coffee on cognitive function might be attributed to the reorganization of FC toward more efficient network properties. Based on our findings, the patterns of network reorganization could be used as quantitative markers to elucidate the mechanisms underlying the beneficial effects of coffee on cognition, especially executive function.

The Implications of Motor and Cognitive Inhibition for Hot and Cool Executive Functions: The Case of Quadrato Motor Training

Enabling the ceasing of ongoing or prepotent responses and the controlling of interference, motor inhibition facilitates the development of executive functions (EFs) such as thought before action, decision-making, self-regulation of affect, motivation, and arousal. In the current paper, a characterization is offered of the relationship between motor inhibition and the executive functioning system, in the context of a proposed division into predominantly affective (hot) and cognitive (cool) components corresponding to neural trajectories originating in the prefrontal cortex. This division is central to understanding the effects of a specifically-structured sensorimotor movement training practice, known as Quadrato Motor Training (QMT), on hot and cool EFs. QMT's effects on crucial mechanisms of integrating different EF components are discussed.