Paradox lost? Exploring the role of alpha oscillations during externally vs. internally directed attention and the implications for idling and inhibition hypotheses

A Review on the Cognitive Neural Mechanisms of Anaphor Processing During Language Comprehension

Anaphora is an essential means of maintaining textual coherence, the phenomenon of replacing one word or phrase in the preceding part of a discourse with another. At least two crucial stages are involved in anaphor processing: bonding and resolution. The links between the anaphor and potential antecedents are established in the former stage, which would be evaluated and integrated into the latter stage. We reviewed relevant event-related potential (ERP) studies that examined the time course of anaphor processing and neural oscillation studies that explored energy changes in alpha, theta, and gamma frequency bands, which were associated with attention, working memory retrieval, and integration, respectively. The existing neuroimaging studies revealed the involvement of language processing networks and the Theory of Mind (ToM). Further research should explore the neural correlates and the effects of potential factors on anaphor processing, which could help gain a more comprehensive picture from multiple perspectives.

Seeing things in psychosis: Reduced theta power in early neural responses to ambiguous visual stimuli predicts perceptual distortions

OBJECTIVE

In this study we aimed to identify possible neural origins of perceptual disturbances in psychotic disorders.

METHODS

Individuals with schizophrenia and bipolar disorder with psychosis (n = 40), their biological siblings (n = 17), and healthy controls (n = 27) viewed ambiguous object stimuli equivalent in primary visual cortical processing demands, allowing for identification of neural abnormalities occurring beyond basic sensory processing. Magnetoencephalography was collected and neural oscillations were quantified using time-frequency analysis.

RESULTS

Individuals with schizophrenia showed reduced early theta responses over occipital cortex and diminished late desynchronization of alpha/beta in select conditions over parietal cortex. Reduced theta was associated with more schizotypal traits and self-reported perceptual anomalies. Less alpha/beta desynchronization was marginally associated with greater negative symptoms.

CONCLUSIONS

Visual cortical anomalies in schizophrenia beyond primary visual cortex are reflected in reduced early occipital theta oscillations. This impaired bottom-up sensory processing is related to everyday perceptual abnormalities. Diminished later alpha/beta desynchronization in schizophrenia may reflect difficulty disengaging from default mode to access top-down mechanisms that facilitate perception.

SIGNIFICANCE

Early sensory signals, communicated through theta-band oscillations, and later semantic processing, engaged through the desynchronization of alpha/beta oscillations, contribute to ambiguous object detection as well as perceptual disturbances in schizophrenia.

Probing Neurophysiological Processes Related to Self-Referential Processing to Predict Improvement in Adolescents With Depression Receiving Cognitive Behavioral Therapy

BACKGROUND

Cognitive behavioral therapy (CBT) is a gold-standard approach for treating major depressive disorder in adolescents. However, nearly half of adolescents receiving CBT do not improve. To personalize treatment, it is essential to identify objective markers that predict treatment responsiveness. To address this aim, we investigated neurophysiological processes related to self-referential processing that predicted CBT response among female adolescents with depression.

METHODS

At baseline, female adolescents ages 13 to 18 years (N = 80) completed a comprehensive clinical assessment, and a self-referential encoding task was administered while electroencephalographic data were recorded. Baseline electroencephalographic data were utilized to identify oscillatory differences between healthy adolescents (n = 42) and adolescents with depression (n = 38). Following the baseline assessment, adolescents with depression received up to 12 weeks of CBT. Baseline differences in electroencephalographic oscillations between healthy adolescents and those with depression were used to guide CBT prediction analysis. Cluster-based event-related spectral perturbation analysis was used to probe theta and alpha event-related synchronization (ERS)/event-related desynchronization (ERD) response to negative and positive words.

RESULTS

Baseline analyses showed that, relative to the healthy adolescents, adolescents with depression exhibited higher levels of frontal theta ERS and greater posterior alpha ERD. Multilevel modeling identified primary neural pretreatment predictors of treatment response: greater theta ERS in the right prefrontal cortex after the onset of negative words and lower alpha ERD in both the right prefrontal cortex and posterior cingulate cortex. ERS and ERD associations with treatment response remained significant, with baseline depressive and anxiety symptoms included as covariates in all analyses.

CONCLUSIONS

Consistent with prior research, results highlighted that relative to healthy adolescents, adolescents with depression are characterized by prominent theta synchronization and alpha desynchronization over the prefrontal cortex and posterior cingulate cortex, respectively. Cluster-based event-related spectral perturbation analysis also identified key mechanisms underlying depression-related self-referential processing that predicted improved symptoms during the course of CBT. Ultimately, a better characterization of the neural underpinnings of adolescent depression and its treatment may lead to more personalized interventions.

EEG alpha power during creative ideation of graphic symbols

Graphic symbolic creation-transforming abstract concepts into visual forms-is a cognitively complex and uniquely human skill. Neurophysiological evidence suggests that oscillatory alpha activity is correlated with visual-figurative creative thinking. However, whether alpha oscillations play a functional role in generating graphic symbols remains unclear. To address this issue, we compared the EEG alpha power of 40 healthy adults while ideating creative and conventional graphic symbols representing an abstract concept's meaning (e.g., the word 'peace'). Our results revealed that the ideation of graphic symbols elicited alpha synchronization, with higher levels in the conventional compared to the creative condition, mainly over frontal-central, frontal-temporal, parietal-occipital, and occipital regions. Furthermore, we observed greater alpha synchronization in the right hemisphere than in the left across both conditions, particularly between temporal, central-parietal, and parietal electrodes. This asymmetry extended to central electrodes in the creative condition, while in the conventional condition, it was more pronounced over parietal-occipital regions. Finally, we also found that frontal and occipital alpha synchronization during the creative ideation phase predicted the subsequent originality scores of the graphic symbols produced. Together, these findings enhance our understanding of the dynamics of oscillatory alpha activity during graphic symbol creation, shedding light on how the interaction between inhibitory top-down control mechanisms and cognitive flexibility processes facilitates the transformation of abstract concepts into visual forms. These findings provide new insights into the neural processes underlying this uniquely human ability.

Neural activity is modulated by spontaneous and volitionally controlled breathing

Recent studies have provided evidence regarding respiration-brain coupling, but our understanding of how continuously varying dynamics of breathing modulate neural activity remains incomplete. We examined whether the neural state differs between spontaneous and volitionally controlled breathing and across the phases of breathing, inspiration and expiration. Magnetoencephalography (MEG) with a respiratory belt was used to record cortical oscillatory activity during spontaneous, deep, and square breathing (n = 33). Additionally, self-report measures of mood and arousal were applied to assess changes in the psychological state during the breathing techniques. Alpha power was suppressed during inspiration and increased during expiration (p < .01) indicating dynamically fluctuating neural states across the respiratory cycle. This effect was observed in the sensorimotor areas during both spontaneous and volitionally controlled deep breathing. Compared to spontaneous and volitionally controlled square breathing, alpha power increased during deep breathing (p < .01) within a cortical network extending to frontal and temporal areas. We also observed a steeper aperiodic slope and a broadband shift in the power spectrum in the left superior frontal gyrus during square breathing in comparison with spontaneous breathing suggesting that not only oscillatory activity but also the more general spectral characteristics of ongoing neural activity are modulated by the rate, depth, and pattern of breathing. Self-reported mood and arousal did not differ across the breathing techniques. Altogether, we demonstrate that neural activity is modulated by the phases of breathing and can also be volitionally influenced by varying the rate, depth, and pattern of breathing.

Electrophysiological signature of interoceptive attention: a spectral and source localization analysis

The ability to attend to and consciously process interoceptive signals is deemed critical for the development of minimal self, adaptive self-regulation and affective experience, and optimal expression of both instrumental and executive cognitive functions. Yet, notwithstanding the richness of theoretical proposals concerning inferential accounts of interoception, empirical evidence is still scarce. Building on such premises, this study was designed to investigate the electrophysiological signature of cognitive processes leading to aware coding of interoceptive signals via EEG source localization. Thirty-six healthy participants completed an interoceptive accuracy task, i.e., the Heartbeat Counting Task (HCT), while we collected task-related and resting state electrophysiological activity. eLORETA modelling and statistical nonparametric mapping were used to estimate intracortical current density and link such estimates to participants' performance at the task. Source analysis highlighted higher current density estimates for alpha frequencies during HCT with respect to rest, with the primary cortical generator in the right parahippocampal gyrus. Also, a set of medial cortical structures-primarily represented by the cingulate gyrus-showed significant relation between task-related changes in current density estimates for beta oscillations and HCT scores. Findings suggest the informativity of EEG task-related measures of neural activation when used to assess interoceptive skills, as well as of the potential of metrics and analysis based on source localization in the quest to improve our understanding of interoceptive accuracy and neurofunctional correlates of related active inferences.

Origins and consequences of cognitive fatigue

Everybody knows intuitively what mental fatigue is. However, we poorly understand why fatigue emerges with time spent on demanding cognitive work and how such 'cognitive fatigue' impacts neural processing and behavioral guidance. Here, we review experimental investigations that induced cognitive fatigue and recorded its potential markers, including self-report, behavioral performance, economic choice, physiological and neural activity. We then review theoretical models of cognitive fatigue, classically divided into biological and motivational accounts. To explain key observations and reconcile debated theories, we finally propose a conceptual model (dubbed MetaMotiF), in which cognitive fatigue would emerge for biological reasons and yet affect motivational processes that regulate the behavior. More precisely, fatigue would arise from metabolic alterations in cognitive control brain regions, following their excessive mobilization. In turn, these metabolic alterations would increase the cost of cognitive control, which would shift decisions towards actions that require little effort and yield immediate rewards.

Can guilt enhance sensitivity to other's suffering? An EEG investigation into moral emotions and pain empathy

As a unique form of empathy, pain empathy often has a close relationship with society and morality. Research has revealed that moral emotions can influence pain empathy. The underlying physiological mechanism still needs to be further examined to understand how moral emotions affect pain empathy. This study employs EEG and Machine Learning techniques, using a painful image induction paradigm to explore the impact of moral emotion (guilt)-on pain empathy and its neural mechanisms. Participants without pain sensation were instructed to observe and evaluate pictures of an anonymous hand in painful or non-painful pictures under feelings of guilt or neutral emotion. Results found slower reaction times and higher pain ratings for painful pictures. Furthermore, guilt led to higher pain ratings. Under conditions of painful pictures, guilt-induced greater P3(350-450ms) amplitudes and higher α oscillations and enhanced the functional connectivity between the prefrontal cortex, the central frontal region, and the parieto-occipital lobe. K-nearest neighbor can effectively classify high and low-pain empathy under guilt emotion. The result showed that guilt promotes the brain's processing of painful picture, causing individuals to pay high attention and engage in deep cognitive processing. This study provides insights into enhancing empathy and fostering interpersonal relationships.

Takeover and non-driving related task performance in conditional automated driving: EEG and behavior Parameters interaction

In this study, a conditional automated driving scenario is simulated using virtual reality (VR) technology to explore whether office works presented through augmented reality (AR) affect task and takeover performance, and the neural mechanism was revealed. Sixty-four participants were recruited and their electroencephalography (EEG) was used to measure the brain activities. The results indicated that non-driving-related tasks (NDRTs) requiring higher internal attention focus resulted in poorer task and takeover performance. The alpha power decline magnitude in the parietotemporal (PT) was positively correlated with the takeover time; and the greater the alpha power decline in the right centroparietal (CP) hemisphere, the worse is the participants' memory quality for NDRTs. The ventral attention network (VAN) and right parietal cortex, which are active during working memory, are more likely to explain these findings. The results can provide suggestions for the design of AR-ADS and help improve the safety in L3 driving automation systems.

Precision data-driven modeling of cortical dynamics reveals person-specific mechanisms underpinning brain electrophysiology

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and has been used to identify neural markers of individual differences. In this work, we present an algorithmic optimization framework that directly inverts and parameterizes brain-wide dynamical-systems models involving hundreds of interacting neural populations, from single-subject M/EEG time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG metrics. Last, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitatory-inhibitory balance, highlighting the explanatory power of our framework to generate mechanistic insights.

Electroencephalographic markers in Major Depressive Disorder: insights from absolute, relative power, and asymmetry analyses

Introduction

Major Depressive Disorder (MDD) leads to dysfunction and impairment in neurological structures and cognitive functions. Despite extensive research, the pathophysiological mechanisms and effects of MDD on the brain remain unclear. This study aims to assess the impact of MDD on brain activity using EEG power spectral analysis and asymmetry metrics.

Methods

EEG recordings were obtained from 48 patients with MDD and 78 healthy controls. The data were segmented into 2-second windows (1024 data points) and analyzed using the Welch method, an advanced variant of the Fast Fourier Transform (FFT). A Hanning time window with 50% overlap was applied to compute the modified periodogram. Absolute and relative power, along with asymmetry values in the theta, alpha, and beta frequency bands, were calculated.

Results

Patients with MDD exhibited significantly higher absolute and relative power in the theta and beta bands and decreased power in the alpha band compared to healthy controls. Asymmetry analysis revealed significant differences between symmetric channels in the theta band (F7-F8, C3-C4, T3-T4, T5-T6), alpha band (F7-F8, C3-C4, T3-T4, T5-T6, O1-O2), and beta band (C3-C4, T3-T4, T5-T6, P3-P4).

Discussion

The findings suggest that MDD affects brain mechanisms and cognitive functions, as evidenced by altered power values in the theta and alpha bands. Additionally, asymmetry values in theta, alpha, and beta bands may serve as potential biomarkers for MDD. This study highlights that beyond the commonly used alpha asymmetry, theta and beta asymmetry can also provide valuable insights into the neurophysiological effects of MDD, aligning with previous neuroimaging studies that indicate impairments in memory, attention, and neuroanatomical connectivity in MDD.

Motor imagery perspective and brain oscillations characteristics: Differences between right- and left-handers

Motor imagery (MI) encompasses kinesthetic motor imagery (KMI), internal visual-motor motor imagery (IVMI), and external visual-motor motor imagery (EVMI). This study explored α/β oscillations during MI of left-/right-hand movement from KMI/IVMI/EVMI perspectives in a group of left- (N = 20) and right-handed (N = 20), volunteers selected based on their laterality quotient (RH > 80; LH > -80). We analyzed changes in the power of α/β oscillations from visual- and motor-related clusters of independent components, connectivity (imaginary part of coherence; ICOH) between electroencephalographic activity from selected regions of interest (ROIs), and the correctness of the MI. The left-handed individuals showed more robust α/β activity in visual-related ROI during EVMI for their non-dominant hand, compared during IVMI. However, they did not show a difference in brain activity for EVMI/IVMI compared with KMI and connectivity variance across EVMI/IVMI and KMI. The right-handed individuals exhibited visual area suppression during KMI, which could signify focusing on internal sensations and blocking visual processing in this condition. ICOH connectivity in the RH group varied depending on the task and hand involved, with more robust connections for EVMI of the non-dominant hand compared with IVMI and stronger connections for EVMI and KMI of the non-dominant hand compared with the dominant hand. The results suggest that left-handed individuals rely more on visual representations during MI, especially for their non-dominant hand. At the same time, right-handed people may create more multimodal images during the same tasks.

Strength of Low-Frequency EEG Phase Entrainment to External Stimuli Is Associated with Fluctuations in the Brain's Internal State

The brain attends to environmental rhythms by aligning the phase of internal oscillations. However, the factors underlying fluctuations in the strength of this phase entrainment remain largely unknown. In the present study, we examined whether the strength of low-frequency electroencephalography (EEG) phase entrainment to rhythmic stimulus sequences varied with the pupil size and posterior alpha-band power, thought to reflect the arousal level and excitability of posterior cortical brain areas, respectively. We recorded the pupil size and scalp EEG while participants carried out an intermodal selective attention task, in which they were instructed to attend to a rhythmic sequence of visual or auditory stimuli and ignore the other perceptual modality. As expected, intertrial phase coherence (ITC), a measure of entrainment strength, was larger for the task-relevant than for the task-irrelevant modality. Across the experiment, the pupil size and posterior alpha power were strongly linked with each other. Interestingly, ITC tracked both variables: larger pupil size was associated with a selective increase in entrainment to the task-relevant stimulus sequence, whereas larger posterior alpha power was associated with a decrease in phase entrainment to both the task-relevant and task-irrelevant stimulus sequences. Exploratory analyses showed that a temporal relation between ITC and posterior alpha power emerged in the time periods around pupil maxima and pupil minima. These results indicate that endogenous sources contribute distinctly to the fluctuations of EEG phase entrainment.

Comorbidity of concussion and depression alters brain functional connectivity in collegiate student-athletes

Depression and concussion are highly prevalent neuropsychological disorders that often occur simultaneously. However, due to the high degree of symptom overlap between the two events, including but not limited to headache, sleep disturbances, appetite changes, fatigue, and difficulty concentrating, they may be treated in isolation. Thus, clinical awareness of additive symptom load may be missed. This study measures neuropsychological and electroencephalography (EEG) alpha band coherence differences in collegiate student-athletes with history of comorbid depression and concussion, in comparison to those with a single morbidity and healthy controls (HC). 35 collegiate athletes completed neuropsychological screenings and EEG measures. Participants were grouped by concussion and depression history. Differences in alpha band coherence were calculated using two-way ANOVA with post hoc correction for multiple comparisons. Comorbid participants scored significantly worse on neuropsychological screening, BDI-FS, and PCSS than those with a single morbidity and HC. Two-way ANOVA by group revealed significant main effects of alpha band coherence for concussion, depression, and their interaction term. Post-hoc analysis showed that comorbid participants had more abnormal alpha band coherence than single morbidity, when compared to HC. Comorbidity of concussion and depression increased symptom reporting and revealed more altered alpha band coherence than single morbidity, compared to HC. The abnormalities of the comorbid group exclusively showed decreased alpha band coherence in comparison to healthy controls. The comorbidity of depression and SRC has a compounding effect on depression symptoms, post-concussion symptoms, and brain functional connectivity. This research demonstrates a promising objective measure in comorbid individuals, previously only measured via subjective symptom reporting.

Neurological Evidence of Diverse Self-Help Breathing Training With Virtual Reality and Biofeedback Assistance: Extensive Exploration Study of Electroencephalography Markers

BACKGROUND

Recent advancements in virtual reality (VR) and biofeedback (BF) technologies have opened new avenues for breathing training. Breathing training has been suggested as an effective means for mental disorders, but it is difficult to master the technique at the beginning. VR-BF technologies address the problem of breathing, and visualizing breathing may facilitate the learning of breathing training. This study explores the integration of VR and BF to enhance user engagement in self-help breathing training, which is a multifaceted approach encompassing mindful breathing, guided breathing, and breath counting techniques.

OBJECTIVE

We identified 3 common breathing training techniques in previous studies, namely mindful breathing, guided breathing, and breath counting. Despite the availability of diverse breathing training methods, their varying effectiveness and underlying neurological mechanisms remain insufficiently understood. We investigated using electroencephalography (EEG) indices across multiple breathing training modalities to address this gap.

METHODS

Our automated VR-based breathing training environment incorporated real-time EEG, heart rate, and breath signal BF. We examined 4 distinct breathing training conditions (resting, mindful breathing, guided breathing, and breath counting) in a cross-sectional experiment involving 51 healthy young adults, who were recruited through online forum advertisements and billboard posters. In an experimental session, participants practiced resting state and each breathing training technique for 6 minutes. We then compared the neurological differences across the 4 conditions in terms of EEG band power and EEG effective connectivity outflow and inflow with repeated measures ANOVA and paired t tests.

RESULTS

The analyses included the data of 51 participants. Notably, EEG band power across the theta, alpha, low-beta, high-beta, and gamma bands varied significantly over the entire scalp (t ≥1.96, P values <.05). Outflow analysis identified condition-specific variations in the delta, alpha, and gamma bands (P values <.05), while inflow analysis revealed significant differences across all frequency bands (P values <.05). Connectivity flow analysis highlighted the predominant influence of the right frontal, central, and parietal brain regions in the neurological mechanisms underlying the breathing training techniques.

CONCLUSIONS

This study provides neurological evidence supporting the effectiveness of self-help breathing training through the combined use of VR and BF technologies. Our findings suggest the involvement of internal-external attention focus and the dorsal attention network in different breathing training conditions. There is a huge potential for the use of breathing training with VR-BF techniques in terms of clinical settings, the new living style since COVID-19, and the commercial value of introducing VR-BF breathing training into consumer-level digital products. Furthermore, we propose avenues for future research with an emphasis on the exploration of applications and the gamification potential in combined VR and BF breathing training.

TRIAL REGISTRATION

ClinicalTrials.gov NCT06656741; https://clinicaltrials.gov/study/NCT06656741.

Socioeconomic status (SES) and cognitive outcomes are predicted by resting-state EEG in school-aged children

Children's socioeconomic status (SES) is related to patterns of intrinsic resting-state brain function that subserve relevant cognitive processes over the course of development. Although infant research has demonstrated the association between children's environments, cognitive outcomes, and resting-state electroencephalography (rsEEG), it remains unknown how these aspects of their environment, tied to SES, impact neural and cognitive development throughout the school years. To address this gap, we applied a multivariate pattern analysis (MVPA) to rsEEG data to identify which neural frequencies at rest are differentially associated with unique aspects of socioeconomic status (SES; income and maternal education) and cognitive (vocabulary, working memory) outcomes among school-aged children (8-15 years). We find that the alpha frequency is associated with both income and maternal education, while lower gamma and theta fluctuations are tied to dissociable aspects of SES and cognitive outcomes. Specifically, changes in the gamma frequency are predictive of both maternal education and vocabulary outcome, while changes in the theta frequency are related to both income and working memory ability. The current findings extend our understanding of unique pathways by which SES influences cognitive and neural development in school-aged children.

Mindfulness meditation is associated with global EEG spectral changes in theta, alpha, and beta amplitudes

Mindfulness meditation is linked to a broad range of psychological and physical health benefits, potentially mediated by changes in neural oscillations. This study explored changes in neural oscillations associated with both immediate and regular mindfulness meditation practice. Electroencephalographic (EEG) data were collected from 40 healthy young adults (Mage = 20.8, 24 females) during eyes-closed resting and mindfulness meditation states in two separate recording sessions, six weeks apart. Participants were novice meditators, and following the first recording session, were randomly assigned to either a daily mindfulness meditation practice or classical music listening as an active control, which they completed until the second recording session. Traditional bands of delta (1.0-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), beta (13.5-30.0 Hz), and gamma (30.5-45.0 Hz) were used to explore changes in global EEG spectral amplitude. A significant increase in theta between sessions was observed in both groups and states. Alpha decreased significantly during meditation compared with rest, and a three-way interaction indicated a smaller reduction during meditation between sessions in the mindfulness group. There was a similar interaction in beta, which remained stable between sessions during both rest and meditation in the mindfulness group while varying in the classical music listening group. No significant effects were observed in global delta or gamma amplitudes. These findings suggest that changes in neural oscillations associated with breath-focused mindfulness meditation may be related to processes underlying attention and awareness. Further research is necessary to consolidate these findings, particularly in relation to the associated health benefits.

Predicting attentional focus: Heartbeat-evoked responses and brain dynamics during interoceptive and exteroceptive processing

Attention shapes our consciousness content and perception by increasing the probability of becoming aware and/or better encoding a selection of the incoming inner or outer sensory world. Engaging interoceptive and exteroceptive attention should elicit distinctive neural responses to visceral and external stimuli and could be useful in detecting covert command-following in unresponsive patients. We designed a task to engage healthy participants' attention toward their heartbeats or auditory stimuli and investigated whether brain dynamics and the heartbeat-evoked potential (HEP) distinguished covert interoceptive-exteroceptive attention. Exteroceptive attention yielded an overall flattening of the power spectral density (PSD), whereas during interoception, there was a decrease in complexity, an increase in frontal connectivity and theta oscillations, and a modulation of the HEP. Subject-level classifiers based on HEP features classified the attentional state of 17/20 participants. Kolmogorov complexity, permutation entropy, and weighted symbolic mutual information showed comparable accuracy in classifying covert attention and exhibited a synergic behavior with the HEP features. PSD features demonstrated exceptional performance (20/20). Command-following was assessed in five brain-injured patients with a modified version of the task. An unresponsive wakefulness syndrome/vegetative state patient and a locked-in syndrome patient demonstrated a willful modulation of the HEP and together with the explored brain markers suggest that patients were complying with task instructions. Our findings underscore the importance of attentional mechanisms in shaping interoceptive and exteroceptive sensory processing and expand the framework of heart-brain interactions employed for diagnostic purposes in patients with disorders of consciousness.

Mindfulness meditation alters neural oscillations independently of arousal

Neuroscience has identified that mindfulness meditation induces a state of relaxed alertness, characterised by changes in theta and alpha oscillations and reduced sympathetic arousal, although the underlying mechanisms remain unclear. This study aims to address this gap by examining changes in neural oscillations and arousal during mindfulness meditation using both traditional and data-driven methods. Fifty-two healthy young adults underwent electroencephalography (EEG) and skin conductance level (SCL) recordings during resting baseline and mindfulness meditation conditions, both conducted with eyes closed. The EEG data revealed a significant decrease in traditional alpha (8-13 Hz) amplitude during mindfulness meditation compared to rest. However, no significant differences were observed between conditions in traditional delta, theta, beta, or gamma amplitudes. Frequency Principal Components Analysis (fPCA) was employed as a data-driven approach, identifying six components consistent across conditions. A complex delta-theta-alpha component significantly increased during mindfulness meditation. In contrast, low alpha (~9.5 Hz) and low alpha-beta (~11 Hz) components decreased significantly during mindfulness meditation. No significant differences were observed between conditions in the delta, high alpha, and high alpha-beta components. Additionally, there were no significant differences in SCL between conditions, nor were there correlations between traditional alpha or fPCA components and SCL. These findings support the conceptualisation of mindfulness meditation as a state of relaxed alertness, characterised by changes in neural oscillations likely associated with attention and awareness. However, the observed changes do not appear to be driven by arousal.

Aberrant connectivity of the lateralized readiness system in non-syndromic congenital mirror movements

OBJECTIVES

Non-syndromic CMM has a complex phenotype. Abnormal corpus callosum and corticospinal tract processes are suggested mechanisms of the mirror movements. To further explore behavioural and neural phenotype(s) the present study tests the hypothesis that the response readiness network comprising supplementary motor area (SMA) and connections with motor cortex (M1) functions abnormally in CMM.

METHODS

Twelve participants with (non-syndromic) CMM and a control group (n = 28) were tested on a probabilistic Go-NoGo task while electroencephalography (EEG) was recorded to assess possible group differences in lateralized readiness of voluntary hand movements together with measures of SMA-M1 functional connectivity.

RESULTS

The CMM group demonstrated delayed lateralized readiness and stronger functional connectivity between left-brain SMA-M1 regions. Connectivity strength was correlated with measures of behavioural performance but not with extent of mirroring.

CONCLUSIONS

Abnormalities in brain processes upstream of movement output likely reflect neurocompensation as a result of lifelong experience with mirroring in CMM.

SIGNIFICANCE

These findings extend the known neural abnormalities in CMM to include brain networks upstream from those involved in motor output and raise the question of whether neurocompensatory plasticity might be involved.

Resting-State Alpha Activity in the Frontal and Occipital Lobes and Assessment of Cognitive Impairment in Depression Patients

Background

Major depressive disorder (MDD) becomes one of the psychiatric disorders characteristic of a combination of cognitive, emotional, and somatic symptoms. Additionally, cognitive impairment has the most significant impact on functional results. However, the evaluation of cognitive level is still based on various subjective questionnaires as there is no objective standard assessment yet. This research focuses on resting-state alpha activity to identify cognition in MDD patients using electroencephalography (EEG) signals.

Methods

Ninety-two subjects were recruited: 44 patients with MDD and 48 healthy individuals as controls. Functional outcome and cognition were assessed using standardized instruments, and the EEG resting state signal of open and closed eyes was recorded. The comparison and correlation of cognitive levels with alpha power in the bilateral frontal region, bilateral central region, bilateral occipital region, and middle line was evaluated.

Results

The relative alpha power in MDD group was significantly lower than that in the control group (P < 0.05). Through correlation analysis, it was shown that the bilateral frontal and occipital alpha power of MDD patients in the closed-eyes state was positively correlated with information processing rate, verbal learning, working memory, and attention retention. The alpha power of the bilateral frontal region in the open-eyes state was positively correlated with information processing rate, working memory, and attention retention (P < 0.05).

Conclusion

The research indicates that the changes in frontal and occipital alpha activities may be a promising neurophysiological indicator of cognitive level to diagnose and treat response prediction.

Wavelet Coherence Analysis of Post-Stroke Intermuscular Coupling Modulated by Myoelectric-Controlled Interfaces

Intermuscular coupling reflects the corticospinal interaction associated with the control of muscles. Nevertheless, the deterioration of intermuscular coupling caused by stroke has not received much attention. The purpose of this study was to investigate the effect of myoelectric-controlled interface (MCI) dimensionality on the intermuscular coupling after stroke. In total, ten age-matched controls and eight stroke patients were recruited and executed elbow tracking tasks within 1D or 2D MCI. Movement performance was quantified using the root mean square error (RMSE). Wavelet coherence was used to analyze the intermuscular coupling in alpha band (8-12 Hz) and beta band (15-35 Hz). The results found that smaller RMSE of antagonist muscles was observed in both groups within 2D MCI compared to 1D MCI. The alpha-band wavelet coherence was significantly lower in the patients compared to the controls during elbow extension. Furthermore, a decreased alpha-band and beta-band wavelet coherence was observed in the controls and stroke patients, as the dimensionality of MCI increased. These results may suggest that stroke-related neural impairments deteriorate the motor performance and intermuscular coordination pattern, and, further, that MCI holds promise as a novel effective tool for rehabilitation through the direct modulation of muscle activation pattern.

Exploring the Relationship Between Imitated and Associated Mechanism on Performance of Visual Imagery Brain-Computer Interface

Visual Imagery (VI) can be defined as the manipulation of visual information derived from memory rather than perception. Currently, the brain responses underlying imitation and associative VI are not clear. In this study, we explore the differences from imitation to associative VI on the brain responses based on EEG signals. In this study, eight participants were instructed to observe visual cues from three predefined images or characters (tree, computer, or sphere), and then imagine the same cues. The results indicate that there is a significant difference in power intensity among electrode channels in the occipital lobe, posterior parietal lobe, and temporal lobe during the imagination phase between imitative tasks and associative tasks, as revealed by t-tests (p < 0.05, rejecting the null hypothesis). Overall, imitation mechanisms and associative mechanisms represent the short-term memory (STM) and long-term memory (LTM) features of objects. This study addresses a crucial research gap in VI, as there is currently a scarcity of formal simultaneous comparisons in the existing literature.

Selective cortical adaptations associated with neural efficiency in visuospatial tasks - the comparison of electroencephalographic profiles of expert and novice artists

Visuospatial cognition encapsulates an individual's ability to efficiently navigate and make sense of the multimodal cues from their surroundings, and therefore has been linked to expert performance across multiple domains, including sports, performing arts, and highly skilled tasks, such as drawing (Morrone and Minini, 2023). As neural efficiency posits a task-specific functional reorganization facilitated by long-term training, the present study employs a visuospatial construction task as a means of investigating the neurophysiological adaptations associated with expert visuospatial cognitive performance. Electroencephalogram (EEG) data acquisitions were used to evaluate the event-related changes (ER%) and statistical topographic maps of nine expert versus nine novice artists. The expert artists displayed overall higher global ER% compared to the novices within task-active intervals. Significant increases in relative ER% were found in the theta (t (10) = 3.528, p = 0.003, CI = [27.3,120.9]), lower-alpha (t (10) = 3.751, p = 0.002, CI = [28.2,110.5]), upper-alpha (t (10) = 3.829, p = 0.002, CI = [50.2,189.8]), and low beta (t (10) = 4.342, p < 0.001, CI = [37.0,114.9]) frequency bands, when comparing the experts to the novice participants. These results were particularly found in the frontal (t (14) = 2.014, p = 0.032, CI = [7.7,245.4]) and occipital (t (14) = 2.647, p = 0.010, CI = [45.0,429.7]) regions. Further, a significant decrease in alpha ER% from lower to upper activity (t (8) = 4.475, p = 0.001, CI = [21.0, 65.8]) was found across cortical regions in the novice group. Notably, greater deviation between lower and upper-alpha activity was found across scalp locations in the novice group, compared to the experts. Overall, the findings demonstrate potential local and global EEG-based indices of selective cortical adaptations within a task requiring a high degree of visuospatial cognition, although further work is needed to replicate these findings across other domains.

Anxiety Symptoms in Young Children Are Associated With a Maladaptive Neurobehavioral Profile of Error Responding

BACKGROUND

Childhood anxiety symptoms have been linked to alterations in cognitive control and error processing, but the diverse findings on neural markers of anxiety in young children, which vary by severity and developmental stage, suggest the need for a wider perspective. Integrating new neural markers with established ones, such as the error-related negativity, the error positivity, and frontal theta, could clarify this association. Error-related alpha suppression (ERAS) is a recently proposed index of post-error attentional engagement that has not yet been explored in children with anxiety.

METHODS

To identify neurobehavioral profiles of anxiety in young children by integrating ERAS with the error-related negativity, error positivity, frontal theta, and post-error performance indicators, we employed K-means clustering as an unsupervised multimetric approach. For this, we first aimed to confirm the presence and scalp distribution of ERAS in young children. We performed event-related potentials and spectral analysis of electroencephalogram data collected during a Go/NoGo task (Zoo Task) completed by 181 children (ages 4-7 years; 103 female) who were sampled from across the clinical-to-nonclinical range of anxiety severity using the Child Behavior Checklist.

RESULTS

Results confirmed ERAS, showing lower post-error alpha power, maximal suppression at occipital sites, and less ERAS in younger children. K-means clustering revealed that high anxiety and younger age were associated with reduction in ERAS and frontal theta, less negative error-related negativity, enlarged error positivity, more post-error slowing, and reduced post-error accuracy.

CONCLUSIONS

Our findings indicate a link between ERAS, maladaptive neural mechanisms of attention elicited by errors, and anxiety in young children, suggesting that anxiety may arise from or interfere with attention and error processing.

Modulation of EEG Signals by Visual and Auditory Distractors in Virtual Reality-Based Continuous Performance Tests

Compared to traditional continuous performance tasks, virtual reality-based continuous performance tests (VR-CPT) offer higher ecological validity. While previous studies have primarily focused on behavioral outcomes in VR-CPT and incorporated various distractors to enhance ecological realism, little attention has been paid to the effects of distractors on EEG. Therefore, our study aimed to investigate the influence of distractors on EEG during VR-CPT. We studied visual distractors and auditory distractors separately, recruiting 68 subjects (M =20.82, SD =1.72) and asking each to complete four tasks. These tasks were categorized into four groups according to the presence or absence of visual and auditory distractors. We conducted paired t-tests on the mean relative power of the five electrodes in the ROI region across different frequency bands. Significant differences were found in theta waves between Group 3 (M =2.49, SD =2.02) and Group 4 (M =2.68, SD =2.39) (p < 0.05); in alpha waves between Group 3 (M =2.08, SD =3.73) and Group 4 (M =3.03, SD =4.60) (p < 0.001); and in beta waves between Group 1 (M = -4.44 , SD =2.29) and Group 2 (M = -5.03 , SD =2.48) (p < 0.001), as well as between Group 3 (M = -4.48 , SD =2.03) and Group 4 (M = -4.67 , SD =2.23) (p < 0.05). The incorporation of distractors in VR-CPT modulates EEG signals across different frequency bands, with visual distractors attenuating theta band activity, auditory distractors enhancing alpha band activity, and both types of distractors reducing beta oscillations following target stimuli. This insight holds significant promise for the rehabilitation of children and adolescents with attention deficits.

The neuro-oscillatory profiles of static and dynamic music-induced visual imagery

Visual imagery, i.e., seeing in the absence of the corresponding retinal input, has been linked to visual and motor processing areas of the brain. Music listening provides an ideal vehicle for exploring the neural correlates of visual imagery because it has been shown to reliably induce a broad variety of content, ranging from abstract shapes to dynamic scenes. Forty-two participants listened with closed eyes to twenty-four excerpts of music, while a 15-channel EEG was recorded, and, after each excerpt, rated the extent to which they experienced static and dynamic visual imagery. Our results show both static and dynamic imagery to be associated with posterior alpha suppression (especially in lower alpha) early in the onset of music listening, while static imagery was associated with an additional alpha enhancement later in the listening experience. With regard to the beta band, our results demonstrate beta enhancement to static imagery, but first beta suppression before enhancement in response to dynamic imagery. We also observed a positive association, early in the listening experience, between gamma power and dynamic imagery ratings that was not present for static imagery ratings. Finally, we offer evidence that musical training may selectively drive effects found with respect to static and dynamic imagery and alpha, beta, and gamma band oscillations. Taken together, our results show the promise of using music listening as an effective stimulus for examining the neural correlates of visual imagery and its contents. Our study also highlights the relevance of future work seeking to study the temporal dynamics of music-induced visual imagery.

Alpha desynchronization during the filtering initiation phase reflects active processing of distractors

The ability to select task-relevant information and filter out task-irrelevant information is critical to our success in daily goal-directed behavior. Researchers call this ability filtering efficiency and divide it into three cognitive processing stages: detection of distractors, initiation of filtering, and unnecessary storage. Although researchers have conducted more studies on ERP components related to filtration efficiency, there are few studies related to neural oscillations. Alpha oscillation activity is related to the active processing of information and the suppression of distractors. In the current EEG study, we used the change detection task with distracted items to examine whether alpha activity during filtering initiation reflects reactive suppression of distractors by manipulating memory load levels and the presence or absence of distractors. Results showed that, the presence of the distractors caused an increase in the degree of desynchronization of the alpha oscillations, and in the subsequent time, the alpha activity level returned to a level consistent with the absence of interference conditions. Phase synchronization between frontal and posterior brain regions in the upper alpha oscillations found no effects associated with distractors. Based on these results, we believed that the alpha activity during the filtering initiation phase reflected the active processing of distractors, but this may also be due to lower perceptual load of the target items. In addition, we observed a dominance effect of the right hemisphere in both time-frequency results and connectivity results. We speculate that this effect is related to the activation of the right ventral frontoparietal network.

Influence of High-frequency Yoga Breathing (Kapalabhati) on States Changes in Gamma Oscillation

Background

Yoga breathing has been shown to enhance neurocognitive function and positive emotions by increasing electrical power in several frequency bands and synchronizing interhemispheric brain waves. The current study examined the immediate impact of practicing Kapalabhati (KBH) on the electrical activity of the brain.

Methods

Thirty-six individuals who met the inclusion and exclusion criteria and ranged in age from 18 to 25 were randomly assigned, 1:1, to the KBH (n = 18) and breath awareness (BAW) (n = 18) groups. Before data collection, both groups received their respective practices for 10 min each day for a total of 15 days. The brain's electrical activities were assessed using 128-channel EEG recording. The electrodes were placed on their scalps according to the international 10-10 system, ensuring optimal coverage of different brain regions. The EEG signals were amplified, digitized, and stored for offline analysis.

Results

The EEG data showed that the practice of KBH significantly increased alpha waves in the frontal and temporal regions. Moreover, gamma waves increased significantly in the frontal, temporal, and occipital regions after the practice of KBH when compared with BAW.

Conclusion

The results suggest the involvement of frontal and temporal regions, which highlights the importance of KBH in enhancing higher-order cognitive processes. These results provide valuable insights and support for the use of KBH as a potential intervention for individuals seeking to enhance their cognitive abilities.

Evolutionary origin of alpha rhythms in vertebrates

The purpose of this review extends beyond the traditional triune brain model, aiming to elucidate the evolutionary aspects of alpha rhythms in vertebrates. The forebrain, comprising the telencephalon (pallium) and diencephalon (thalamus, hypothalamus), is a common feature in the brains of all vertebrates. In mammals, evolution has prioritized the development of the forebrain, especially the neocortex, over the midbrain (mesencephalon) optic tectum, which serves as the prototype for the visual brain. This evolution enables mammals to process visual information in the retina-thalamus (lateral geniculate nucleus)-occipital cortex pathway. The origin of posterior-dominant alpha rhythms observed in mammals in quiet and dark environments is not solely attributed to cholinergic pontine nuclei cells functioning as a 10 Hz pacemaker in the brainstem. It also involves the ability of the neocortex's cortical layers to generate traveling waves of alpha rhythms with waxing and waning characteristics. The utilization of alpha rhythms might have facilitated the shift of attention from external visual inputs to internal cognitive processes as an adaptation to thrive in dark environments. The evolution of alpha rhythms might trace back to the dinosaur era, suggesting that enhanced cortical connectivity linked to alpha bands could have facilitated the development of nocturnal awakening in the ancestors of mammals. In fishes, reptiles, and birds, the pallium lacks a cortical layer. However, there is a lack of research clearly observing dominant alpha rhythms in the pallium or organized nuclear structures in fishes, reptiles, or birds. Through convergent evolution, the pallium of birds, which exhibits cortex-like fiber architecture, has not only acquired advanced cognitive and motor abilities but also the capability to generate low-frequency oscillations (4-25 Hz) resembling alpha rhythms. This suggests that the origins of alpha rhythms might lie in the pallium of a common ancestor of birds and mammals.

A Role for Bottom-Up Alpha Oscillations in Temporal Integration

Neural oscillations in the 8-12 Hz alpha band are thought to represent top-down inhibitory control and to influence temporal resolution: Individuals with faster peak frequencies segregate stimuli appearing closer in time. Recently, this theory has been challenged. Here, we investigate a special case in which alpha does not correlate with temporal resolution: when stimuli are presented amidst strong visual drive. Based on findings regarding alpha rhythmogenesis and wave spatial propagation, we suggest that stimulus-induced, bottom-up alpha oscillations play a role in temporal integration. We propose a theoretical model, informed by visual persistence, lateral inhibition, and network refractory periods, and simulate physiologically plausible scenarios of the interaction between bottom-up alpha and the temporal segregation. Our simulations reveal that different features of oscillations, including frequency, phase, and power, can influence temporal perception and provide a theoretically informed starting point for future empirical studies.

Inhibitory control in WM gate-opening: Insights from alpha desynchronization and norepinephrine activity under atDCS stimulation

Our everyday activities require the maintenance and continuous updating of information in working memory (WM). To control this dynamic, WM gating mechanisms have been suggested to be in place, but the neurophysiological mechanisms behind these processes are far from being understood. This is especially the case when it comes to the role of oscillatory neural activity. In the current study we combined EEG recordings, and anodal transcranial direct current stimulation (atDCS) and pupil diameter recordings to triangulate neurophysiology, functional neuroanatomy and neurobiology. The results revealed that atDCS, compared to sham stimulation, affected the WM gate opening mechanism, but not the WM gate closing mechanism. The altered behavioral performance was associated with specific changes in alpha band activities (reflected by alpha desynchronization), indicating a role for inhibitory control during WM gate opening. Functionally, the left superior and inferior parietal cortices, were associated with these processes. The findings are the first to show a causal relevance of alpha desynchronization processes in WM gating processes. Notably, pupil diameter recordings as an indirect index of the norepinephrine (NE) system activity revealed that individuals with stronger inhibitory control (as indexed through alpha desynchronization) showed less pupil dilation, suggesting they needed less NE activity to support WM gate opening. However, when atDCS was applied, this connection disappeared. The study suggests a close link between inhibitory controlled WM gating in parietal cortices, alpha band dynamics and the NE system.

Sensory Drive Modifies Brain Dynamics and the Temporal Integration Window

Perception is suggested to occur in discrete temporal windows, clocked by cycles of neural oscillations. An important testable prediction of this theory is that individuals' peak frequencies of oscillations should correlate with their ability to segregate the appearance of two successive stimuli. An influential study tested this prediction and showed that individual peak frequency of spontaneously occurring alpha (8-12 Hz) correlated with the temporal segregation threshold between two successive flashes of light [Samaha, J., & Postle, B. R. The speed of alpha-band oscillations predicts the temporal resolution of visual perception. Current Biology, 25, 2985-2990, 2015]. However, these findings were recently challenged [Buergers, S., & Noppeney, U. The role of alpha oscillations in temporal binding within and across the senses. Nature Human Behaviour, 6, 732-742, 2022]. To advance our understanding of the link between oscillations and temporal segregation, we devised a novel experimental approach. Rather than relying entirely on spontaneous brain dynamics, we presented a visual grating before the flash stimuli that is known to induce continuous oscillations in the gamma band (45-65 Hz). By manipulating the contrast of the grating, we found that high contrast induces a stronger gamma response and a shorter temporal segregation threshold, compared to low-contrast trials. In addition, we used a novel tool to characterize sustained oscillations and found that, for half of the participants, both the low- and high-contrast gratings were accompanied by a sustained and phase-locked alpha oscillation. These participants tended to have longer temporal segregation thresholds. Our results suggest that visual stimulus drive, reflected by oscillations in specific bands, is related to the temporal resolution of visual perception.

Uncovering a stability signature of brain dynamics associated with meditation experience using massive time-series feature extraction

Previous research has examined resting electroencephalographic (EEG) data to explore brain activity related to meditation. However, previous research has mostly examined power in different frequency bands. The practical objective of this study was to comprehensively test whether other types of time-series analysis methods are better suited to characterize brain activity related to meditation. To achieve this, we compared >7000 time-series features of the EEG signal to comprehensively characterize brain activity differences in meditators, using many measures that are novel in meditation research. Eyes-closed resting-state EEG data from 49 meditators and 46 non-meditators was decomposed into the top eight principal components (PCs). We extracted 7381 time-series features from each PC and each participant and used them to train classification algorithms to identify meditators. Highly differentiating individual features from successful classifiers were analysed in detail. Only the third PC (which had a central-parietal maximum) showed above-chance classification accuracy (67 %, pFDR = 0.007), for which 405 features significantly distinguished meditators (all pFDR < 0.05). Top-performing features indicated that meditators exhibited more consistent statistical properties across shorter subsegments of their EEG time-series (higher stationarity) and displayed an altered distributional shape of values about the mean. By contrast, classifiers trained with traditional band-power measures did not distinguish the groups (pFDR > 0.05). Our novel analysis approach suggests the key signatures of meditators' brain activity are higher temporal stability and a distribution of time-series values suggestive of longer, larger, or more frequent non-outlying voltage deviations from the mean within the third PC of their EEG data. The higher temporal stability observed in this EEG component might underpin the higher attentional stability associated with meditation. The novel time-series properties identified here have considerable potential for future exploration in meditation research and the analysis of neural dynamics more broadly.

EEG-based neurophysiological indices for expert psychomotor performance - a review

A primary objective of current human neuropsychological performance research is to define the physiological correlates of adaptive knowledge utilization, in order to support the enhanced execution of both simple and complex tasks. Within the present article, electroencephalography-based neurophysiological indices characterizing expert psychomotor performance, will be explored. As a means of characterizing fundamental processes underlying efficient psychometric performance, the neural efficiency model will be evaluated in terms of alpha-wave-based selective cortical processes. Cognitive and motor domains will initially be explored independently, which will act to encapsulate the task-related neuronal adaptive requirements for enhanced psychomotor performance associating with the neural efficiency model. Moderating variables impacting the practical application of such neuropsychological model, will also be investigated. As a result, the aim of this review is to provide insight into detectable task-related modulation involved in developed neurocognitive strategies which support heightened psychomotor performance, for the implementation within practical settings requiring a high degree of expert performance (such as sports or military operational settings).

Predicting the subjective intensity of imagined experiences from electrophysiological measures of oscillatory brain activity

Most people can conjure images and sounds that they experience in their minds. There are, however, marked individual differences. Some people report that they cannot generate imagined sensory experiences at all (aphantasics) and others report that they have unusually intense imagined experiences (hyper-phantasics). These individual differences have been linked to activity in sensory brain regions, driven by feedback. We would therefore expect imagined experiences to be associated with specific frequencies of oscillatory brain activity, as these can be a hallmark of neural interactions within and across regions of the brain. Replicating a number of other studies, relative to a Resting-State we find that the act of engaging in auditory or in visual imagery is linked to reductions in the power of oscillatory brain activity across a broad range of frequencies, with prominent peaks in the alpha band (8-12 Hz). This oscillatory activity, however, did not predict individual differences in the subjective intensity of imagined experiences. For audio imagery, these were rather predicted by reductions within the theta (6-9 Hz) and gamma (33-38 Hz) bands, and by increases in beta (15-17 Hz) band activity. For visual imagery these were predicted by reductions in lower (14-16 Hz) and upper (29-32 Hz) beta band activity, and by an increase in mid-beta band (24-26 Hz) activity. Our data suggest that there is sufficient ground truth in the subjective reports people use to describe the intensity of their imagined sensory experiences to allow these to be linked to the power of distinct rhythms of brain activity. In future, we hope to combine this approach with better measures of the subjective intensity of imagined sensory experiences to provide a clearer picture of individual differences in the subjective intensity of imagined experiences, and of why these eventuate.

[Electroencephalography: features of the obtained data and its applicability in psychiatry]

Presently, there is an increased interest in expanding the range of diagnostic and scientific applications of electroencephalography (EEG). The method is attractive due to non-invasiveness, availability of equipment with a wide range of modifications for various purposes, and the ability to track the dynamics of brain electrical activity directly and with high temporal resolution. Spectral, coherency and other types of analysis provide volumetric information about its power, frequency distribution, spatial organization of signal and its self-similarity in dynamics or in different sections at a time. The development of computing technologies provides processing of volumetric data obtained using EEG and a qualitatively new level of their analysis using various mathematical models. This review discusses benefits and limitations of using the EEG in scientific research, currently known interpretation of the obtained data and its physiological and pathological correlates. It is expected to determine the complex relationship between the parameters of brain electrical activity and various functional and pathological conditions. The possibility of using EEG characteristics as biomarkers of various physiological and pathological conditions is being considered. Electronic databases, including MEDLINE (on PubMed), Google Scholar and Russian Scientific Citation Index (RSCI, on elibrary.ru), scientific journals and books were searched to find relevant studies.

Precision data-driven modeling of cortical dynamics reveals idiosyncratic mechanisms underlying canonical oscillations

Task-free brain activity affords unique insight into the functional structure of brain network dynamics and is a strong marker of individual differences. In this work, we present an algorithmic optimization framework that makes it possible to directly invert and parameterize brain-wide dynamical-systems models involving hundreds of interacting brain areas, from single-subject time-series recordings. This technique provides a powerful neurocomputational tool for interrogating mechanisms underlying individual brain dynamics ("precision brain models") and making quantitative predictions. We extensively validate the models' performance in forecasting future brain activity and predicting individual variability in key M/EEG markers. Lastly, we demonstrate the power of our technique in resolving individual differences in the generation of alpha and beta-frequency oscillations. We characterize subjects based upon model attractor topology and a dynamical-systems mechanism by which these topologies generate individual variation in the expression of alpha vs. beta rhythms. We trace these phenomena back to global variation in excitation-inhibition balance, highlighting the explanatory power of our framework in generating mechanistic insights.

Investigation of advanced mindfulness meditation "cessation" experiences using EEG spectral analysis in an intensively sampled case study

Mindfulness meditation is a contemplative practice informed by Buddhism that targets the development of present-focused awareness and non-judgment of experience. Interest in mindfulness is burgeoning, and it has been shown to be effective in improving mental and physical health in clinical and non-clinical contexts. In this report, for the first time, we used electroencephalography (EEG) combined with a neurophenomenological approach to examine the neural signature of "cessation" events, which are dramatic experiences of complete discontinuation in awareness similar to the loss of consciousness, which are reported to be experienced by very experienced meditators, and are proposed to be evidence of mastery of mindfulness meditation. We intensively sampled these cessations as experienced by a single advanced meditator (with over 23,000 h of meditation training) and analyzed 37 cessation events collected in 29 EEG sessions between November 12, 2019, and March 11, 2020. Spectral analyses of the EEG data surrounding cessations showed that these events were marked by a large-scale alpha-power decrease starting around 40 s before their onset, and that this alpha-power was lowest immediately following a cessation. Region-of-interest (ROI) based examination of this finding revealed that this alpha-suppression showed a linear decrease in the occipital and parietal regions of the brain during the pre-cessation time period. Additionally, there were modest increases in theta power for the central, parietal, and right temporal ROIs during the pre-cessation timeframe, whereas power in the Delta and Beta frequency bands were not significantly different surrounding cessations. By relating cessations to objective and intrinsic measures of brain activity (i.e., EEG power) that are related to consciousness and high-level psychological functioning, these results provide evidence for the ability of experienced meditators to voluntarily modulate their state of consciousness and lay the foundation for studying these unique states using a neuroscientific approach.

Storm on predictive brain: A neurocomputational account of ketamine antidepressant effect

For the past decade, ketamine, an N-methyl-D-aspartate receptor (NMDAr) antagonist, has been considered a promising treatment for major depressive disorder (MDD). Unlike the delayed effect of monoaminergic treatment, ketamine may produce fast-acting antidepressant effects hours after a single administration at subanesthetic dose. Along with these antidepressant effects, it may also induce transient dissociative (disturbing of the sense of self and reality) symptoms during acute administration which resolve within hours. To understand ketamine's rapid-acting antidepressant effect, several biological hypotheses have been explored, but despite these promising avenues, there is a lack of model to understand the timeframe of antidepressant and dissociative effects of ketamine. In this article, we propose a neurocomputational account of ketamine's antidepressant and dissociative effects based on the Predictive Processing (PP) theory, a framework for cognitive and sensory processing. PP theory suggests that the brain produces top-down predictions to process incoming sensory signals, and generates bottom-up prediction errors (PEs) which are then used to update predictions. This iterative dynamic neural process would relies on N-methyl-D-aspartate (NMDAr) and α-amino-3-hydroxy-5-methyl-4-isoxazole-propionic receptors (AMPAr), two major component of the glutamatergic signaling. Furthermore, it has been suggested that MDD is characterized by over-rigid predictions which cannot be updated by the PEs, leading to miscalibration of hierarchical inference and self-reinforcing negative feedback loops. Based on former empirical studies using behavioral paradigms, neurophysiological recordings, and computational modeling, we suggest that ketamine impairs top-down predictions by blocking NMDA receptors, and enhances presynaptic glutamate release and PEs, producing transient dissociative symptoms and fast-acting antidepressant effect in hours following acute administration. Moreover, we present data showing that ketamine may enhance a delayed neural plasticity pathways through AMPAr potentiation, triggering a prolonged antidepressant effect up to seven days for unique administration. Taken together, the two sides of antidepressant effects with distinct timeframe could constitute the keystone of antidepressant properties of ketamine. These PP disturbances may also participate to a ketamine-induced time window of mental flexibility, which can be used to improve the psychotherapeutic process. Finally, these proposals could be used as a theoretical framework for future research into fast-acting antidepressants, and combination with existing antidepressant and psychotherapy.

Proactive and reactive language control in bilingual language production revealed by decoding sustained potentials and electroencephalography oscillations

Adopting highly sensitive multivariate electroencephalography (EEG) and alpha-band decoding analyses, the present study investigated proactive and reactive language control during bilingual language production. In a language-switching task, Chinese-English bilinguals were asked to name pictures based on visually presented cues. EEG and alpha-band decoding accuracy associated with switch and non-switch trials were used as indicators for inhibition over the non-target language. Multivariate EEG decoding analyses showed that the decoding accuracy in L1 but not in L2, was above chance level shortly after cue onset. In addition, alpha-band decoding results showed that the decoding accuracy in L1 rose above chance level in an early time window and a late time window locked to the stimulus. Together, these asymmetric patterns of decoding accuracy indicate that both proactive and reactive attentional control over the dominant L1 are exerted during bilingual word production, with a possibility of overlap between two control mechanisms. We addressed theoretical implications based on these findings for bilingual language control models.

EEG coherence before and after giving birth

During pregnancy and the postpartum period, changes in brain volume and in motivational, sensory, cognitive, and emotional processes have been described. However, to date, longitudinal modifications of brain function have been understudied. To explore regional cortical coupling, in pregnancy and at 3 months postpartum, we analyzed resting-state electroencephalographic (EEG) coherence in the delta, theta, alpha1, alpha2, beta1, and beta2 frequency bands across frontal and parietal regions of the maternal brain (Fp1, Fp2, F3, F4, P3, and P4). We found that from pregnancy to the postpartum period, mothers showed less intrahemispheric EEG coherence between the frontal and parietal regions in the alpha1 and alpha2 bands, as well as greater interhemispheric EEG coherence between frontopolar regions in the beta2 band. These changes suggest decreased inhibition of neural circuits. These neurophysiological changes may represent an adaptive process characteristic of motherhood.

The Experience of Meaningful Coincidences Is Associated with Stronger Alpha Power Increases during an Eyes-closed Resting Condition: A Bayesian Replication Approach

Recognizing and perceiving meaningful patterns in an ever-changing environment is fundamental to (human) beings. Apophenia, patternicity, and the propensity to perceive meaningful coincidences might result from the human brain working as a prediction machine that constantly matches sensory information to prior expectations. The propensity for Type I errors varies between people and, at its extreme, is associated with symptoms of schizophrenia. However, on a nonclinical level seeing meaning in randomness might be benevolent and was found to be associated with creativity and openness. However, hardly any neuroscientific investigation has examined EEG patterns of the propensity to experience meaningful coincidences in this manner. We hypothesized deviations in brain functions as one potential reason why some people experience more meaning in random arrangements than others. The gating by inhibition theory suggests that alpha power increases represent basic control mechanisms of sensory processes during varying task requirements. We found that people perceiving more meaningful coincidences had higher alpha power during an eyes-closed versus eyes-opened condition compared with people experiencing less meaningful coincidences. This indicates deviations in the sensory inhibition mechanism of the brain, which are critically relevant for higher cognitive functions. Applying Bayesian statistics, we replicated this finding in another independent sample.

Brain structure and function in the fourth decade of life after extremely low birth weight: An MRI and EEG study

OBJECTIVE

To examine potential long-term effects of extremely low birth weight (ELBW; ≤ 1000 g) on adult brain structure, brain function, and cognitive-behavioral performance.

METHODS

A subset of survivors from the prospectively-followed McMaster ELBW Cohort (n = 23, MBW = 816 g) and their peers born at normal birth weight (NBW; ≥ 2500 g; n = 14, MBW = 3361 g) provided T1-weighted magnetic resonance imaging (MRI) brain scans, resting electroencephalographic (EEG) recordings, and behavioral responses to a face-processing task in their early thirties.

RESULTS

Visual discrimination accuracy for human faces, resting EEG alpha power, and long-distance alpha coherence were lower in ELBW survivors than NBW adults, and volumes of white matter hypointensities (WMH) were higher. Across groups, face-processing performance was correlated positively with posterior EEG spectral power and long-distance alpha and theta coherence, and negatively with WMH. The associations between face-processing scores and parietal alpha power and theta coherence were reduced after adjustment for WMH.

CONCLUSIONS

Electrocortical activity, brain functional connectivity, and higher-order processing ability may be negatively affected by WMH burden, which is greater in adults born extremely preterm.

SIGNIFICANCE

Decrements in electrocortical activity and behavioral performance in adult ELBW survivors may be partly explained by increased WMH volumes in this vulnerable population.

Phasic, Event-Related Transcutaneous Auricular Vagus Nerve Stimulation Modifies Behavioral, Pupillary, and Low-Frequency Oscillatory Power Responses

Transcutaneous auricular vagus nerve stimulation (taVNS) has been proposed to activate the locus ceruleus-noradrenaline (LC-NA) system. However, previous studies failed to find consistent modulatory effects of taVNS on LC-NA biomarkers. Previous studies suggest that phasic taVNS may be capable of modulating LC-NA biomarkers such as pupil dilation and alpha oscillations. However, it is unclear whether these effects extend beyond pure sensory vagal nerve responses. Critically, the potential of the pupillary light reflex as an additional taVNS biomarker has not been explored so far. Here, we applied phasic active and sham taVNS in 29 subjects (16 female, 13 male) while they performed an emotional Stroop task (EST) and a passive pupil light reflex task (PLRT). We recorded pupil size and brain activity dynamics using a combined Magnetoencephalography (MEG) and pupillometry design. Our results show that phasic taVNS significantly increased pupil dilation and performance during the EST. During the PLRT, active taVNS reduced and delayed pupil constriction. In the MEG, taVNS increased frontal-midline theta and alpha power during the EST, whereas occipital alpha power was reduced during both the EST and PLRT. Our findings provide evidence that phasic taVNS systematically modulates behavioral, pupillary, and electrophysiological parameters of LC-NA activity during cognitive processing. Moreover, we demonstrate for the first time that the pupillary light reflex can be used as a simple and effective proxy of taVNS efficacy. These findings have important implications for the development of noninvasive neuromodulation interventions for various cognitive and clinical applications.SIGNIFICANCE STATEMENT taVNS has gained increasing attention as a noninvasive neuromodulation technique and is widely used in clinical and nonclinical research. Nevertheless, the exact mechanism of action of taVNS is not yet fully understood. By assessing physiology and behavior in a response conflict task in healthy humans, we demonstrate the first successful application of a phasic, noninvasive vagus nerve stimulation to improve cognitive control and to systematically modulate pupillary and electrophysiological markers of the noradrenergic system. Understanding the mechanisms of action of taVNS could optimize future clinical applications and lead to better treatments for mental disorders associated with noradrenergic dysfunction. In addition, we present a new taVNS-sensitive pupillary measure representing an easy-to-use biomarker for future taVNS studies.

A Neurophysiological Evaluation of Cognitive Load during Augmented Reality Interactions in Various Industrial Maintenance and Assembly Tasks

Augmented reality (AR) has been shown to improve productivity in industry, but its adverse effects (e.g., headaches, eye strain, nausea, and mental workload) on users warrant further investigation. The objective of this study is to investigate the effects of different instruction methods (i.e., HoloLens AR-based and paper-based instructions) and task complexity (low and high-demanding tasks) on cognitive workloads and performance. Twenty-eight healthy males with a mean age of 32.12 (SD 2.45) years were recruited in this study and were randomly divided into two groups. The first group performed the experiment using AR-based instruction, and the second group used paper-based instruction. Performance was measured using total task time (TTT). The cognitive workload was measured using the power of electroencephalograph (EEG) features and the NASA task load index (NASA TLX). The results showed that using AR instructions resulted in a reduction in maintenance times and an increase in mental workload compared to paper instructions, particularly for the more demanding tasks. With AR instruction, 0.45% and 14.94% less time was spent on low- and high-demand tasks, respectively, as compared to paper instructions. According to the EEG features, employing AR to guide employees during highly demanding maintenance tasks increased information processing, which could be linked with an increased germane cognitive load. Increased germane cognitive load means participants can better facilitate long-term knowledge and skill acquisition. These results suggested that AR is superior and recommended for highly demanding maintenance tasks since it speeds up maintenance times and increases the possibility that information is stored in long-term memory and encrypted for recalls.

Inhalation boosts perceptual awareness and decision speed

The emergence of consciousness is one of biology's biggest mysteries. During the past two decades, a major effort has been made to identify the neural correlates of consciousness, but in comparison, little is known about the physiological mechanisms underlying first-person subjective experience. Attention is considered the gateway of information to consciousness. Recent work suggests that the breathing phase (i.e., inhalation vs. exhalation) modulates attention, in such a way that attention directed toward exteroceptive information would increase during inhalation. One key hypothesis emerging from this work is that inhalation would improve perceptual awareness and near-threshold decision-making. The present study directly tested this hypothesis. We recorded the breathing rhythms of 30 humans performing a near-threshold decision-making task, in which they had to decide whether a liminal Gabor was tilted to the right or the left (objective decision task) and then to rate their perceptual awareness of the Gabor orientation (subjective decision task). In line with our hypothesis, the data revealed that, relative to exhalation, inhalation improves perceptual awareness and speeds up objective decision-making, without impairing accuracy. Overall, the present study builds on timely questions regarding the physiological mechanisms underlying consciousness and shows that breathing shapes the emergence of subjective experience and decision-making.NEW & NOTEWORTHY Breathing is a ubiquitous biological rhythm in animal life. However, little is known about its effect on consciousness and decision-making. Here, we measured the respiratory rhythm of humans performing a near-threshold discrimination experiment. We show that inhalation, compared with exhalation, improves perceptual awareness and accelerates decision-making while leaving accuracy unaffected.

Handedness effects on imagery of dominant- versus non-dominant-hand movements: An electroencephalographic investigation

Mental representations of our bodies are thought to influence how we interact with our surroundings. We can examine these mental representations through motor imagery, the imagination of movement using scalp EEG recordings. The visual modality of motor imagery emphasises 'seeing' the imagined movement and is associated with increased activity in the alpha rhythm (8-14 Hz) measured over the occipital regions. The kinaesthetic modality emphasises 'feeling' the movement and is associated with decreased activity in the mu rhythm (8-14 Hz) measured over the sensorimotor cortices. These two modalities can be engaged in isolation or together. We recorded EEG activity while 37 participants (17 left-hand dominant) completed an objective hand motor imagery task. Left-handers exhibited significant activity differences between occipital and motor regions only during imagery of right-hand (non-dominant-hand) movements. This difference was primarily driven by less oscillatory activity in the mu rhythm, which may reflect a shift in imagery strategy wherein participants placed more effort into generating the kinaesthetic sensations of non-dominant-hand imagery. Spatial features of 8-14 Hz activity generated from principal component analysis (PCA) provide further support for a strategy shift. Right-handers also exhibited significant differences between alpha and mu activity during imagery of non-dominant movements. However, this difference was not primarily driven by either rhythm, and no differences were observed in the group's PCA results. Together, these findings indicate that individuals imagine movement differently when it involves their dominant versus non-dominant hand, and left-handers may be more flexible in their motor imagery strategies.

Rhythm-based assessment and training for children with attention deficit hyperactivity disorder (ADHD): a feasibility study protocol

Background

The timing-related deficits in individuals with attention deficit hyperactivity disorder (ADHD) contribute to the symptom-related difficulties and cognitive impairments. Current assessment and training measurement only target specific aspects of the timing ability, highlighting the need for more advanced tools to address timing deficits in ADHD. The aim of this study is to develop and validate a rhythm-based assessment and training (RAT) program, which intends to provide a comprehensive understanding of and enhancement to the time-related abilities of children with ADHD, thereby demonstrating its clinical efficacy.

Methods

We will use randomized crossover trials in this study, with participants being randomly assigned to either start with the RAT and then proceed to cognitive training or start with cognitive training and then proceed to the RAT. Both groups will undergo pre- and post- evaluations. The evaluation will be administered immediately before and after the 4-week training period using diagnostic questionnaires, cognitive evaluation tools, and resting electroencephalography (EEG) measurements. Notably, EEG measurements will be conducted concurrently with the RAT evaluations.

Discussion

This study develops and evaluates the feasibility and effectiveness of a RAT while using EEG measurements to elucidate the underlying therapeutic mechanism of auditory rhythm at varying levels of complexity. The study will investigate the potential of RAT as a supplementary or alternative approach for managing ADHD. The multifaceted data collected will yield valuable insights to customize training agendas based on individual developmental stages and prognoses.

Associating Functional Neural Connectivity and Specific Aspects of Sensorimotor Control in Chronic Stroke

Hand sensorimotor deficits often result from stroke, limiting the ability to perform daily living activities. Sensorimotor deficits are heterogeneous among stroke survivors. Previous work suggests a cause of hand deficits is altered neural connectivity. However, the relationships between neural connectivity and specific aspects of sensorimotor control have seldom been explored. Understanding these relationships is important for developing personalized rehabilitation strategies to improve individual patients' specific sensorimotor deficits and, thus, rehabilitation outcomes. Here, we investigated the hypothesis that specific aspects of sensorimotor control will be associated with distinct neural connectivity in chronic stroke survivors. Twelve chronic stroke survivors performed a paretic hand grip-and-relax task while EEG was collected. Four aspects of hand sensorimotor grip control were extracted, including reaction time, relaxation time, force magnitude control, and force direction control. EEG source connectivity in the bilateral sensorimotor regions was calculated in α and β frequency bands during grip preparation and execution. Each of the four hand grip measures was significantly associated with a distinct connectivity measure. These results support further investigations into functional neural connectivity signatures that explain various aspects of sensorimotor control, to assist the development of personalized rehabilitation that targets the specific brain networks responsible for the individuals' distinct sensorimotor deficits.