EEG differences in children between eyes-closed and eyes-open resting conditions

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.

EEG spectral power in developmental coordination disorder and attention-deficit/hyperactivity disorder: a pilot study

Developmental coordination disorder (DCD) and attention-deficit/hyperactivity disorder (ADHD) overlap in symptoms and often co-occur. Differentiation of DCD and ADHD is crucial for a better understanding of the conditions and targeted support. Measuring electrical brain activity with EEG may help to discern and better understand the conditions given that it can objectively capture changes and potential differences in brain activity related to externally measurable symptoms beneficial for targeted interventions. Therefore, a pilot study was conducted to exploratorily examine neurophysiological differences between adults with DCD and/or ADHD at rest. A total of N = 46 adults with DCD (n = 12), ADHD (n = 9), both DCD + ADHD (n = 8), or typical development (n = 17) completed 2 min of rest with eyes-closed and eyes-open while their EEG was recorded. Spectral power was calculated for frequency bands: delta (0.5-3 Hz), theta (3.5-7 Hz), alpha (7.5-12.5 Hz), beta (13-25 Hz), mu (8-13 Hz), gamma (low: 30-40 Hz; high: 40-50 Hz). Within-participants, spectral power in a majority of waveforms significantly increased from eyes-open to eyes-closed conditions. Groups differed significantly in occipital beta power during the eyes-open condition, driven by the DCD versus typically developing group comparison. However, other group comparisons reached only marginal significance, including whole brain alpha and mu power with eyes-open, and frontal beta and occipital high gamma power during eyes-closed. While no strong markers could be determined to differentiate DCD versus ADHD, we theorize that several patterns in beta activity were indicative of potential motor maintenance differences in DCD at rest. Therefore, larger studies comparing EEG spectral power may be useful to identify neurological mechanisms of DCD and continued differentiation of DCD and ADHD.

Electrodermal and central measures of the tonic orienting reflex (OR)

Sokolov described both phasic and tonic aspects of the Orienting Reflex (OR), but subsequent research and theory development has focussed primarily on the phasic OR at the expense of the tonic OR. The present study used prestimulus skin conductance level (SCL) during a dishabituation paradigm to model the tonic OR, examining its amplitude patterning over repeated standard stimulus presentations and a change stimulus. We expected sensitisation (increased amplitude) following the initial and change trials, and habituation (decrement) over the intervening trials. Prestimulus EEG alpha level was explored as a potential central measure of the tonic OR (as an inverse correlate), examining its pattern over stimulus repetition and change in relation to the SCL model. We presented a habituation series of innocuous auditory stimuli to two groups (each N = 20) at different ISIs (Long 13-15 s and Short 5-7 s) and recorded electrodermal and EEG data during two counterbalanced conditions; Indifferent: no task requirements; Significant: silent counting. Across groups and conditions, prestimulus SCLs and alpha amplitudes generally showed the expected trials patterns, confirming our main hypotheses. Findings have important implications for including the assessment of Sokolov's tonic OR in modelling central and autonomic nervous system interactions of fundamental attention and learning processes.

EEG alpha reactivity on eyes opening discriminates patients with schizophrenia and schizoaffective disorder

OBJECTIVE

Alpha activity in the electroencephalogram (EEG) is typically dominant during rest with closed eyes but suppressed by visual stimulation. Previous research has shown that alpha-blockade is less pronounced in schizophrenia patients compared to healthy individuals, but no studies have examined it in schizoaffective disorder.

METHODS

A resting state EEG was used for the analysis of the alpha-reactivity between the eyes closed and the eyes opened conditions in overall (8 - 13 Hz), low (8 - 10 Hz) and high (10 - 13 Hz) alpha bands in three groups: schizophrenia patients (SC, n = 30), schizoaffective disorder (SA, n = 30), and healthy controls (HC, n = 36). All patients had their first psychotic episode and were receiving antipsychotic therapy.

RESULTS

A significant decrease in alpha power was noted across all subjects from the eyes-closed to eyes-open condition, spanning all regions. Alpha reactivity over the posterior regions was lower in SC compared to HC within overall and high alpha. SA showed a trend towards reduced alpha reactivity compared to HC, especially evident over the left posterior region within the overall alpha. Alpha reactivity was more pronounced over the middle and right posterior regions of SA as compared to SC, particularly in the high alpha. Alpha reactivity in SC and SA patients was associated with various negative symptoms.

CONCLUSIONS

Our findings imply distinct alterations in arousal mechanisms in SC and SA and their relation to negative symptomatology. Arousal is more preserved in SA.

SIGNIFICANCE

This study is the first to compare the EEG features of arousal in SC and SA.

In Utero Exposure to Alcohol and Tobacco and Electroencephalogram Power During Childhood

Importance

Prenatal alcohol exposure (PAE) and prenatal tobacco exposure (PTE) are risk factors associated with adverse neurobehavioral and cognitive outcomes.

Objective

To quantify long-term associations of PAE and PTE with brain activity in early and middle childhood via electroencephalography (EEG).

Design, Setting, and Participants

This cohort study included participants enrolled in the Safe Passage Study (August 2007 to January 2015), from which a subset of 649 participants were followed up in the Environmental Influences on Child Health Outcomes Program. From September 2018 through November 2022, EEG recordings were obtained at ages 4, 5, 7, 9, or 11 years. Data were analyzed from November 2022 to November 2023.

Exposures

Maternal self-reported consumptions of alcohol and tobacco during pregnancy were captured at the recruitment interview and at up to 3 visits during pregnancy (20-24, 28-32, and ≥34 weeks' gestation). Classifications of PAE (continuous drinking, quit-early drinking, and nondrinking) and PTE (continuous smoking, quit-early smoking, and nonsmoking) were previously obtained.

Main Outcomes and Measures

EEG band powers (theta, alpha, beta, gamma) were extracted from the EEG recordings. Linear regression models were used to estimate the associations of PAE and PTE with EEG estimates.

Results

The final sample included 649 participants (333 [51.3%] female) aged 4, 5, 7, 9, or 11 years. Children whose mothers were in the quit-early drinking cluster had increased alpha power (0.116 [95% CI, 0.023 to 0.209] μV2; P = .02) compared with individuals without PAE. The magnitude of this increase was approximately double for children exposed to continuous drinking (0.211 [95% CI, 0.005 to 0.417] μV2; P = .04). Children whose mothers were in the continuous smoking cluster had decreased beta power (-0.031 [95% CI, -0.059 to -0.003] μV2; P = .03) and gamma power (-0.020 [95% CI, -0.039 to -0.000] μV2; P = .04) compared with the nonsmoking cluster. In exploratory sex-stratified models, male participants in the quit-early PAE cluster had greater EEG power in the alpha band (0.159 [95% CI, 0.003 to 0.315] μV2; P = .04) compared with those with no PAE, and the difference was approximately double for male participants with continuous PAE (0.354 [95% CI, 0.041 to 0.667] μV2; P = .03). Male participants in the continuous PTE cluster had decreased beta (-0.048 [95% CI, -0.090 to - 0.007] μV2; P = .02) and gamma (-0.032 [95% CI, -0.061 - 0.002] μV2; P = .04) power compared with those with no PTE.

Conclusions and Relevance

These findings suggest that even low levels of PAE and PTE were associated with long-term alterations of brain activity.

Unveiling the Multifaceted Problems Associated with Dysrhythmia

Dysrhythmia is a term referring to the occurrence of spontaneous and repetitive changes in potentials with parameters deviating from those considered normal. The term refers to heart anomalies but has a broader meaning. Dysrhythmias may concern the heart, neurological system, digestive system, and sensory organs. Ion currents conducted through ion channels are a universal phenomenon. The occurrence of channel abnormalities will therefore result in disorders with clinical manifestations depending on the affected tissue, but phenomena from other tissues and organs may also manifest themselves. A similar problem concerns the implementation of pharmacotherapy, the mechanism of which is related to the impact on various ion currents. Treatment in this case may cause unfavorable effects on other tissues and organs. Drugs acting through the modulation of ion currents are characterized by relatively low tissue specificity. To assess a therapy's efficacy and safety, the risk of occurrences in other tissues with similar mechanisms of action must be considered. In the present review, the focus is shifted prominently onto a comparison of abnormal electrical activity within different tissues and organs. This review includes an overview of the types of dysrhythmias and the basic techniques of clinical examination of electrophysiological disorders. It also presents a concise overview of the available pharmacotherapy in particular diseases. In addition, the authors review the relevant ion channels and their research technique based on patch clumping.

Possible disrupted biological movement processing in Developmental Coordination Disorder

AIM

There is emerging evidence that the Mirror Neuron System (MNS) might contribute to the motor learning difficulties characteristic of Developmental Coordination Disorder (DCD). This study aimed to identify whether MNS activity differed between children with and without DCD during action observation, action execution and during a non-action baseline.

METHODS

Electroencephalography (EEG) was used to measure mu rhythm (a proxy for MNS activation) in 8-12-year-old children either with (n = 20) or without (n = 19) a diagnosis of DCD. The mu rhythm was recorded at rest and during five experimental conditions: (1) observation of gross motor and (2) fine motor actions; (3) execution of gross motor and (4) fine motor actions; and (5) non-biological movement. To address whether potential co-occurring traits of other neurodevelopmental conditions were associated with differences in mu rhythm, parents reported their child's attention and social communication skills. Mixed and repeated measure ANOVAs were conducted to examine differences in mu desynchronization and mu power respectively.

RESULTS

The non-DCD group showed greater mu rhythm desynchronization than children with DCD (i.e., more MNS activity), with both groups demonstrating increasing desynchronization from observation of fine actions to execution of gross actions. However, we also found that the children with DCD had less mu power during the non-biological movement condition than the non-DCD children, although mu power did not differ between groups during the resting condition. Correlations between mu desynchronization and children's attention and motor skills showed that poorer attention and motor abilities were associated with reduced MNS activity.

CONCLUSION

Compared to children without DCD, the MNS in children with DCD did not distinguish between biological and non-biological movement. It is possible that the reduced specificity of the MNS in children with DCD is an underlying factor in the motor impairments observed in the disorder. The differential MNS activity could reflect broader atypical activity in perceptual networks that feed into the MNS in DCD.

High Variability Periods in the EEG Distinguish Cognitive Brain States

OBJECTIVE

To describe a novel measure of EEG signal variability that distinguishes cognitive brain states.

METHOD

We describe a novel characterization of amplitude variability in the EEG signal termed "High Variability Periods" or "HVPs", defined as segments when the standard deviation of a moving window is continuously higher than the quartile cutoff. We characterize the parameter space of the metric in terms of window size, overlap, and threshold to suggest ideal parameter choice and compare its performance as a discriminator of brain state to alternate single channel measures of variability such as entropy, complexity, harmonic regression fit, and spectral measures.

RESULTS

We show that the average HVP duration provides a substantially distinct view of the signal relative to alternate metrics of variability and, when used in combination with these metrics, significantly enhances the ability to predict whether an individual has their eyes open or closed and is performing a working memory and Raven's pattern completion task. In addition, HVPs disappear under anesthesia and do not reappear in early periods of recovery.

CONCLUSIONS

HVP metrics enhance the discrimination of various brain states and are fast to estimate.

SIGNIFICANCE

HVP metrics can provide an additional view of signal variability that has potential clinical application in the rapid discrimination of brain states.

Frontal Alpha Asymmetry Argues for the Heterogeneity of Psychological Resilience

Depression is associated with frontal alpha asymmetry (FAA) and Psychological Resilience (PR), although in different ways. Only cursory attention has been given to how these three constructs interact despite the possible clinical and research implications of those associations. One limitation of recent research into these associations has been conceptualising PR as a unitary construct, whereas it has been shown to be multi-component. This study investigated the underlying components of PR, their correlations with FAA, and the effect that participants' depressive status had upon those correlations in a community sample of 54 males and 46 females aged between 18 yr and 75 years. Results confirmed the overall inverse association between total PR and depression for four of the original five PR components and for one of the two components found in this sample. Similarly, there were differences between the ways that FAA and PR components were associated, depending upon the depressive status of participants. Source localisation data indicated that the PR components were not uniformly correlated with alpha activity in the same brain regions. These findings of content, efficacy, and neurophysiological differences between the five components of PR and their associations with FAA argue against consideration of PR as a unitary construct.

Exploratory Study on the Clinical use of EEG for the People with Chronic Stroke and Their Correlation with the Neuropsychological Outcome

Objective. To measure the EEG signals of the people with chronic stroke in eyes-closed and eyes-open condition and study their relationship with the cognitive function and mental wellbeing. Methods. The investigators would conduct cognitive and mental wellbeing tests on recruited subjects. Their EEG signal was acquired by the 16-channel EEG system. The absolute power under different frequency bands and EEG indices (delta alpha ratio and pairwise derived brain symmetry index) in different eye conditions was calculated. Pearson's correlation was conducted to investigate the association between the clinical tests and the EEG index. Results. 32 subjects were recruited for the study. There was a significant correlation between the pairwise derived brain symmetry index (pdBSI) in eyes-open condition with the Stroop Test (p = .002), Paced Auditory Serial Addition Test-3 s (p = .008)/2 s (p = .002) and WHO-5 well-being scale (p = .023). Conclusions. There is a significant correlation between the brain symmetry index and the cognitive and wellbeing assessment. Brain symmetry index over the delta frequency has been found to be the most useful parameter relating to the clinical score.Significance:It is recommended to use EEG as an adjunctive neuropsychological assessment in clinics for people with chronic stroke, especially for clients who could not undertake conventional assessments (eg aphasia, attention problem).Highlights: There is a significant correlation between the EEG index and the clinical neuropsychological assessmentPairwise Derived Brain Symmetry index in delta frequency range correlated with most of the neuropsychological outcome.It is feasible for us to adopt EEG as an adjunctive assessment in clinical settings.

Tensor Decomposition Analysis of Longitudinal EEG Signals Reveals Differential Oscillatory Dynamics in Eyes-Closed and Eyes-Open Motor Imagery BCI: A Case Report

Functional dissociation of brain neural activity induced by opening or closing the eyes has been well established. However, how the temporal dynamics of the underlying neuronal modulations differ between these eye conditions during movement-related behaviours is less known. Using a robotic-assisted motor imagery brain-computer interface (MI BCI), we measured neural activity over the motor regions with electroencephalography (EEG) in a stroke survivor during his longitudinal rehabilitation training. We investigated lateralized oscillatory sensorimotor rhythm modulations while the patient imagined moving his hemiplegic hand with closed and open eyes to control an external robotic splint. In order to precisely identify the main profiles of neural activation affected by MI with eyes-open (MIEO) and eyes-closed (MIEC), a data-driven approach based on parallel factor analysis (PARAFAC) tensor decomposition was employed. Using the proposed framework, a set of narrow-band, subject-specific sensorimotor rhythms was identified; each of them had its own spatial and time signature. When MIEC trials were compared with MIEO trials, three key narrow-band rhythms whose peak frequencies centred at ∼8.0 Hz, ∼11.5 Hz, and ∼15.5 Hz, were identified with differently modulated oscillatory dynamics during movement preparation, initiation, and completion time frames. Furthermore, we observed that lower and higher sensorimotor oscillations represent different functional mechanisms within the MI paradigm, reinforcing the hypothesis that rhythmic activity in the human sensorimotor system is dissociated. Leveraging PARAFAC, this study achieves remarkable precision in estimating latent sensorimotor neural substrates, aiding the investigation of the specific functional mechanisms involved in the MI process.

Periodic and Aperiodic EEG Features as Potential Markers of Developmental Dyslexia

Developmental Dyslexia (DD) is a neurobiological condition affecting the ability to read fluently and/or accurately. Analyzing resting-state electroencephalographic (EEG) activity in DD may provide a deeper characterization of the underlying pathophysiology and possible biomarkers. So far, studies investigating resting-state activity in DD provided limited evidence and did not consider the aperiodic component of the power spectrum. In the present study, adults with (n = 26) and without DD (n = 31) underwent a reading skills assessment and resting-state EEG to investigate potential alterations in aperiodic activity, their impact on the periodic counterpart and reading performance. In parieto-occipital channels, DD participants showed a significantly different aperiodic activity as indexed by a flatter and lower power spectrum. These aperiodic measures were significantly related to text reading time, suggesting a link with individual differences in reading difficulties. In the beta band, the DD group showed significantly decreased aperiodic-adjusted power compared to typical readers, which was significantly correlated to word reading accuracy. Overall, here we provide evidence showing alterations of the endogenous aperiodic activity in DD participants consistently with the increased neural noise hypothesis. In addition, we confirm alterations of endogenous beta rhythms, which are discussed in terms of their potential link with magnocellular-dorsal stream deficit.

EEG rhythm based emotion recognition using multivariate decomposition and ensemble machine learning classifier

Recently, electroencephalogram (EEG) signals have shown great potential to recognize human emotions. The goal of effective computing is to assist computers in understanding various types of emotions via human-computer interaction (HCI). Multichannel EEG signals are used to measure the electrical activity of the brain in space and time. Automated emotion recognition using multichannel EEG signals is an interesting area of cognitive neuroscience and affective computing research. This research proposes EEG multichannel rhythmic features and ensemble machine learning (EML) classifiers with leave-one-subject-out cross-validation (LOSOCV) for automatic emotion classification from multichannel EEG recordings. Multivariate fast iterative filtering (MvFIF) is used to assess the EEG rhythm sequences. EEG rhythms delta(δ), theta(θ), alpha(α), beta(β), and gamma(γ) are separated based on the mean frequency of the EEG rhythm sequence. Three Hjorth parameters and nine entropy features were extracted from multichannel EEG rhythms. Extracted features are selected using the minimum redundancy maximum relevance (mRMR) approach. The experimental design was performed on two emotional datasets (GAMEEMO and DREAMER). The validation showed that gamma rhythm multichannel features with EML-based subspace K-nearest neighbor (SS KNN) were as high as 93.5%-99.8%, achieving high classification accuracy. The comparisons of δ, θ, α, β, and γ rhythms with EML, support vector machine (SVM), and artificial neural network (ANN) were performed. we also analyzed multi-class emotions (HVHA, HVLA, LVHA, LVLA) with an ensemble-based bagging tree on gamma rhythm. It provides a novel solution for multichannel rhythm-specific features in EEG data analysis.

Resting-state EEG patterns of preschool-aged boys with autism spectrum disorder: A pilot study

Defective cognition development during preschool years is believed to be linked with core symptoms of autism spectrum disorder (ASD). Neurophysiological research on mechanisms underly the cognitive disabilities of preschool-aged children with ASD is scarce currently. This pilot study aimed to compare the resting spectral EEG power of preschool-aged boys with ASD with their matched typically developing peers. Children in the ASD group demonstrated reduced central and posterior absolute delta (1-4 Hz) and enhanced frontal absolute beta (12-30 Hz) and gamma (30-45 Hz). The relative power of the ASD group was elevated in delta, theta (4-8 Hz), alpha (8-12 Hz), beta, and gamma bands as compared to the controls. The theta/beta ratio decreased in the frontal regions and enhanced at Cz and Pz electrodes in the ASD group. Correlations between the inhibition and metacognition indices of the behavior rating inventory of executive function-preschool version (BRIEF-P) and the theta/beta ratio for children of both groups were significant. In conclusion, the present study revealed atypical resting spectral characteristics of boys with ASD at preschool ages. Future large-sampled studies for the generalization of our findings and a better understanding of the relationships between brain oscillations and phenotypes of ASD are warranted.

Resting state dynamics in people with varying degrees of anxiety and mindfulness: A nonlinear and nonstationary perspective

Anxiety and mindfulness are two inversely linked traits shown to be involved in various physiological domains. The current study used resting state electroencephalography (EEG) to explore differences between people with low mindfulness-high anxiety (LMHA) (n = 29) and high mindfulness-low anxiety (HMLA) (n = 27). The resting EEG was collected for a total of 6 min, with a randomized sequence of eyes closed and eyes opened conditions. Two advanced EEG analysis methods, Holo-Hilbert Spectral Analysis and Holo-Hilbert cross-frequency phase clustering (HHCFPC) were employed to estimate the power-based amplitude modulation of carrier frequencies, and cross-frequency coupling between low and high frequencies, respectively. The presence of higher oscillation power across the delta and theta frequencies in the LMHA group than the HMLA group might have been due to the similarity between the resting state and situations of uncertainty, which reportedly triggers motivational and emotional arousal. Although these two groups were formed based on their trait anxiety and trait mindfulness scores, it was anxiety that was found to be significant predictor of the EEG power, not mindfulness. It led us to conclude that it might be anxiety, not mindfulness, which might have contributed to higher electrophysiological arousal. Additionally, a higher δ-β and δ-γ CFC in LMHA suggested greater local-global neural integration, consequently a greater functional association between cortex and limbic system than in the HMLA group. The present cross-sectional study may guide future longitudinal studies on anxiety aiming with interventions such as mindfulness to characterize the individuals based on their resting state physiology.

The neural correlates of amplitude of low-frequency fluctuation: a multimodal resting-state MEG and fMRI-EEG study

The amplitude of low-frequency fluctuation (ALFF) describes the regional intensity of spontaneous blood-oxygen-level-dependent signal in resting-state functional magnetic resonance imaging (fMRI). How the fMRI-ALFF relates to the amplitude in electrophysiological signals remains unclear. We here aimed to investigate the neural correlates of fMRI-ALFF by comparing the spatial difference of amplitude between the eyes-closed (EC) and eyes-open (EO) states from fMRI and magnetoencephalography (MEG), respectively. By synthesizing MEG signal into amplitude-based envelope time course, we first investigated 2 types of amplitude in MEG, meaning the amplitude of neural activities from delta to gamma (i.e. MEG-amplitude) and the amplitude of their low-frequency modulation at the fMRI range (i.e. MEG-ALFF). We observed that the MEG-ALFF in EC was increased at parietal sensors, ranging from alpha to beta; whereas the MEG-amplitude in EC was increased at the occipital sensors in alpha. Source-level analysis revealed that the increased MEG-ALFF in the sensorimotor cortex overlapped with the most reliable EC-EO differences observed in fMRI at slow-3 (0.073-0.198 Hz), and these differences were more significant after global mean standardization. Taken together, our results support that (i) the amplitude at 2 timescales in MEG reflect distinct physiological information and that (ii) the fMRI-ALFF may relate to the ALFF in neural activity.

Links between excessive daytime sleepiness and EEG power and activation in two subtypes of ADHD

OBJECTIVES

This study aimed to replicate previously reported EEG characteristics between typically developing (TD) children and two subtypes of Attention Deficit Hyperactivity Disorder (ADHD) using a frontal, single-channel, dry-sensor portable EEG device, and explore whether differences are moderated by excessive daytime sleepiness (EDS).

METHODS

Children with ADHD Inattentive (ADHD-I) and ADHD Combined presentation (ADHD-C) and typically-developing (TD) children (N = 34 in each group) had frontal EEG recorded during eyes-closed resting, eyes-open resting, and focus tasks. Participants also completed the Children's Self-Report Sleep Patterns - Sleepiness Scale as a measure of EDS.

RESULTS

Consistent with previous literature, there were increases in frontal delta and theta power in the ADHD-C compared to ADHD-I and TD groups, in all conditions. Novel power and activation effects in ADHD subtypes, as well as significant group and EDS interactions for alpha and beta power were also found.

CONCLUSIONS

These findings highlight the importance of considering ADHD subtypes and EDS when exploring EEG characteristics, and have important implications for the diagnosis and treatment of children with ADHD.

Assessing vestibular function using electroencephalogram rhythms evoked during the caloric test

Introduction

The vestibular system is responsible for motion perception and balance preservation in the body. The vestibular function examination is useful for determining the cause of associated symptoms, diagnosis, and therapy of the patients. The associated cerebral cortex processes and integrates information and is the ultimate perceptual site for vestibular-related symptoms. In recent clinical examinations, less consideration has been given to the cortex associated with the vestibular system. As a result, it is crucial to increase focus on the expression of the cortical level while evaluating vestibular function. From the viewpoint of neuroelectrophysiology, electroencephalograms (EEG) can enhance the assessments of vestibular function at the cortex level.

Methods

This study recorded nystagmus and EEG data throughout the caloric test. Four phases were considered according to the vestibular activation status: before activation, activation, fixation suppression, and recovery. In different phases, the distribution and changes of the relative power of the EEG rhythms (delta, theta, alpha, and beta) were analyzed, and the correlation between EEG characteristics and nystagmus was also investigated.

Results

The results showed that, when the vestibule was activated, the alpha power of the occipital region increased, and the beta power of the central and top regions and the occipital region on the left decreased. The changes in the alpha and beta rhythms significantly correlate with nystagmus values in left warm stimulation.

Discussion

Our findings offer a fresh perspective on cortical electrophysiology for the assessment of vestibular function by demonstrating that the relative power change in EEG rhythms can be used to assess vestibular function.

Longitudinal characterization of EEG power spectra during eyes open and eyes closed conditions in children

This study is the first to examine spectrum-wide (1 to 250 Hz) differences in electroencephalogram (EEG) power between eyes open (EO) and eyes closed (EC) resting state conditions in 486 children. The results extend the findings of previous studies by characterizing EEG power differences from 30 to 250 Hz between EO and EC across childhood. Developmental changes in EEG power showed spatial and frequency band differences as a function of age and EO/EC condition. A 64-electrode system was used to record EEG at 4, 5, 7, 9, and 11 years of age. Specific findings were: (1) the alpha peak shifts from 8 Hz at 4 years to 9 Hz at 11 years, (2) EC results in increased EEG power (compared to EO) at lower frequencies but decreased EEG power at higher frequencies for all ages, (3) the EEG power difference between EO and EC changes from positive to negative within a narrow frequency band which shifts toward higher frequencies with age, from 9 to 12 Hz at 4 years to 32 Hz at 11 years, (4) at all ages EC is characterized by an increase in lower frequency EEG power most prominently over posterior regions, (5) at all ages, during EC, decreases in EEG power above 30 Hz are mostly over anterior regions of the scalp. This report demonstrates that the simple challenge of opening and closing the eyes offers the potential to provide quantitative biomarkers of phenotypic variation in brain maturation by employing a brief, minimally invasive protocol throughout childhood.

The development of peak alpha frequency from infancy to adolescence and its role in visual temporal processing: A meta-analysis

While it has been shown that alpha frequency increases over development (Stroganova et al., 1999), a precise trajectory has not yet been specified, making it challenging to constrain theories linking alpha rhythms to perceptual development. We conducted a comprehensive review of studies measuring resting-state occipital peak alpha frequency (PAF, the frequency exhibiting maximum power) from birth to 18 years of age. From 889 potentially relevant studies, we identified 40 reporting PAF (109 samples; 3882 subjects). A nonlinear regression revealed that PAF increases quickly in early childhood (from 6.1 Hz at 6 months to 8.4 Hz at 5 years) and levels off in adolescence (9.7 Hz at 13 years), with an asymptote at 10.1 Hz. We found no effect of resting state procedure (eyes-open versus eyes-closed) or biological sex. PAF has been implicated as a clock on visual temporal processing, with faster frequencies associated with higher visual temporal resolution. Psychophysical studies have shown that temporal resolution reaches adult levels by 5 years of age (Freschl et al., 2019, 2020). The fact that PAF reaches the adult range of 8-12 Hz by that age strengthens the link between PAF and temporal resolution.

Frontal Alpha Asymmetry in Children with Trauma Exposure

The purpose of the current study was to investigate differences in frontal alpha asymmetry (FAA) between children (5-17 years) with or without histories of trauma exposure. EEG data were obtained from 165 children who participated in the Healthy Brain Network Initiative during rest with eyes open and closed. FAA during resting-state electroencephalography was significantly more negative in the trauma-exposed group, suggesting greater left lateralized FAA and avoidance-oriented motivation. Moreover, alpha suppression (difference in alpha amplitude between eyes open and eyes closed conditions) was marginally greater in the trauma-exposed group. The results suggest that early exposure to trauma may be associated with trait-level avoidance of environmental stimuli, which ultimately may be predictive of psychopathology, including posttraumatic stress disorder (PTSD). Study findings thus provide preliminary evidence of brain-based mechanisms that may confer risk for PTSD in the wake of early trauma exposure.

Effect of time windows in LSTM networks for EEG-based BCIs

People with impaired motor function could be helped by an effective brain–computer interface (BCI) based on a real-time electroencephalogram (EEG) and artificial intelligence algorithms. However, current methodologies for interpreting patient instructions from an EEG are not accurate enough to be completely safe in a real-world situation , where a poor decision would place their physical integrity at risk, such as when traveling in an electric wheelchair in a city. For various reasons, such as the low signal-to-noise ratio of portable EEGs or the effects of signal contamination (disturbances due to user movement, temporal variation of the features of EEG signals, etc.), a long short-term memory network (LSTM) (a type of recurrent neural network) that is able to learn data flow patterns from EEG signals could improve the classification of the actions taken by the user. In this paper, the effectiveness of using an LSTM with a low-cost wireless EEG device in real time is tested, and the time window that maximizes its classification accuracy is studied. The goal is to be able to implement it in the BCI of a smart wheelchair with a simple coded command protocol, such as opening or closing the eyes, which could be executed by patients with reduced mobility. Results show a higher resolution of the LSTM with an accuracy range between 77.61 and 92.14% compared to traditional classifiers (59.71%), and an optimal time window of around 7 s for the task done by users in this work. In addition, tests in real-life contexts show that a trade-off between accuracy and response times is necessary to ensure detection.

Resting state electroencephalography (EEG) correlates with children's language skills: Evidence from sentence repetition

Spontaneous neural oscillatory activity reflects the brain's functional architecture and has previously been shown to correlate with perceptual, motor and executive skills. The current study used resting state electroencephalography to examine the relationship between spontaneous neural oscillatory activity and children's language skills. Participants in the study were 52 English-speaking children aged around 10-years. Language was assessed using a sentence repetition task. The main analysis revealed resting state theta power negatively correlated with this task. No significant correlations were found in the other studied frequency bands (delta, alpha, beta, gamma). As part of typical brain development, spontaneous theta power declines across childhood and adolescence. The negative correlation observed in this study may therefore be indicating children's language skills are related to the maturation of theta oscillations. More generally, the study provides further evidence that oscillatory activity in the developing brain, even at rest, is reliably associated with children's language skills.

Eyes-closed versus eyes-open differences in spontaneous neural dynamics during development

Background:

Assessing brain activity during rest has become a widely used approach in developmental neuroscience. Extant literature has measured resting brain activity both during eyes-open and eyes-closed conditions, but the difference between these conditions has not yet been well characterized. Studies, limited to fMRI and EEG, have suggested that eyes-open versus -closed conditions may differentially impact neural activity, especially in visual cortices.

Methods:

Spontaneous cortical activity was recorded using MEG from 108 typically developing youth (9-15 years-old; 55 female) during separate sessions of eyes-open and eyes-closed rest. MEG source images were computed, and the strength of spontaneous neural activity was estimated in the canonical delta, theta, alpha, beta, and gamma bands, respectively. Power spectral density maps for eyes-open were subtracted from eyes-closed rest, and then submitted to vertex-wise regression models to identify spatially specific differences between conditions and as a function of age and sex.

Results:

Relative alpha power was weaker in the eyes-open compared to -closed condition, but otherwise eyes-open was stronger in all frequency bands, with differences concentrated in the occipital cortex. Relative theta power became stronger in the eyes-open compared to the eyes-closed condition with increasing age in frontal cortex. No differences were observed between males and females.

Conclusions:

The differences in relative power from eyes-closed to -open conditions are consistent with changes observed in task-based visual sensory responses. Age differences occurred in relatively late developing frontal regions, consistent with canonical attention regions, suggesting that these differences could be reflective of developmental changes in attention processes during puberty. Taken together, resting-state paradigms using eyes-open versus -closed produce distinct results and, in fact, can help pinpoint sensory related brain activity.

Electroencephalogram aperiodic power spectral slope can be reliably measured and predicts ADHD risk in early development

The aperiodic exponent of the electroencephalogram (EEG) power spectrum has received growing attention as a physiological marker of neurodevelopmental psychopathology, including attention-deficit/hyperactivity disorder (ADHD). However, its use as a marker of ADHD risk across development, and particularly in very young children, is limited by unknown reliability, difficulty in aligning canonical band-based measures across development periods, and unclear effects of treatment in later development. Here, we investigate the internal consistency of the aperiodic EEG power spectrum slope and its association with ADHD risk in both infants (n = 69, 1-month-old) and adolescents (n = 262, ages 11-17 years). Results confirm good to excellent internal consistency in infancy and adolescence. In infancy, a larger aperiodic exponent was associated with greater family history of ADHD. In contrast, in adolescence, ADHD diagnosis was associated with a smaller aperiodic exponent, but only in children with ADHD who had not received stimulant medication treatment. Results suggest that disruptions in cortical development associated with ADHD risk may be detectable shortly after birth via this approach. Together, findings imply a dynamic developmental shift in which the developmentally normative flattening of the EEG power spectrum is exaggerated in ADHD, potentially reflecting imbalances in cortical excitation and inhibition that could contribute to long-lasting differences in brain connectivity.

Spectral parameterization for studying neurodevelopment: How and why

A growing body of literature suggests that the explicit parameterization of neural power spectra is important for the appropriate physiological interpretation of periodic and aperiodic electroencephalogram (EEG) activity. In this paper, we discuss why parameterization is an imperative step for developmental cognitive neuroscientists interested in cognition and behavior across the lifespan, as well as how parameterization can be readily accomplished with an automated spectral parameterization ("specparam") algorithm (Donoghue et al., 2020a). We provide annotated code for power spectral parameterization, via specparam, in Jupyter Notebook and R Studio. We then apply this algorithm to EEG data in childhood (N = 60; Mage = 9.97, SD = 0.95) to illustrate its utility for developmental cognitive neuroscientists. Ultimately, the explicit parameterization of EEG power spectra may help us refine our understanding of how dynamic neural communication contributes to normative and aberrant cognition across the lifespan. Data and annotated analysis code for this manuscript are available on GitHub as a supplement to the open-access specparam toolbox.

Periodic and aperiodic neural activity displays age-dependent changes across early-to-middle childhood

The neurodevelopmental period spanning early-to-middle childhood represents a time of significant growth and reorganisation throughout the cortex. Such changes are critical for the emergence and maturation of a range of social and cognitive processes. Here, we utilised both eyes open and eyes closed resting-state electroencephalography (EEG) to examine maturational changes in both oscillatory (i.e., periodic) and non-oscillatory (aperiodic, '1/f-like') activity in a large cohort of participants ranging from 4-to-12 years of age (N = 139, average age=9.41 years, SD=1.95). The EEG signal was parameterised into aperiodic and periodic components, and linear regression models were used to evaluate if chronological age could predict aperiodic exponent and offset, as well as well as peak frequency and power within the alpha and beta ranges. Exponent and offset were found to both decrease with age, while aperiodic-adjusted alpha peak frequency increased with age; however, there was no association between age and peak frequency for the beta band. Age was also unrelated to aperiodic-adjusted spectral power within either the alpha or beta bands, despite both frequency ranges being correlated with the aperiodic signal. Overall, these results highlight the capacity for both periodic and aperiodic features of the EEG to elucidate age-related functional changes within the developing brain.

Angular gyrus connectivity at alpha and beta oscillations is reduced during tonic pain - Differential effect of eye state

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Tonic pain differentially altered AG connectivity during eyes closed and eyes open.

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Negative mood and/or sleep quality can influence pain-related connectivity.

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Eyes closed baseline may allow for a reliable detection of pain-related changes.

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Eyes-closed-eyes-open sequence is crucial for assessing pain-related connectivity.

The angular gyrus (AG) is a common hub in the pain networks. The role of the AG during pain perception, however, is still unclear. This crossover study examined the effect of tonic pain on resting state functional connectivity (rsFC) of the AG under eyes closed (EC) and eyes open (EO). It included two sessions (placebo/pain) separated by 24 hours. Pain was induced using topical capsaicin (or placebo as control) on the right forearm. Electroencephalographic rsFC assessed by Granger causality was acquired from 28 healthy participants (14 women) before (baseline) and 1-hour following the application of placebo/capsaicin. Subjects were randomly assigned and balanced to groups of recording sequence (EC-EO, EO-EC). Decreased rsFC at alpha-1 and beta, but not alpha-2, oscillations was found during pain compared to baseline during EC only. For alpha-1, EC-EO group showed a pain-induced decrease only among connections between the right AG and each of the posterior cingulate cortex (PCC, P = 0.002), medial prefrontal cortex (mPFC, P = 0.005), and the left AG (P = 0.023). For beta rsFC, the EC-EO group showed a bilateral decrease in rsFC spanning the connections between the right AG and mPFC (P = 0.015) and between the left AG and each of PCC (P = 0.004) and mPFC (P = 0.026). In contrast, the EO-EC group showed an increase in beta rsFC only among connections between the left AG and each of PCC (P = 0.012) and mPFC (P = 0.036). No significant change in the AG rsFC was found during EO. These results provide insight into the involvement of the AG in pain perception and reveal methodological considerations when assessing rsFC during EO and EC.

Age-related changes in the EEG in an eyes-open condition: I. Normal development

This study investigated age related changes in the EEG of normal children in an eyes-open condition, in order to provide developmental norms for the study of children and adolescents with Attention-Deficit/Hyperactivity Disorder (AD/HD) - see our companion paper (Mason et al., submitted). EEG was recorded at 17 sites from 75 children (63 boys and 12 girls, in the approximately 5:1 ratio common in AD/HD) between the ages of 5 and 16 years. They comprised three groups, each of 25 children (21 boys and 4 girls), divided into Young (5-8 years), Middle (9-12 years), and Old (13-16 years). The EEG was recorded during an eyes-open resting condition and Fourier transformed to provide estimates for total power, and absolute and relative power in the delta, theta, alpha and beta bands. Total power and absolute delta, theta, alpha, and beta decreased with increasing age, as did relative delta, while relative alpha increased with increasing age. Changes occurred faster in the posterior regions for total power, absolute theta and alpha, relative theta, and in frontal regions for absolute and relative beta. Some lateral developmental effects differed with band. These results indicate that maturation effects observed in the eyes-open EEG show some similarities to those reported in eyes-closed conditions, although substantial differences are apparent in the maturation of fast wave activity, particularly alpha. The data provide simple age-norms for eyes-open investigations of EEG differences in young clinical groups, particularly AD/HD. They encourage further investigations of the activational effects of this simple eyes-closed/eyes-open manipulation, which may aid understanding of the energetics of behaviour.

Neurofeedback Training Protocol Based on Selecting Distinctive Features to Treat or Reduce ADHD Symptoms

Recent research has shown that electroencephalography (EEG) theta/beta ratio (TBR) in cases with attention deficit hyperactivity disorder (ADHD) has thus far been reported lower than that in healthy individuals. Accordingly, utilizing EEG-TBR as a biomarker to diagnose ADHD has been called into question. Besides, employing known protocol to reduce EEG-TBR in the vertex (Cz) channel to treat ADHD via neurofeedback (NFB) has been doubted. The present study was to propose a new NFB treatment protocol to manage ADHD using EEG signals from 30 healthy controls and 30 children with ADHD through an attention-based task and to calculate relative power in their different frequency bands. Then, the most significant distinguishing features of EEG signals from both groups were determined via a genetic algorithm (GA). The results revealed that EEG-TBR values in children with ADHD were lower compared with those in healthy peers; however, such a difference was not statistically significant. Likewise, inhibiting alpha band activity and enhancing delta one in F7 or T5 channels was proposed as a new NFB treatment protocol for ADHD. No significant increase in EEG-TBR in the Cz channel among children with ADHD casts doubt on the effectiveness of using EEG-TBR inhibitory protocols in the Cz channel. Consequently, it was proposed to apply the new protocol along with reinforced beta-band activity to treat or reduce ADHD symptoms.

Development of Frontal EEG Differences Between Eyes-Closed and Eyes-Open Resting Conditions in Children: Data From a Single-Channel Dry-Sensor Portable Device

Changes in EEG when moving from an eyes-closed to an eyes-open resting condition result from bottom-up sensory processing and have been referred to as activation. In children, activation is characterized by a global reduction in alpha, frontally present reductions for delta and theta, and a frontal increase for beta. The present study aimed to replicate frontal EEG activation effects using single-channel, dry-sensor EEG, and to extend current understanding by examining developmental change in children. Frontal EEG was recorded using a single-channel, dry-sensor EEG device while 182 children aged 7 to 12 years completed eyes-closed resting (EC), eyes-open resting (EO), and focus (FO) tasks. Results indicated that frontal delta, theta, and alpha power were reduced, and frontal beta power was increased, in the EO compared with the EC condition. Exploratory analysis of a form of top-down activation showed that frontal beta power was increased in the FO compared with to the EO condition, with no differences for other bands. The activation effects were robust at the individual level. The bottom-up activation effects reduced with age for frontal delta and theta, increased for frontal alpha, with no developmental change for top-down or bottom-up frontal beta activation. These findings contribute further to validation of the single-channel, dry-sensor, frontal EEG and provide support for use in a range of medical, therapeutic, and clinical domains.

The Role of Quantitative Electroencephalogram in the Diagnosis and Subgrouping of Attention-Deficit/Hyperactivity Disorder

Attention-deficit/hyperactivity disorder (ADHD) leads to functional decline in academic performance, interpersonal relationships, and development in school-aged children. Early diagnosis and appropriate intervention can significantly reduce the functional decline caused by ADHD. Currently, there is no established biological marker for ADHD. Some studies have suggested that various indicators from the quantitative electroencephalogram (QEEG) may be useful biological markers for the diagnosis of ADHD. Until the 2010s, theta/beta ratio (TBR) was a biomarker candidate for ADHD that consistently showed high diagnostic value. However, limitations of TBR have recently been reported. Studies have demonstrated that phase-amplitude coupling, especially theta phase-gamma amplitude coupling, are related to cognitive dysfunction and may assist in the diagnosis of ADHD. As yet, the underlying mechanism is not clearly established, and the clinical efficacy of these biomarkers needs to be proven through well-controlled studies. Based on the heterogeneous characteristics of ADHD, subgrouping through QEEG plays a key role in diagnosis and treatment planning. Sophisticated, well-designed studies and meta-analyses are necessary to confirm these findings.

Effects of sleep restriction on the sleep electroencephalogram of adolescents

STUDY OBJECTIVES

This report describes findings from an ongoing longitudinal study of the effects of varied sleep durations on wake and sleep electroencephalogram (EEG) and daytime function in adolescents. Here, we focus on the effects of age and time in bed (TIB) on total sleep time (TST) and nonrapid eye movement (NREM) and rapid eye movement (REM) EEG.

METHODS

We studied 77 participants (41 male) ranging in age from 9.9 to 16.2 years over the 3 years of this study. Each year, participants adhered to each of three different sleep schedules: four consecutive nights of 7, 8.5, or 10 h TIB.

RESULTS

Altering TIB successfully modified TST, which averaged 406, 472 and 530 min on the fourth night of 7, 8.5, and 10 h TIB, respectively. As predicted by homeostatic models, shorter sleep durations produced higher delta power in both NREM and REM although these effects were small. Restricted sleep more substantially reduced alpha power in both NREM and REM sleep. In NREM but not REM sleep, sleep restriction strongly reduced both the all-night accumulation of sigma EEG activity (11-15 Hz energy) and the rate of sigma production (11-15 Hz power).

CONCLUSIONS

The EEG changes in response to TIB reduction are evidence of insufficient sleep recovery. The decrease in sigma activity presumably reflects depressed sleep spindle activity and suggests a manner by which sleep restriction reduces waking cognitive function in adolescents. Our results thus far demonstrate that relatively modest TIB manipulations provide a useful tool for investigating adolescent sleep biology.

Frontoparietal network and neuropsychological measures in typically developing children

Resting-state activity has been used to gain a broader understanding of typical and aberrant developmental changes. However, the developmental trajectory of resting-state activity in relation to cognitive performance has not been studied in detail. The present study assessed spectral characteristics of theta (5-8 Hz) and alpha (9-13 Hz) frequency bands during resting-state in a priori selected regions of the frontoparietal network (FPN). We also examined the relationship between resting-state activity and cognitive performance in typically developing children. We hypothesized that older children and children with high attentional scores would have higher parietal alpha activity and frontal theta activity while at rest compared to young children and those with lower attentional scores. MEG data were collected in 65 typically developing children, ages 9-14 years, as part of the Developmental Chronnecto-Genomics study. Resting-state data were collected during eyes open and eyes closed for 5 min. Participants completed the NIH Toolbox Flanker Inhibitory Control (FICA) and Attention Test and Dimensional Change Card Sort Test (DCCS) to assess top-down attentional control. Spectral power density was used to characterize the FPN. We found during eyes open and eyes closed, all participants had higher theta and alpha power in parietal regions relative to frontal regions. The group with high attentional scores had higher alpha power during resting-state eyes closed compared to those with low attentional scores. However, there were no significant differences between age groups, suggesting changes in the maturation of neural oscillations in theta and alpha are not evident among children in the 9-14-year age range.

Sensitive period for the plasticity of alpha activity in humans

Visual experience is crucial for the development of neural processing. For example, alpha activity development is a vision-dependent mechanism. Indeed, studies report no alpha activity is present in blind adults. Nevertheless, studies have not investigated the developmental trajectory of this activity in infants and children with blindness. Here, we hypothesize that the difference in neural activity of blind compared to sighted subjects is: absent at birth, progressive with age, specifically occipital and linked to a gradual motor impairment. Therefore, we consider spectral power of resting-state EEG and its association with motor impairment indices, in blind subjects and in sighted controls between 0 and 11 years of age. Blind subjects show posterior alpha activity during the first three years of life, although weaker and slower maturing compared to sighted subjects. The first great differentiation between blind and sighted subjects occurs between 3 and 6 years of age. Starting in this period, reduced alpha activity increases the probability of motor impairment in blind subjects, likely because of impaired perception/interaction. These results show that visual experience mediates the neural mechanisms generating alpha oscillations during the first years of life, suggesting that it is a sensitive period for the plasticity of this process.

Individual dynamics of delta-beta coupling: using a multilevel framework to examine inter- and intraindividual differences in relation to social anxiety and behavioral inhibition

BACKGROUND

Variation in EEG-derived delta-beta coupling has recently emerged as a potential neural marker of emotion regulation, providing a novel and noninvasive method for assessing a risk factor for anxiety. However, our understanding of delta-beta coupling has been limited to group-level comparisons, which provide limited information about an individual's neural dynamics.

METHODS

The present study used multilevel modeling to map second-by-second coupling patterns between delta and beta power. Specifically, we examined how inter- and intraindividual delta-beta coupling patterns changed as a function of social anxiety symptoms and temperamental behavioral inhibition (BI).

RESULTS

We found that stronger inter- and intraindividual delta-beta coupling were both associated with social anxiety. In contrast, the high-BI group showed weaker coupling relative to the non-BI group, a pattern that did not emerge when analyzing continuous scores of BI.

CONCLUSIONS

In characterizing inter- and intraindividual coupling across the sample, we illustrate the utility of examining neural processes across levels of analysis in relation to psychopathology to create multilevel assessments of functioning and risk.

Automated accurate emotion recognition system using rhythm-specific deep convolutional neural network technique with multi-channel EEG signals

Emotion is interpreted as a psycho-physiological process, and it is associated with personality, behavior, motivation, and character of a person. The objective of affective computing is to recognize different types of emotions for human-computer interaction (HCI) applications. The spatiotemporal brain electrical activity is measured using multi-channel electroencephalogram (EEG) signals. Automated emotion recognition using multi-channel EEG signals is an exciting research topic in cognitive neuroscience and affective computing. This paper proposes the rhythm-specific multi-channel convolutional neural network (CNN) based approach for automated emotion recognition using multi-channel EEG signals. The delta (δ), theta (θ), alpha (α), beta (β), and gamma (γ) rhythms of EEG signal for each channel are evaluated using band-pass filters. The EEG rhythms from the selected channels coupled with deep CNN are used for emotion classification tasks such as low-valence (LV) vs. high valence (HV), low-arousal (LA) vs. high-arousal (HA), and low-dominance (LD) vs. high dominance (HD) respectively. The deep CNN architecture considered in the proposed work has eight convolutions, three average pooling, four batch-normalization, three spatial drop-outs, two drop-outs, one global average pooling and, three dense layers. We have validated our developed model using three publicly available databases: DEAP, DREAMER, and DASPS. The results reveal that the proposed multivariate deep CNN approach coupled with β-rhythm has obtained the accuracy values of 98.91%, 98.45%, and 98.69% for LV vs. HV, LA vs. HA, and LD vs. HD emotion classification strategies, respectively using DEAP database with 10-fold cross-validation (CV) scheme. Similarly, the accuracy values of 98.56%, 98.82%, and 98.99% are obtained for LV vs. HV, LA vs. HA, and LD vs. HD classification schemes, respectively, using deep CNN and θ-rhythm. The proposed multi-channel rhythm-specific deep CNN classification model has obtained the average accuracy value of 57.14% using α-rhythm and trial-specific CV using DASPS database. Moreover, for 8-quadrant based emotion classification strategy, the deep CNN based classifier has obtained an overall accuracy value of 24.37% using γ-rhythms of multi-channel EEG signals. Our developed deep CNN model can be used for real-time automated emotion recognition applications.

EEG Data Quality: Determinants and Impact in a Multicenter Study of Children, Adolescents, and Adults with Attention-Deficit/Hyperactivity Disorder (ADHD)

Electroencephalography (EEG) represents a widely established method for assessing altered and typically developing brain function. However, systematic studies on EEG data quality, its correlates, and consequences are scarce. To address this research gap, the current study focused on the percentage of artifact-free segments after standard EEG pre-processing as a data quality index. We analyzed participant-related and methodological influences, and validity by replicating landmark EEG effects. Further, effects of data quality on spectral power analyses beyond participant-related characteristics were explored. EEG data from a multicenter ADHD-cohort (age range 6 to 45 years), and a non-ADHD school-age control group were analyzed (n_total = 305). Resting-state data during eyes open, and eyes closed conditions, and task-related data during a cued Continuous Performance Task (CPT) were collected. After pre-processing, general linear models, and stepwise regression models were fitted to the data. We found that EEG data quality was strongly related to demographic characteristics, but not to methodological factors. We were able to replicate maturational, task, and ADHD effects reported in the EEG literature, establishing a link with EEG-landmark effects. Furthermore, we showed that poor data quality significantly increases spectral power beyond effects of maturation and symptom severity. Taken together, the current results indicate that with a careful design and systematic quality control, informative large-scale multicenter trials characterizing neurophysiological mechanisms in neurodevelopmental disorders across the lifespan are feasible. Nevertheless, results are restricted to the limitations reported. Future work will clarify predictive value.

Sex differences in resting EEG in healthy young adults

Resting EEG, measured in eyes-closed (EC) and eyes-open (EO) states, can provide insight into behavioural differences between groups. Surprisingly, differences in resting EEG between females and males have not been investigated systematically in previous literature. The present study utilised the four traditional EEG bands to confirm their baseline EC topographies and reactivity (EO minus EC) across groups, to clarify topographical differences between sexes, and to confirm alpha as a measure of arousal. Participants were eighty healthy young adults (40 female), with a mean age of 20.4 (range 18-26) years. Continuous resting EEG was recorded from 30 scalp sites during three 2-minute conditions (EO1, EC, EO2), and EOG-corrected. Data from each condition were divided into 60 sequential 2-second epochs. Accepted artefact-free epochs were Fourier Transformed, and absolute amplitudes in the delta (0.5-3.5 Hz), theta (4.0-7.5 Hz), alpha (8.0-13.0 Hz), and beta (13.5-29.5 Hz) bands were calculated. Across groups in EC, significant topographical differences were found between the band amplitudes, broadly compatible with previous reports. Females had greater overall amplitudes in delta, alpha and beta, enhanced midline activity in theta, and parietal and midline activity in the alpha and beta bands. From EC to EO, reactivity was apparent across the bands as significant reductions, particularly in the parietal region. For females compared to males, the reduction in parietal midline delta and theta, parietal alpha and parietal midline beta was significantly larger. Additionally, across groups, alpha activity was confirmed as an inverse measure of arousal. These findings indicate significant differences in neuronal activity between young adult females and males, and help our interpretation of alpha changes.

Investigating brain electrical activity and functional connectivity in adolescents with clinically elevated levels of ADHD symptoms in alpha frequency band

EEG measures such as power and connectivity have been widely used to investigate the neuronal underpinnings of ADHD. Traditionally, the fixed band analysis, in which a single frequency band is applied to all the subjects, has been used to estimate these EEG measures. However, there are important interindividual differences in the predominant frequency of alpha-band oscillations. In this study, we present an individualized estimate of EEG in the alpha band and compared the results with traditional fixed band analysis. We also examined the EEG profile separately in lower and upper alpha bands. We further examined the association between EEG measures and ADHD symptoms. Eyes closed resting EEG was collected from 21 adolescents with clinically elevated levels of ADHD and 21 age and gender matched control subjects. Spectral power and connectivity were computed in lower and upper alpha bands. Results revealed a dissociation between upper and lower alpha band power and connectivity in ADHD. The ADHD group showed reduced power and connectivity in the lower alpha band and an elevation of upper alpha power compared to the Control group. EEG power in the lower alpha band was negatively associated with ADHD severity. Our results, however, did not provide conclusive evidence for IAF as an overall greater measure of EEG compared to the traditional fixed band method.

Cognitive and electrophysiological markers of adult full syndrome and subthreshold attention-deficit/hyperactivity disorder

Attention-deficit/hyperactivity disorder (ADHD) has been often referred to as an executive function deficit disorder with a specific electrophysiological signature. Although previous research suggests that individuals with subthreshold symptoms also suffer from severe impairments in daily life, only few studies have investigated cognitive and neural alterations in this group. Here, we explored impairments in executive functions and their electrophysiological correlates in a sample of adults with full syndrome (N = 113) and subthreshold (N = 46) ADHD compared to controls (N = 42). Results suggest that adults with full syndrome ADHD exhibit more executive function deficits than controls, while there were no electrophysiological differences found between groups. Also, we observed only small differences in neuropsychological variables between subthreshold ADHD and controls and no evidence for altered neural activity in the resting state. While subthreshold ADHD was not associated with altered executive functions or abnormal electrophysiological activity, this group reported significant psychological impairments and comorbidity.

Effectiveness of the level of personal relevance of visual autobiographical stimuli in the induction of positive emotions in young and older adults: pilot study protocol for a randomized controlled trial

BACKGROUND

The ability to retrieve specific memories is a cognitive and emotional protective factor. Among the most effective techniques to generate autobiographical memories is the use of audio-visual stimuli, particularly images. Developing and improving techniques that facilitate the generation of such memories could be highly effective in the prevention of depressive symptoms, especially in the elderly population. The aim of the present study is to examine how the level of personal relevance of pictures as autobiographical memory cues to induce positive emotions may affect an individual's emotion regulation.

METHODS

The participants, 120 older adults aged 65 and over and 120 young adults aged between 18 and 35, of both sexes and without depressive symptoms, will be induced to a negative mood state by means of viewing a film clip. Following the negative mood induction, the participants will be shown positive images according to experimental group to which they were randomly assigned (high personal relevance: personal autobiographical photographs; medium personal relevance: pictures of favourite locations associated with specific positive autobiographical memories; and low personal relevance: positive images from the International Affective Picture System). We will analyse the differences in subjective (responses to questionnaires) and objectives measures (EEG signal, heart rate variability and electrodermal activity) between the groups before and after the induction of negative affect and following the recall of positive memories.

DISCUSSION

The use of images associated with specific positive autobiographical memories may be an effective input for inducing positive mood states, which has potentially important implications for their use as a cognitive behavioural technique to treat emotional disorders, such as depression, which are highly prevalent among older adults.

TRIAL REGISTRATION

ClinicalTrials.gov NCT04251104 . Registered on 30 January 2020.

Atypical Electrophysiological Indices of Eyes-Open and Eyes-Closed Resting-State in Children and Adolescents with ADHD and Autism

Investigating electrophysiological measures during resting-state might be useful to investigate brain functioning and responsivity in individuals under diagnostic assessment for attention deficit hyperactivity disorder (ADHD) and autism. EEG was recorded in 43 children with or without ADHD and autism, during a 4-min-long resting-state session which included an eyes-closed and an eyes-open condition. We calculated and analyzed occipital absolute and relative spectral power in the alpha frequency band (8-12 Hz), and alpha reactivity, conceptualized as the difference in alpha power between eyes-closed and eyes-open conditions. Alpha power was increased during eyes-closed compared to eyes-open resting-state. While absolute alpha power was reduced in children with autism, relative alpha power was reduced in children with ADHD, especially during the eyes-closed condition. Reduced relative alpha reactivity was mainly associated with lower IQ and not with ADHD or autism. Atypical brain functioning during resting-state seems differently associated with ADHD and autism, however further studies replicating these results are needed; we therefore suggest involving research groups worldwide by creating a shared and publicly available repository of resting-state EEG data collected in people with different psychological, psychiatric, or neurodevelopmental conditions, including ADHD and autism.

Eyes Wide Shut: Primary Process Opens Up

Freud was the first to invite his patients to lie down on a couch, facilitating the closing of the eyes. If the mere fact of closing the eyes favors access to unconscious materials, it should also favor primary process mentation. Primary process is an associative mode of thought based on superficial similarities including phonology, while secondary process mentation in language is primarily concerned with meaning. Fifty-two participants were given French Word Lists with phonological choices (P) corresponding to primary processes, while semantic choices (S) represent secondary processes when they are in mutual competition (PS). For example, participants were given a first word, such as, e.g. cale (to hold), and then had to choose between lac (P; lake) and fixe (S; fix), which alternative was most similar to the first word, cale. Two control lists, SN and PN, where the other choice is unrelated (N for nothing), verify that the subjects are equally capable of recognizing the phonological and semantics similarity. Results show an (near 10% increase in P choices in PS when participants close their eyes, while results on PN and SN were unchanged. The mere fact of closing the eyes induces a modest increase in primary process mentation. Based on the literature, the eyes closed (EC) condition is linked to increased alpha synchronization, which is thought to induce an inward mental shift. This research contributes to validating the psychoanalytic technique consisting on inviting patients to lie down on a couch and invite them to close their eyes.

EEG spectral power, but not theta/beta ratio, is a neuromarker for adult ADHD

Adults with attention-deficit/hyperactivity disorder (ADHD) have been described as having altered resting-state electroencephalographic (EEG) spectral power and theta/beta ratio (TBR). However, a recent review (Pulini et al. 2018) identified methodological errors in neuroimaging, including EEG, ADHD classification studies. Therefore, the specific EEG neuromarkers of adult ADHD remain to be identified, as do the EEG characteristics that mediate between genes and behaviour (mediational endophenotypes). Resting-state eyes-open and eyes-closed EEG was measured from 38 adults with ADHD, 45 first-degree relatives of people with ADHD and 51 unrelated controls. A machine learning classification analysis using penalized logistic regression (Elastic Net) examined if EEG spectral power (1-45 Hz) and TBR could classify participants into ADHD, first-degree relatives and/or control groups. Random-label permutation was used to quantify any bias in the analysis. Eyes-open absolute and relative EEG power distinguished ADHD from control participants (area under receiver operating characteristic = 0.71-0.77). The best predictors of ADHD status were increased power in delta, theta and low-alpha over centro-parietal regions, and in frontal low-beta and parietal mid-beta. TBR did not successfully classify ADHD status. Elevated eyes-open power in delta, theta, low-alpha and low-beta distinguished first-degree relatives from controls (area under receiver operating characteristic = 0.68-0.72), suggesting that these features may be a mediational endophenotype for adult ADHD. Resting-state EEG spectral power may be a neuromarker and mediational endophenotype of adult ADHD. These results did not support TBR as a diagnostic neuromarker for ADHD. It is possible that TBR is a characteristic of childhood ADHD.

The asynchronous state's relation to large-scale potentials in cortex

Understanding the relation between large-scale potentials (M/EEG) and their underlying neural activity can improve the precision of research and clinical diagnosis. Recent insights into cortical dynamics highlighted a state of strongly reduced spike count correlations, termed the asynchronous state (AS). The AS has received considerable attention from experimenters and theorists alike, regarding its implications for cortical dynamics and coding of information. However, how reconcilable are these vanishing correlations in the AS with large-scale potentials such as M/EEG observed in most experiments? Typically the latter are assumed to be based on underlying correlations in activity, in particular between subthreshold potentials. We survey the occurrence of the AS across brain states, regions, and layers and argue for a reconciliation of this seeming disparity: large-scale potentials are either observed, first, at transitions between cortical activity states, which entail transient changes in population firing rate, as well as during the AS, and, second, on the basis of sufficiently large, asynchronous populations that only need to exhibit weak correlations in activity. Cells with no or little spiking activity can contribute to large-scale potentials via their subthreshold currents, while they do not contribute to the estimation of spiking correlations, defining the AS. Furthermore, third, the AS occurs only within particular cortical regions and layers associated with the currently selected modality, allowing for correlations at other times and between other areas and layers.