Resting state EEG oscillatory power differences in ADHD college students and their peers

Prediction of Post-Operative Delirium in Older Adults from Preoperative Cognition and Alpha Power from Resting-State EEG

Postoperative Delirium (POD) is the most common complication following surgery among older adults, and has been consistently associated with increased mortality and morbidity, cognitive decline, and loss of independence, as well as markedly increased health-care costs. The development of new tools to identify individuals at high risk for POD could guide clinical decision-making and enable targeted interventions to potentially decrease delirium incidence and POD-related complications. In this study, we used machine learning techniques to evaluate whether baseline (pre-operative) cognitive function and resting-state electroencephalography could be used to identify patients at risk for POD. Pre-operative resting-state EEGs and the Montreal Cognitive Assessment (MoCA) were collected from 85 patients (age = 73 ± 6.4 years) undergoing elective surgery, 12 of whom subsequently developed POD. The model with the highest f1-score for predicting delirium, a linear-discriminant analysis (LDA) model incorporating MoCA scores and occipital alpha-band EEG features, was subsequently validated in an independent, prospective cohort of 51 older adults (age ≥ 60) undergoing elective surgery, 6 of whom developed POD. The LDA-based model, with a total of 7 features, was able to predict POD with area under the receiver operating characteristic curve, specificity and accuracy all >90%, and sensitivity > 80%, in the validation cohort. Notably, models incorporating both resting-state EEG and MoCA scores outperformed those including either EEG or MoCA alone. While requiring prospective validation in larger cohorts, these results suggest that prediction of POD with high accuracy may be feasible in clinical settings using simple and widely available clinical tools.

Highlights

Predict postoperative delirium using pre-operative EEG alpha power and MoCA scores.Prediction performance improves over cognitive assessment alone.ROC-AUC, specificity, accuracy >90%, and sensitivity > 80%, in a validation cohort.Abnormalities in baseline EEG are a risk factor for postoperative delirium.

Role of visual brainwave entrainment on the resting state brainwaves of children with and without attention-deficit/hyperactivity disorder

The relationship between brainwave oscillations and Attention-Deficit/Hyperactivity Disorder (ADHD)-related cognitive challenges is a trending proposition in the field of Cognitive Neuroscience. Studies suggest the role of brainwave oscillations in the symptom expressions of ADHD-diagnosed children. Intervention studies have further suggested the scope of brain stimulation techniques in improving cognition. The current manuscript explored the effect of changes in the brainwaves post-sensory entrainment on cognitive performance of children. We calculated each participant's brainwave difference and ratios of theta, alpha, and beta power after the entrainment sessions. Further, we explored possible correlations between these values and the psychometric scores. The beta resting state showed the strongest association with selective attention performance of all participants. Theta-beta ratio (TBR) showed an inverse correlation with selective attention and working memory performances. The theta frequency was associated with decreased working performance in children without ADHD. Our findings also suggest a predominant role of TBR than the theta-alpha ratio in determining the cognitive performance of children with ADHD. The individual differences in the entrainment reception were attributed to the participant's age, IQ, and their innate baseline frequencies. The implications of our findings can initiate substantiating brainwave-based entrainment sessions as a therapeutic modality to improve cognition among children.

Rhythmic Attention and ADHD: A Narrative and Systematic Review

In recent decades, a growing body of evidence has confirmed the existence of rhythmic fluctuations in attention, but the effect of inter-individual variations in these attentional rhythms has yet to be investigated. The aim of this review is to identify trends in the attention deficit/hyperactivity disorder (ADHD) literature that could be indicative of between-subject differences in rhythmic attention. A narrative review of the rhythmic attention and electrophysiological ADHD research literature was conducted, and the commonly-reported difference in slow-wave power between ADHD subjects and controls was found to have the most relevance to an understanding of rhythmic attention. A systematic review of the literature examining electrophysiological power differences in ADHD was then conducted to identify studies with conditions similar to those utilised in the rhythmic attention research literature. Fifteen relevant studies were identified and reviewed. The most consistent finding in the studies reviewed was for no spectral power differences between ADHD subjects and controls. However, the strongest trend in the studies reporting power differences was for higher power in the delta and theta frequency bands and lower power in the alpha band. In the context of rhythmic attention, this trend is suggestive of a slowing in the frequency and/or increase in the amplitude of the attentional oscillation in a subgroup of ADHD subjects. It is suggested that this characteristic electrophysiological modulation could be indicative of a global slowing of the attentional rhythm and/or an increase in the rhythmic recruitment of neurons in frontal attention networks in individuals with ADHD.

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.

Microstate dynamics and spectral components as markers of persistent and remittent attention-deficit/hyperactivity disorder

OBJECTIVE

We leveraged microstate characteristics and power features to examine temporal and spectral deviations underlying persistent and remittent attention-deficit/hyperactivity disorder (ADHD).

METHODS

50 young adults with childhood ADHD (28 persisters, 22 remitters) and 28 demographically similar healthy controls (HC) were compared on microstates features and frequency principal components (f-PCs) of eye-closed resting state. Support vector machine model with sequential forward selection (SVM-SFS) was utilized to discriminate three groups.

RESULTS

Four microstates and four comparable f-PCs were identified. Compared to HC, ADHD persisters showed prolonged duration in microstate C, elevated power of the delta component (D), and compromised amplitude of the two alpha components (A1 and A2). Remitters showed increased duration and coverage of microstate C, together with decreased activity of D, relatively intact amplitude of A1, and amplitude reduction in A2. The SVM-SFS algorithm achieved an accuracy of 93.59% in classifying persisters, remitters and controls. The most discriminative features selected were those exhibiting group differences.

CONCLUSIONS

We found widespread anomalies in ADHD persisters in brain dynamics and intrinsic EEG components. Meanwhile, the neural features in remitters exhibited multiple patterns.

SIGNIFICANCE

This study underlines the use of microstate dynamics and spectral components as potential markers of persistent and remittent ADHD.

Music and movement therapy improves quality of life and attention and associated electroencephalogram changes in patients with attention-deficit/hyperactivity disorder

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurobehavioral disorder. Treatments for ADHD include pharmacological and nonpharmacological therapy. However, pharmacological treatments have side effects such as poor appetite, sleep disturbance, and headache. Moreover, nonpharmacological treatments are not effective in ameliorating core symptoms and are time-consuming. Hence, developing an alternative and effective treatment without (or with fewer) side effects is crucial. Music therapy has long been used to treat numerous neurological diseases. Although listening to music is beneficial for mood and cognitive functions in patients with ADHD, research on the effects of music and movement therapy in children with ADHD is lacking.

METHODS

The present study investigated the effects of an 8-week music and movement intervention in 13 children with ADHD. The Pediatric Quality of Life Inventory (PedsQL) was used to evaluate changes in participants' quality of life. Conners' Kiddie Continuous Performance Test (K-CPT 2) and the Swanson, Nolan, and Pelham rating scale (SNAP-IV) were used to assess core symptoms. Electroencephalogram (EEG) recordings were analyzed to determine neurophysiological changes.

RESULTS

The results revealed that the participants' quality of life increased significantly after the 8-week intervention. Furthermore, the participants' hit reaction times in the block 1 and block 2 tests of K-CPT 2 decreased significantly after the intervention. EEG analysis demonstrated an increase in alpha power and Higuchi's fractal dimension and a decrease in delta power in certain EEG channels.

CONCLUSION

Our music and movement intervention is a potential alternative and effective tool for ADHD treatment and it can significantly improve patients' quality of life and attention.

Alpha modulation via transcranial alternating current stimulation in adults with attention-deficit hyperactivity disorder

Background

One potential therapy treating attention-deficit/hyperactivity disorder (ADHD) is to modulate dysfunctional brain activations using brain stimulation techniques. While the number of studies investigating the effect of transcranial direct current stimulation on ADHD symptoms continues to increase, transcranial alternating current stimulation (tACS) is poorly examined. Previous studies reported impaired alpha brain oscillation (8-12 Hz) that may be associated with increased attention deficits in ADHD. Our aim was to enhance alpha power in adult ADHD patients via tACS, using different methods to explore potential therapeutic effects.

Methods

Undergoing a crossover design, adults with ADHD received active and sham stimulation on distinct days. Before and after each intervention, mean alpha power, attention performance, subjective symptom ratings, as well as head and gaze movement were examined.

Results

Frequency analyses revealed a significant power increase in the alpha band after both interventions. Despite a trend toward an interaction effect, this alpha power increase was, however, not significantly higher after active stimulation compared to sham stimulation. For the other measures, some additional pre-post effects were found, which were not intervention-related.

Conclusion

Our study cannot provide clear evidence for a tACS-induced increase in alpha power in adult ADHD patients, and thus no stimulation related improvement of attention parameters. We provide further recommendations for the future investigation of tACS as a potential ADHD treatment.

Compensatory mechanism of attention-deficit/hyperactivity disorder recovery in resting state alpha rhythms

Alpha rhythms in the human electroencephalogram (EEG), oscillating at 8-13 Hz, are located in parieto-occipital cortex and are strongest when awake people close their eyes. It has been suggested that alpha rhythms were related to attention-related functions and mental disorders (e.g., Attention-deficit/hyperactivity disorder (ADHD)). However, many studies have shown inconsistent results on the difference in alpha oscillation between ADHD and control groups. Hence it is essential to verify this difference. In this study, a dataset of EEG recording (128 channel EGI) from 87 healthy controls (HC) and 162 ADHD (141 persisters and 21 remitters) adults in a resting state with their eyes closed was used to address this question and a three-gauss model (summation of baseline and alpha components) was conducted to fit the data. To our surprise, the power of alpha components was not a significant difference among the three groups. Instead, the baseline power of remission and HC group in the alpha band is significantly stronger than that of persister groups. Our results suggest that ADHD recovery may have compensatory mechanisms and many abnormalities in EEG may be due to the influence of behavior rather than the difference in brain signals.

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.

Electroencephalographic Microstates as Novel Functional Biomarkers for Adult Attention-Deficit/Hyperactivity Disorder

BACKGROUND

Research on the electroencephalographic (EEG) signatures of attention-deficit/hyperactivity disorder (ADHD) has historically concentrated on its frequency spectrum or event-related evoked potentials. In this work, we investigate EEG microstates (MSs), an alternative framework defined by the clustering of recurring topographical patterns, as a novel approach for examining large-scale cortical dynamics in ADHD.

METHODS

Using k-means clustering, we studied the spatiotemporal dynamics of ADHD during the rest condition by comparing the MS segmentations between adult patients with ADHD and neurotypical control subjects across two independent datasets: the first dataset consisted of 66 patients with ADHD and 66 control subjects, and the second dataset comprised 22 patients with ADHD and 22 control subjects and was used for out-of-sample validation.

RESULTS

Spatially, patients with ADHD and control subjects displayed equivalent MS topographies (canonical maps), indicating the preservation of prototypical EEG generators in patients with ADHD. However, this concordance was accompanied by significant differences in temporal dynamics. At the group level, and across both datasets, ADHD diagnosis was associated with longer mean durations of a frontocentral topography (MS D), indicating that its electrocortical generator(s) could be acting as pronounced attractors of global cortical dynamics. In addition, its spatiotemporal metrics were correlated with sleep disturbance, the latter being known to have a strong relationship with ADHD. Finally, in the first (larger) dataset, we also found evidence of decreased time coverage and mean duration of a left-right diagonal topography (MS A), which inversely correlated with ADHD scores.

CONCLUSIONS

Overall, our study underlines the value of EEG MSs as promising functional biomarkers for ADHD, offering an additional lens through which to examine its neurophysiological mechanisms.

Preliminary Real-World Evidence Supporting the Efficacy of a Remote Neurofeedback System in Improving Mental Health: Retrospective Single-Group Pretest-Posttest Study

Background

Neurofeedback training (NFT) has been shown to be effective in treating several disorders (eg, attention-deficit/hyperactivity disorder [ADHD], anxiety, and depression); however, little is currently known regarding the effectiveness of remote NFT systems.

Objective

This retrospective study provides real-world data (N=593) to assess the efficacy of app-based remote NFT in improving brain health and cognitive performance.

Methods

Improvement was measured from pre- to postintervention of in-app assessments that included validated symptom questionnaires (the 12-item General Health Questionnaire, the ADHD Rating Scale IV, the Adult ADHD Self-Report Scale, the 7-item Generalized Anxiety Disorder scale, and the 9-item Patient Health Questionnaire), a cognitive test of attention and executive functioning (ie, continuous performance task), and resting electroencephalography (EEG) markers. Clinically significant improvement was evaluated using standard approaches.

Results

The greatest improvement was reported for the anxiety questionnaire, for which 69% (68/99) of participants moved from abnormal to healthy score ranges. Overall, adult and child participants who engaged in neurofeedback to improve attention and executive functions demonstrated improved ADHD scores and enhanced performance on a cognitive (ie, response inhibition) task. Adults with ADHD additionally demonstrated elevated delta/alpha and theta/alpha ratios at baseline and a reduction in the delta/alpha ratio indicator following neurofeedback.

Conclusions

Preliminary findings suggest the efficacy of app-based remote neurofeedback in improving mental health, given the reduced symptom severity from pre- to postassessment for general psychological health, ADHD, anxiety, and depression, as well as adjusted resting EEG neural markers for individuals with symptoms of ADHD. Collectively, this supports the utility of the in-app assessment in monitoring behavioral and neural indices of mental health.

Effects of cathodal transcranial direct current stimulation on inhibitory and attention control in children and adolescents with attention-deficit hyperactivity disorder: A pilot randomized sham-controlled crossover study

The pathophysiological of attention-deficit hyperactivity disorder (ADHD) includes hypoactivation of the dorso-lateral prefrontal cortex (DLPFC). Most studies have used anodal (excitatory) transcranial direct current stimulation (tDCS) to improve ADHD symptoms, however, a meta-analysis showed limited effect on improving inhibition, and no evidence of attention improvement. We thus present a pilot protocol for investigating the effect of other montage i.e. cathodal (inhibitory) tDCS on neurophysiological and behavioral measures in ADHD. Eleven participants underwent active (1.5 mA, 20 min) and sham cathodal tDCS over the left DLPFC for 5 consecutive days at a 1-month interval. Quantitative electroencephalography was recorded in a resting state with the eyes opened and closed during visual go/no-go and auditory continuous performance tasks at baseline, after five sessions, and at 1-week and 1-month follow-ups. Correct responses and omission errors were recorded. After five active sessions, alpha power increased in the right frontal area when the eyes were opened, and delta power in the left frontal area and omission errors decreased during go/no-go tasks, with no differences at follow-ups. The results revealed improvements in inhibitory control, but not for attention. No aftereffects were observed in either outcomes. However, the changes found in both hemispheres would probably support the hypothesis that cathodal stimulation over the left DLPFC may increase the activity of the right DLPFC via transcallosal inhibition. Results of this pilot trial would help to design and implement a full-scale randomized control trials for further ADHD research. This study was registered on ClinicalTrials.gov (NCT03955692).

Electroencephalography complexity in resting and task states in adults with attention-deficit/hyperactivity disorder

Analysing EEG complexity could provide insight into neural connectivity underlying attention-deficit/hyperactivity disorder symptoms. EEG complexity was calculated through multiscale entropy and compared between adults with attention-deficit/hyperactivity disorder and their peers during resting and go/nogo task states. Multiscale entropy change from the resting state to the task state was also examined as an index of the brain’s ability to change from a resting to an active state. Thirty unmedicated adults with attention-deficit/hyperactivity disorder were compared with 30 match-paired healthy peers on the multiscale entropy in the resting and task states as well as their multiscale entropy change. Results showed differences in multiscale entropy between individuals with attention-deficit/hyperactivity disorder and their peers during the resting state as well as the task state. The multiscale entropy measured from the comparison group was larger than that from the attention-deficit/hyperactivity disorder group in the resting state, whereas the reverse pattern was found during the task state. Our most robust finding showed that the multiscale entropy change from individuals with attention-deficit/hyperactivity disorder was smaller than that from their peers, specifically at frontal sites. Interestingly, individuals without attention-deficit/hyperactivity disorder performed better with decreasing multiscale entropy changes, demonstrating higher accuracy, faster reaction time and less variability in their reaction times. These data suggest that multiscale entropy could not only provide insight into neural connectivity differences between adults with attention-deficit/hyperactivity disorder and their peers but also into their behavioural performance.

A randomized controlled study of remote computerized cognitive, neurofeedback, and combined training in the treatment of children with attention-deficit/hyperactivity disorder

There is an increasing interest in non-pharmacological treatments for children with attention-deficit/hyperactivity disorder (AD/HD), especially digital techniques that can be remotely delivered, such as neurofeedback (NFT) and computerized cognitive training (CCT). In this study, a randomized controlled design was used to compare training outcomes between remotely delivered NFT, CCT, and combined NFT/CCT training approaches. A total of 121 children with AD/HD were randomly assigned to the NFT, CCT, or NFT/CCT training groups, with 80 children completing the training program. Pre- and post-training symptoms (primary outcome), executive and daily functions were measured using questionnaires as well as resting EEG during eyes-closed (EC) and eyes-open (EO) conditions. After 3 months of training, the inattentive and hyperactive/impulsive symptoms, inhibition, working memory, learning and life skills of the three groups of children were significantly improved. The objective EEG activity showed a consistent increase in the relative alpha power in the EO condition among the three training groups. Training differences were not observed between groups. There was a positive correlation between pre-training EO relative alpha power and symptom improvement scores of inattention and hyperactivity/impulsivity, as well as a negative correlation between pre-training inattention scores and change in EO relative alpha. This study verified the training effects of NFT, CCT, and combined NFT/CCT training in children with AD/HD and revealed an objective therapeutic role for individual relative alpha activity. The verified feasibility and effectiveness of home-based digital training support promotion and application of digital remote training.

Alfa band power increases in posterior brain regions in attention deficit hyperactivity disorder after digital cognitive stimulation treatment

The changes triggered by pharmacological treatments in resting-state alpha-band (8–14 Hz) oscillations have been widely studied in attention deficit hyperactivity disorder. However, to date, there has been no evidence regarding the possible changes in cognitive stimulation treatments on these oscillations. This paper sets out to verify whether cognitive stimulation treatments based on progressive increases in cognitive load can be effective in triggering changes in alpha-band power in attention deficit hyperactivity disorder. With this objective, we compared a cognitive stimulation treatment (n = 13) to placebo treatment (n = 13) for 12 weeks (36 sessions of 15 min) in child patients (8–11 years old) with attention deficit hyperactivity disorder. Two magnetoencephalographic recordings were acquired for all the participants. In order to extract the areas with changes in alpha power between both magnetoencephalographic recordings, the differences in the power ratio (pre/post-condition) were calculated using an Analysis of Covariance test adjusted for the age variable. The results show an increase in the post-treatment power ratio in the experimental group versus the placebo group (P < 0.01) in posterior regions and the default mode network. In addition, these alpha changes were related to measures of attention, working memory and cognitive flexibility. The results seem to indicate that cognitive stimulation treatment based on progressive increases in cognitive load triggers alpha-band power changes in child attention deficit hyperactivity disorder patients in the direction of their peers without this disorder.

Comparison of Quantitative Electroencephalography between Tic Disorder and Attention-Deficit/Hyperactivity Disorder in Children

Objective

Attention-deficit/hyperactivity disorder (ADHD) and tic disorder (TD) are among the most common comorbid psychopathologies and have a shared genetic basis. The psychopathological and neurophysiological aspects of the mechanism underlying the comorbidity of both disorders have been investigated, but the pathophysiological aspects remain unclear. Therefore, this study aimed to compare the neurophysiological characteristics of ADHD with those of TD using resting-state electroencephalography and exact low-resolution brain electromagnetic tomography (eLORETA) analysis.

Methods

We performed eLORETA analysis based on the resting-state scalp-recorded electrical potential distribution in 34 children with ADHD and 21 age-matched children with TD. Between-group differences in electroencephalography (EEG) current source density in delta, theta, alpha, beta, and gamma bands were investigated in each cortical region.

Results

Compared with the TD group, the ADHD group showed significantly increased theta activity in the frontal region (superior frontal gyrus, t = 3.37, p < 0.05; medial frontal gyrus, t = 3.35, p < 0.05). In contrast, children with TD showed decreased posterior alpha activity than those with ADHD (precuneus, t = −3.40, p < 0.05; posterior cingulate gyrus, t = −3.38, p < 0.05). These findings were only significant when the eyes were closed.

Conclusion

Increased theta activity in the frontal region is a neurophysiological marker that can distinguish ADHD from TD. Also, reduced posterior alpha activity might represent aberrant inhibitory control. Further research needs to confirm these characteristics by simultaneously measuring EEG-functional magnetic resonance imaging.

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.

Electroencephalography Signatures for Conditioned Pain Modulation and Pain Perception in Non-Specific Chronic Low Back Pain-an Exploratory Study

 

Conditioned pain modulation (CPM) can discriminate between healthy and chronic pain patients. However, its relationship with neurophysiological pain mechanisms is poorly understood. Brain oscillations measured by electroencephalography (EEG) might help gain insight into this complex relationship.

OBJECTIVE

To investigate the relationship between CPM response and self-reported pain intensity in non-specific chronic low back pain (NSCLBP) and explore respective EEG signatures associated to these mechanisms.

DESIGN

Cross-sectional analysis. Participants: Thirty NSCLBP patients participated.

METHODS

Self-reported low back pain, questionnaires, mood scales, CPM (static and dynamic quantitative sensory tests), and resting surface EEG data were collected and analyzed. Linear regression models were used for statistical analysis.

RESULTS

CPM was not significantly correlated with self-reported pain intensity scores. Relative power of EEG in the beta and high beta bands as recorded from the frontal, central, and parietal cortical areas were significantly associated with CPM. EEG relative power at delta and theta bands as recorded from the central area were significantly correlated with self-reported pain intensity scores while controlling for self-reported depression.

CONCLUSIONS

Faster EEG frequencies recorded from pain perception areas may provide a signature of a potential cortical compensation caused by chronic pain states. Slower EEG frequencies may have a critical role in abnormal pain processing.

DSM-5 Adult Attention-Deficit/Hyperactivity Disorder: Sex Differences in EEG Activity

This study examined sex differences in the EEG of adults diagnosed with Attention-Deficit/Hyperactivity Disorder (AD/HD) according to DSM-5 criteria. Sixteen females and 16 males with AD/HD, and age- and sex-matched control groups, had an eyes-closed resting EEG recorded from 19 electrode sites. EEGs were Fast Fourier transformed and estimates for total power, absolute and relative power in the delta, theta, alpha, beta and gamma bands, and the theta/beta ratio, were analysed across nine cortical regions. Males with AD/HD, compared with male controls, had globally reduced absolute beta, globally elevated relative theta, and a larger theta/beta ratio. In contrast, no global effects emerged between females with and without AD/HD. Significant group interactions indicated that globally elevated relative theta and elevated frontal-midline theta/beta ratio noted in males with AD/HD differed significantly from results in females. There are statistically significant EEG differences in relative theta and the theta/beta ratio between males and females with and without AD/HD. These results indicate that AD/HD affects the EEG activity of males and females differently. This study helps confirm the need for further independent examination of AD/HD within female populations.

Disrupted Functional Rich-Club Organization of the Brain Networks in Children with Attention-Deficit/Hyperactivity Disorder, a Resting-State EEG Study

Growing evidence indicates that disruptions in the brain's functional connectivity play an important role in the pathophysiology of ADHD. The present study investigates alterations in resting-state EEG source connectivity and rich-club organization in children with inattentive (ADHDI) and combined (ADHDC) ADHD compared with typically developing children (TD) under the eyes-closed condition. EEG source analysis was performed by eLORETA in different frequency bands. The lagged phase synchronization (LPS) and graph theoretical metrics were then used to examine group differences in the topological properties and rich-club organization of functional networks. Compared with the TD children, the ADHDI children were characterized by a widespread significant decrease in delta and beta LPS, as well as increased theta and alpha LPS in the left frontal and right occipital regions. The ADHDC children displayed significant increases in LPS in the central, temporal and posterior areas. Both ADHD groups showed small-worldness properties with significant increases and decreases in the network degree in the θ and β bands, respectively. Both subtypes also displayed reduced levels of network segregation. Group differences in rich-club distribution were found in the central and posterior areas. Our findings suggest that resting-state EEG source connectivity analysis can better characterize alterations in the rich-club organization of functional brain networks in ADHD patients.

EEG Correlates of Sustained Attention Variability during Discrete Multi-finger Force Control Tasks

The neurophysiological characteristics of sustained attention states are unclear in discrete multi-finger force control tasks. In this article, we developed an immersive visuo-haptic task for conducting stimulus-response measurements. Visual cues were randomly provided to signify the required amplitude and tolerance of fingertip force. Participants were required to respond to the visual cues by pressing force transducers using their fingertips. Response time variation was taken as a behavioral measure of sustained attention states during the task. 50% low-variability trials were classified as the optimal state and the other high-variability trials were classified as the suboptimal state using z-scoring over time. A 64-channel electroencephalogram (EEG) acquisition system was used to collect brain activities during the tasks. The haptics-elicited potential amplitude at 20 ∼ 40 ms in latency and over the frontal-central region significantly decreased in the optimal state. Furthermore, the alpha-band power in the spectra of 8 ∼ 13 Hz was significantly suppressed in the frontal-central, right temporal, and parietal regions in the optimal state. Taken together, we have identified neuroelectrophysiological features that were associated with sustained attention during multi-finger force control tasks, which would be potentially used in the development of closed-loop attention detection and training systems exploiting haptic interaction.

An EEG investigation of alpha and beta activity during resting states in adults with Williams syndrome

Background

Williams syndrome (WS) is neurodevelopmental disorder characterised by executive deficits of attention and inhibitory processing. The current study examined the neural mechanisms during resting states in adults with WS in order to investigate how this subserves the attention and inhibitory deficits associated with the syndrome.

Method

Adopting electroencephalography (EEG) methodology, cortical electrical activity was recorded from eleven adults with WS aged 35 + years during Eyes Closed (EC) and Eyes Open (EO) resting states, and compared to that of thirteen typically developing adults matched for chronological age (CA) and ten typically developing children matched for verbal mental ability (MA). Using mixed-design analyses of variance (ANOVA), analyses focused on the full alpha (8–12.5 Hz), low-alpha (8–10 Hz), upper-alpha (10–12.5 Hz), and beta (13–29.5 Hz) bands, as these are thought to have functional significance with attentional and inhibitory processes.

Results

No significant difference in alpha power were found between the WS and CA groups across all analyses, however a trend for numerically lower alpha power was observed in the WS group, consistent with other developmental disorders characterised by attentional/inhibitory deficits such as Attention Deficit Hyperactivity Disorder (ADHD). In contrast, comparable beta power between the WS and CA groups during both EC/EO conditions suggests that their baseline EEG signature is commensurate with successful attentional processing, though this needs to be interpreted with caution due to the small sample size. Analyses also revealed an unusual trend for low variability in the EEG signature of the WS group, which contradicts the heterogeneity typically observed behaviourally.

Conclusions

This novel finding of low variability in the EEG spectra in the WS group has been previously associated with poor behavioural performance in ADHD and is highly informative, highlighting future research needs to also consider how the role of low variability in the EEG profile of WS manifests in relation to their behavioural and cognitive profiles.

Visuospatial Working Memory Capacity in the Brain After Working Memory Training in College Students With ADHD: A Randomized Controlled Trial

Objective: ADHD has been associated with persistent problems of working memory. This study investigated the efficacy of an intensive and adaptive computerized working memory treatment (CWMT) at behavioral and neural levels. Method: College students (n = 89; 40 females) with ADHD were randomized into a standard-length CWMT (45 min/session, 25 sessions, n = 29), shortened-length CWMT (15 min/session, 25 sessions, n = 32), and a waitlist group (n = 28). Both CWMT groups received treatment for 5 days a week for 5 weeks. Lab sessions before and after CWMT assessed electroencephalography (EEG) indicators of working memory, behavioral indicators of working memory performance, and ADHD symptomatology. Results: No evidence was found for neural or any other behavioral transfer effects of improvement for the CWMT treatment groups over the active control or waitlist group. Conclusion: Our study does not provide evidence for the benefits of CWMT at neural or behavioral levels.

A Review of Automated Techniques for Assisting the Early Detection of Alzheimer's Disease with a Focus on EEG

In this paper, we review state-of-the-art approaches that apply signal processing (SP) and machine learning (ML) to automate the detection of Alzheimer's disease (AD) and its prodromal stages. In the first part of the document, we describe the economic and social implications of the disease, traditional diagnosis techniques, and the fundaments of automated AD detection. Then, we present electroencephalography (EEG) as an appropriate alternative for the early detection of AD, owing to its reduced cost, portability, and non-invasiveness. We also describe the main time and frequency domain EEG features that are employed in AD detection. Subsequently, we examine some of the main studies of the last decade that aim to provide an automatic detection of AD and its previous stages by means of SP and ML. In these studies, brain data was acquired using multiple medical techniques such as magnetic resonance imaging, positron emission tomography, and EEG. The main aspects of each approach, namely feature extraction, classification model, validation approach, and performance metrics, are compiled and discussed. Lastly, a set of conclusions and recommendations for future research on AD automatic detection are drawn in the final section of the paper.

Spontaneous Alpha and Theta Oscillations Are Related to Complementary Aspects of Cognitive Control in Younger and Older Adults

The resting-state human electroencephalogram (EEG) power spectrum is dominated by alpha (8-12 Hz) and theta (4-8 Hz) oscillations, and also includes non-oscillatory broadband activity inversely related to frequency (1/f activity). Gratton proposed that alpha and theta oscillations are both related to cognitive control function, though in a complementary manner. Alpha activity is hypothesized to facilitate the maintenance of representations, such as task sets in preparation for expected task conditions. In contrast, theta activity would facilitate changes in representations, such as the updating of task sets in response to unpredicted task demands. Therefore, theta should be related to reactive control (which may prompt changes in task representations), while alpha may be more relevant to proactive control (which implies the maintenance of current task representations). Less is known about the possible relationship between 1/f activity and cognitive control, which was analyzed here in an exploratory fashion. To investigate these hypothesized relationships, we recorded eyes-open and eyes-closed resting-state EEG from younger and older adults and subsequently tested their performance on a cued flanker task, expected to elicit both proactive and reactive control processes. Results showed that alpha power and 1/f offset were smaller in older than younger adults, whereas theta power did not show age-related reductions. Resting alpha power and 1/f offset were associated with proactive control processes, whereas theta power was related to reactive control as measured by the cued flanker task. All associations were present over and above the effect of age, suggesting that these resting-state EEG correlates could be indicative of trait-like individual differences in cognitive control performance, which may be already evident in younger adults, and are still similarly present in healthy older adults.

Altered cortical functional network in drug-naive adult male patients with attention-deficit hyperactivity disorder: A resting-state electroencephalographic study

Relatively little is known about the neurophysiology of adult Attention-deficit/hyperactivity disorder (ADHD). Brain network analysis can yield important insights into the neuropathology in adult ADHD. The objective of this study was to investigate source-level cortical functional network using resting-state electroencephalography (EEG) in drug-naive adult patients with ADHD. Resting-state EEG was performed for 30 adult male patients with ADHD and 27 male healthy controls. Source-level weighted functional networks based on graph theory were evaluated, including strength, clustering coefficient (CC) and path length (PL) in six frequency bands. At the global level, strength (η² = 0.167) and CC (η² = 0.156) were lower while PL (η² = 0.159) was higher for the high beta band in the ADHD patient group compared to healthy controls. At the nodal level, CCs of the high beta band were lower in the left middle temporal gyrus (η² = 0.244), right inferior occipital cortex (η² = 0.214), right posterior transverse collateral sulcus (η² = 0.237), and right anterior occipital sulcus (η² = 0.251) for the adult ADHD group. Furthermore, the nodal-level high beta band CCs of the left middle temporal gyrus and right anterior occipital sulcus were significantly negatively correlated with ADHD symptoms. The altered cortical functional network showed inefficient connectivity in the left middle temporal gyrus, belonging to the default mode network, the right inferior occipital cortex, belonging to the extrastriate visual resting state network, the right posterior transverse collateral sulcus, belonging to the visual network, and the anterior occipital sulcus, reflecting visual attention, which might affect the pathophysiology of ADHD. Taken together, these attenuated network inefficiencies in adult patients with ADHD may lead to suboptimal information processing and affect symptoms of ADHD, such as inattention and hyperactivity. Our findings should be further replicated using longitudinal study designs.

Potential targets for the treatment of ADHD using transcranial electrical current stimulation

Attention deficit hyperactivity disorder (ADHD) is a psychiatric disease with a prevalence of 2%-7.5% among the population. It is characterized by three core symptoms: hyperactivity, impulsivity, and inattention. Although the majority of ADHD patients respond to a combination of psychotherapy and standard pharmacotherapy with Methylphenidate, there is a significant minority of patients that do not respond to these substances. Additionally, the treatment with Methylphenidate can cause a variety of side effects like insomnia, headache, decreased appetite, and xerostomia. It would be favorable to have an alternative treatment-option that could circumnavigate the shortcomings of traditional pharmacological treatments. Recent results show that transcranial electrical stimulation (tES) might offer a promising approach. Since research has shown that ADHD is associated with various alterations in brain activity, brain stimulation methods targeting different facets of neuronal functions are currently under investigation. In this article, we briefly review different tES techniques like transcranial random noise stimulation (tRNS), transcranial direct current stimulation (tDCS) and transcranial alternating current stimulation (tACS) and explain the modes of action of these brain stimulations. We will specifically focus on transcranial alternating current stimulation (tACS) as a potential method of treating ADHD.

Lesions to the Fronto-Parietal Network Impact Alpha-Band Phase Synchrony and Cognitive Control

Long-range phase synchrony in the α-oscillation band (near 10 Hz) has been proposed to facilitate information integration across anatomically segregated regions. Which areas may top-down regulate such cross-regional integration is largely unknown. We previously found that the moment-to-moment strength of high-α band (10-12 Hz) phase synchrony co-varies with activity in a fronto-parietal (FP) network. This network is critical for adaptive cognitive control functions such as cognitive flexibility required during set-shifting. Using electroencephalography (EEG) in 23 patients with focal frontal lobe lesions (resected tumors), we tested the hypothesis that the FP network is necessary for modulation of high-α band phase synchrony. Global phase-synchrony was measured using an adaptation of the phase-locking value (PLV) in a sliding window procedure, which allowed for measurement of changes in EEG-based resting-state functional connectivity across time. As hypothesized, the temporal modulation (range and standard deviation) of high-α phase synchrony was reduced as a function of FP network lesion extent, mostly due to dorsolateral prefrontal cortex (dlPFC) lesions. Furthermore, patients with dlPFC lesions exhibited reduced cognitive flexibility as measured by the Trail-Making Test (set-shifting). Our findings provide evidence that the FP network is necessary for modulatory control of high-α band long-range phase synchrony, and linked to cognitive flexibility.

The Dynamic Properties of a Brain Network During Spatial Working Memory Tasks in College Students With ADHD Traits

This study investigated deficits of spatial working memory in college students with attention-deficit/hyperactivity disorder (ADHD) traits using event-related potentials (ERPs) and the spatial 2-back task. We also computed sensory-level activity using EEG data and investigated theta and alpha neural oscillations, phase-locking values (PLV), and brain networks. Based on the scores from the Adult ADHD Self-Report Scale (ASRS) and Conners' Adult ADHD Rating Scales (CAARS), an ADHD-trait group (n = 40) and a normal control group (n = 41) were selected. Participants were required to respond to whether the presented stimulus was at the same location as that presented two trials earlier. The ADHD-trait group showed significantly slower response times than the control group in the spatial 2-back task. In terms of spectrum, the ADHD-trait group showed significantly reduced theta power than the control group. In contrast, the ADHD-trait group exhibited an increased alpha power compared to the control group with the 250-1000 ms interval after stimulus onset. In terms of the PLV, the ADHD-trait group showed significantly weaker theta phase synchrony and fewer connection numbers in frontal-occipital areas than the control group. In terms of the theta brain network, the ADHD-trait group showed a significantly lower clustering coefficient and longer characteristic path length than the control group for the theta band. The present results indicate that college students with ADHD traits have deficits in spatial working memory and that these abnormal activities in neural oscillation, functional connectivity, and the network may contribute to spatial working memory deficits.

In Quest of Pathognomonic/Endophenotypic Markers of Attention Deficit Hyperactivity Disorder (ADHD): Potential of EEG-Based Frequency Analysis and ERPs to Better Detect, Prevent and Manage ADHD

Attention deficit hyperactivity disorder (ADHD) is a chronic heritable developmental delay psychiatric disorder requiring chronic management, characterized by inattention, hyperactivity, hyperkinectivity and impulsivity. Subjective clinical evaluation still remains crucial in its diagnosis. Discussed are two key aspects in the “characterizing ADHD” and on the quest for objective “pathognomonic/endophenotypic diagnostic markers of ADHD”. The first aspect briefly revolves around issues related to identification of pathognomonic/endophenotypic diagnostic markers in ADHD. Issues discussed include changes in ADHD definition, remission/persistence and overlapping-symptoms cum shared-heritability with its co-morbid cross-border mental disorders. The second aspect discussed is neurobiological and EEG-based studies on ADHD. Given the neurobiological and temporal aspects of ADHD symptoms the electroencephalograph (EEG) like NeuralScan by Medeia appears as an appropriate tool. The EEGs appropriateness is further enhanced when coupled with suitable behavior/cognitive/motor/psychological tasks/paradigms yielding EEG-based markers like event-related-potential (ERPs like P3 amplitudes and latency), reaction time variability (RTV), Theta:Beta ratio (TBR) and sensorimotor rhythm (SMR). At present, these markers could potentially help in the neurobiological characterization of ADHD and either help in identifying or lay the groundwork for identifying pathognomonic and/or endophenotypic EEG-based markers enabling its diagnosis, treatment and management.

Artificial food coloring affects EEG power and ADHD symptoms in college students with ADHD: a pilot study

Objectives: Removing artificial food coloring (AFC) is a common dietary intervention for children with Attention-Deficit/Hyperactivity Disorder (ADHD), but has not been tested in young adults. This pilot study examined the effects of AFC on ADHD symptoms and electroencephalography (EEG) in college students with and without ADHD.Methods: At baseline, control and ADHD participants completed the Adult ADHD Self-Report Scale (ASRS), simple and complex attention measures, and resting-state EEG recordings. ADHD participants (n = 18) and a subset of controls (extended control group or EC, n = 11) avoided AFC in their diet for 2 weeks and then were randomized to a double-blind, placebo-controlled crossover challenge. Subjects received either 225 mg AFC disguised in chocolate cookies or placebo chocolate cookies for 3 days each week, with testing on the third day each week. Baseline comparisons were made using Student's t-test or Wilcoxon rank sum tests and challenge period analyses were run using General Linear Modeling.Results: The ADHD group had significantly greater scores on the ASRS (p < 0.001), confirming a symptom differential between groups; however, there were no differences in attentional measures or EEG at baseline. The AFC challenge resulted in an increase in posterior mean gamma power (p = 0.05), a decrease in posterior relative alpha power (p = 0.04), and a marginal increase in inattentive symptoms (p = 0.08) in the ADHD group. There were no effects of AFC in the EC group.Discussion: This study indicates that AFC exposure may affect brainwave activity and ADHD symptoms in college students with ADHD. Larger studies are needed to confirm these findings.

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.

EEG for Diagnosis of Adult ADHD: A Systematic Review With Narrative Analysis

BACKGROUND

Attention deficit hyperactivity disorder is a common neurodevelopmental disorder characterized by symptoms of inattention, hyperactivity and or impulsivity. Since the development of the concept, a reliable biomarker to aid diagnosis has been sought. One potential method is the use of electroencephalogram to measure neuronal activity. The aim of this review is to provide an up to date synthesis of the literature surrounding the potential use of electroencephalogram for diagnosis of attention deficit hyperactivity disorder in adulthood.

METHODS

A search of PsycINFO, PubMed, and EMBASE was undertaken in February 2019 for peer-reviewed articles exploring electroencephalogram patterns in adults (18 years with no upper limit) diagnosed with attention deficit hyperactivity disorder.

RESULTS

Differences in electroencephalogram activity are potentially unique to adult attention deficit hyperactivity disorder populations. Strongest support was derived for elevated levels of both absolute and relative theta power, alongside the observation that alpha activity is able to typically differentiate between adult attention deficit hyperactivity disorder and normative populations.

CONCLUSIONS

Electroencephalogram can have a use in clinical settings to aid adult attention deficit hyperactivity disorder diagnosis, but areas of inconsistency are apparent.

Multimodal alterations of directed connectivity profiles in patients with attention-deficit/hyperactivity disorders

Functional and effective connectivity measures for tracking brain region interactions that have been investigated using both electroencephalography (EEG) and magnetoencephalography (MEG) bringing up new insights into clinical research. However, the differences between these connectivity methods, especially at the source level, have not yet been systematically studied. The dynamic characterization of coherent sources and temporal partial directed coherence, as measures of functional and effective connectivity, were applied to multimodal resting EEG and MEG data obtained from 11 young patients (mean age 13.2 ± 1.5 years) with attention-deficit/hyperactivity disorder (ADHD) and age-matched healthy subjects. Additionally, machine-learning algorithms were applied to the extracted connectivity features to identify biomarkers differentiating the two groups. An altered thalamo-cortical connectivity profile was attested in patients with ADHD who showed solely information outflow from cortical regions in comparison to healthy controls who exhibited bidirectional interregional connectivity in alpha, beta, and gamma frequency bands. We achieved an accuracy of 98% by combining features from all five studied frequency bands. Our findings suggest that both types of connectivity as extracted from EEG or MEG are sensitive methods to investigate neuronal network features in neuropsychiatric disorders. The connectivity features investigated here can be further tested as biomarkers of ADHD.

Linking alpha oscillations, attention and inhibitory control in adult ADHD with EEG neurofeedback

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Resting alpha power is reduced in adult ADHD suggesting cortical hyper-activation.

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Adult ADHD patients successfully reduce alpha power during neurofeedback.

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A post-neurofeedback rebound normalizes alpha power in adult ADHD.

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Alpha power rebound correlates with improvement of inhibitory control in adult ADHD.

Abnormal patterns of electrical oscillatory activity have been repeatedly described in adult ADHD. In particular, the alpha rhythm (8–12 Hz), known to be modulated during attention, has previously been considered as candidate biomarker for ADHD. In the present study, we asked adult ADHD patients to self-regulate their own alpha rhythm using neurofeedback (NFB), in order to examine the modulation of alpha oscillations on attentional performance and brain plasticity. Twenty-five adult ADHD patients and 22 healthy controls underwent a 64-channel EEG-recording at resting-state and during a Go/NoGo task, before and after a 30 min-NFB session designed to reduce (desynchronize) the power of the alpha rhythm. Alpha power was compared across conditions and groups, and the effects of NFB were statistically assessed by comparing behavioral and EEG measures pre-to-post NFB. Firstly, we found that relative alpha power was attenuated in our ADHD cohort compared to control subjects at baseline and across experimental conditions, suggesting a signature of cortical hyper-activation. Both groups demonstrated a significant and targeted reduction of alpha power during NFB. Interestingly, we observed a post-NFB increase in resting-state alpha (i.e. rebound) in the ADHD group, which restored alpha power towards levels of the normal population. Importantly, the degree of post-NFB alpha normalization during the Go/NoGo task correlated with individual improvements in motor inhibition (i.e. reduced commission errors) only in the ADHD group. Overall, our findings offer novel supporting evidence implicating alpha oscillations in inhibitory control, as well as their potential role in the homeostatic regulation of cortical excitatory/inhibitory balance.

Event-Related Potential Analysis of ADHD and Control Adults During a Sustained Attention Task

Background. Event-related potentials (ERPs) of attention deficit hyperactivity disorder (ADHD) population have been extensively studied using the time-domain representation of signals but time-frequency domain techniques are less explored. Although, adult ADHD is a proven disorder, most of the electrophysiological studies have focused only on children with ADHD. Methods. ERP data of 35 university students with ADHD and 35 control adults were recorded during visual continuous performance task (CPT). Gray level co-occurrence matrix-based texture features were extracted from time-frequency (t-f) images of event-related EEG epochs. Different ERP components measures, that is, amplitudes and latencies corresponding to N1, N2, and P3 components were also computed relative to standard and target stimuli. Results. Texture analysis has shown that the mean value of contrast, dissimilarity, and difference entropy is significantly reduced in adults with ADHD than in control adults. The mean correlation and homogeneity in adults with ADHD were significantly increased as compared with control adults. ERP components analysis has reported that adults with ADHD have reduced N1 amplitude to target stimuli, reduced N2 and P3 amplitude to both standard and target stimuli than controls. Conclusions. The differences in texture features obtained from t-f images of ERPs point toward altered information processing in adults with ADHD during a cognitive task. Findings of reduction in N1, N2, and P3 components highlight deficits of early sensory processing, stimulus categorization, and attentional resources, respectively, in adults with ADHD.

Decreased resting gamma activity in adult attention deficit/hyperactivity disorder

Objectives: To delineate task-free gamma activity in adult ADHD and healthy control subjects based on high-density EEG recordings. Relationship of gamma activity with symptom severity was also examined, since gamma activity is considered to be an index of network functions in the brain that underlie higher-order cognitive processes.Methods: Spontaneous EEG was recorded in adult ADHD subjects (N = 42; 25 methylphenidate-naïve and 17 on methylphenidate treatment) and controls (N = 59) with eyes open. EEG absolute power gamma was investigated in the gamma₁ (30.25-39 Hz) and gamma₂ (39.25-48 Hz) frequency bands.Results: Gamma₁ and gamma₂ activity was diminished in ADHD compared with healthy control subjects. The difference between ADHD and controls was the most pronounced in the right centroparietal region for both gamma₁ and gamma₂. Inverse associations were found between gamma₁ and gamma₂ activity and ADHD symptoms in centroparietal scalp regions.Conclusions: Gamma activity is reduced in adult ADHD, and the reduction has a predominantly right centroparietal distribution. Our findings are consistent with childhood ADHD literature with respect to diminished posterior gamma activity in patients, which may reflect altered dorsal attention network functions. Gamma abnormalities might provide a link between neurophysiological functioning and neuropsychological deficiencies, thereby offering an opportunity to investigate the neurobiological mechanisms that underlie the clinical symptoms of ADHD.

Functional EEG connectivity is a neuromarker for adult attention deficit hyperactivity disorder symptoms

OBJECTIVE

Altered brain functional connectivity has been shown in youth with attention-deficit/hyperactivity disorder (ADHD). However, relatively little is known about functional connectivity in adult ADHD, and how it is linked with the heritability of ADHD.

METHODS

We measured eyes-open and eyes-closed resting electroencephalography (EEG) from 38 adults with ADHD, 45 1st degree relatives of people with ADHD and 51 healthy controls. Functional connectivity among all scalp channels was calculated using a weighted phase lag index for delta, theta, alpha, beta and gamma frequency bands. A machine learning analysis using penalized linear regression was used to identify if connectivity features (10,080 connectivity pairs) could predict ADHD symptoms. Furthermore, we examined if EEG connectivity could accurately classify participants into ADHD, 1st degree relatives and/or control groups.

RESULTS

Hyperactive symptoms were best predicted by eyes-open EEG connectivity in delta, beta and gamma bands. Inattentive symptoms were predicted by eyes-open EEG connectivity in delta, alpha and gamma bands, and eyes-closed EEG connectivity in delta and gamma bands. EEG connectivity features did not reliably classify participants into groups.

CONCLUSIONS

EEG connectivity may represent a neuromarker for ADHD symptoms.

SIGNIFICANCE

EEG connectivity may help elucidate the neural basis of adult ADHD symptoms.

EEG development in Attention Deficit Hyperactivity Disorder: From child to adult

OBJECTIVE

Attention Deficit Hyperactivity Disorder (ADHD) is one of the most common psychiatric disorders found in children. While an extensive literature has documented the EEG in this clinical population, few studies have investigated EEG throughout the lifespan in ADHD. This study aimed to investigate EEG maturational changes, in subjects with ADHD combined type, that spanned from childhood into adulthood.

METHOD

Twenty five male adults with ADHD were assessed between the ages of 8-12 years and again as adults. At both ages, an EEG was recorded during an eyes-closed resting period, and power estimates were calculated for relative delta, theta, alpha and beta.

RESULTS

At the childhood assessment, the ADHD subjects had elevated posterior delta. Relative theta was elevated, with diminished alpha activity across all sites. Significant maturational changes were observed, with reductions in the delta and theta bands, and increases in the alpha and beta bands across all electrodes. In adulthood, relative to controls, diminished frontal delta and elevated global theta activity were apparent.

CONCLUSIONS

Substantial developmental changes occurred in the EEG of these subjects. These results identify important issues when using EEG as part of the diagnosis for ADHD.

SIGNIFICANCE

This study is the first to explore EEG changes from childhood to adulthood over an 11 year period in the same subjects with ADHD.

Increased Beta Activity Links to Impaired Emotional Control in ADHD Adults With High IQ

OBJECTIVE

The present study investigated the neuropathology of everyday-life executive function (EF) deficits in adults with ADHD with high IQ.

METHOD

Forty adults with ADHD with an IQ ≥ 120 and 40 controls were recruited. Ecological EFs were measured, and eyes-closed Electroencephalograph (EEG) signals were recorded during a resting-state condition; EEG power and correlations with impaired EFs were analyzed.

RESULTS

Compared with controls, the ADHD group showed higher scores on all clusters of EF. The ADHD group showed globally increased theta, globally decreased alpha, and increased central beta activity. In the ADHD group, central beta power was significantly related to emotional control ratings, while no such correlation was evident in the control group.

CONCLUSION

The results suggest that resting-state beta activity might be involved in the neuropathology of emotional control in adults with ADHD with high IQ.

Decrypting the electrophysiological individuality of the human brain: Identification of individuals based on resting-state EEG activity

Biometric identification (BI) of individuals is a fast-growing field of research that is producing increasingly sophisticated applications in several spheres of everyday life. Previous magnetic resonance imaging (MRI) studies have demonstrated that based on the high inter-individual variability of brain structure and function, it is possible to identify individuals with high accuracy. Otherwise, there is the common belief that electroencephalographic (EEG) data recorded at the surface of the scalp are too noisy for identification purposes with a comparably high hit rate. In the present work, we compared BI quality (F1-scores, accuracy, sensitivity, and specificity) between different types of functional (instantaneous, lagged, and total coherence, phase synchronization, correlation, and mutual information) and effective (Granger causality, phase synchronization, and coherence) connectivity measures. Results revealed that across functional connectivity metrics, identification accuracy was in the range of 0.98-1, whereas sensitivity and F1-scores were between 0.00 and 1 and specificity was between 0.99 and 1. BI was higher for the connectivity metrics that are contaminated by volume conduction (instantaneous connectivity) compared to those that are unaffected by this variable (lagged connectivity). Support vector machine and neural network algorithms yielded the highest BI, followed by random forest and weighted k-nearest neighborhood, whereas linear discriminant analysis was less accurate. These results provide cross-validated counterevidence to the belief that EEG data are too noisy for identification purposes and demonstrate that functional and effective connectivity metrics are particularly suited for BI applications with comparable accuracy to MRI. Our results have important implications for fast, low-cost, and mobile BI applications.