Altered EEG spectral power during rest and cognitive performance: a comparison of preterm-born adolescents to adolescents 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.

Comparison of comprehensive quantitative EEG metrics between typically developing boys and girls in resting state eyes-open and eyes-closed conditions

Introduction

A majority of published studies comparing quantitative EEG (qEEG) in typically developing (TD) children and children with neurodevelopmental or psychiatric disorders have used a control group (e.g., TD children) that combines boys and girls. This suggests a widespread supposition that typically developing boys and girls have similar brain activity at all locations and frequencies, allowing the data from TD boys and girls to be aggregated in a single group.

Methods

In this study, we have rigorously challenged this assumption by performing a comprehensive qEEG analysis on EEG recoding of TD boys (n = 84) and girls (n = 62), during resting state eyes-open and eyes-closed conditions (EEG recordings from Child Mind Institute's Healthy Brain Network (HBN) initiative). Our qEEG analysis was performed over narrow-band frequencies (e.g., separating low α from high α, etc.), included sex, age, and head size as covariates in the analysis, and encompassed computation of a wide range of qEEG metrics that included both absolute and relative spectral power levels, regional hemispheric asymmetry, and inter- and intra-hemispheric magnitude coherences as well as phase coherency among cortical regions. We have also introduced a novel compact yet comprehensive visual presentation of the results that allows comparison of the qEEG metrics of boys and girls for the entire EEG locations, pairs, and frequencies in a single graph.

Results

Our results show there are wide-spread EEG locations and frequencies where TD boys and girls exhibit differences in their absolute and relative spectral powers, hemispheric power asymmetry, and magnitude coherence and phase synchrony.

Discussion

These findings strongly support the necessity of including sex, age, and head size as covariates in the analysis of qEEG of children, and argue against combining data from boys and girls. Our analysis also supports the utility of narrow-band frequencies, e.g., dividing α, β, and γ band into finer sub-scales. The results of this study can serve as a comprehensive normative qEEG database for resting state studies in children containing both eyes open and eyes closed paradigms.

Altered temporal connectivity and reduced meta-state dynamism in adolescents born very preterm

Adolescents born very preterm have an increased risk for anxiety, social difficulties and inattentiveness, i.e. the 'preterm behavioural phenotype'. The extreme end of these traits comprises the core diagnostic features of attention and hyperactivity disorders and autism spectrum disorder, which have been reported to show aberrant dynamic resting-state functional network connectivity. This study aimed to compare this dynamism between adolescents born very preterm and controls. A resting-state functional magnetic resonance imaging was performed on 24 adolescents born very preterm (gestational age <32 weeks and/or birth weight ≤1500 g) and 32 controls born full term (≥37 weeks of gestation) at 13 years of age. Group-wise comparisons of dynamic connectivity between the resting-state networks were performed using both hard clustering and meta-state analysis of functional network connectivity. The very preterm group yielded a higher fraction of time spent in the least active connectivity state in hard clustering state functional network connectivity, even though no group differences in pairwise connectivity patterns were discovered. The meta-state analysis showed a decreased fluidity and dynamic range in the very preterm group compared with controls. Our results suggest that the 13-year-old adolescents born very preterm differ from controls in the temporal characteristics of functional connectivity. The findings may reflect the long-lasting effects of prematurity and the clinically acknowledged 'preterm behavioural phenotype'.

Abnormal Brain Oscillations in Developmental Disorders: Application of Resting State EEG and MEG in Autism Spectrum Disorder and Fragile X Syndrome

Autism Spectrum Disorder (ASD) and Fragile X Syndrome (FXS) are neurodevelopmental disorders with similar clinical and behavior symptoms and partially overlapping and yet distinct neurobiological origins. It is therefore important to distinguish these disorders from each other as well as from typical development. Examining disruptions in functional connectivity often characteristic of neurodevelopment disorders may be one approach to doing so. This review focuses on EEG and MEG studies of resting state in ASD and FXS, a neuroimaging paradigm frequently used with difficult-to-test populations. It compares the brain regions and frequency bands that appear to be impacted, either in power or connectivity, in each disorder; as well as how these abnormalities may result in the observed symptoms. It argues that the findings in these studies are inconsistent and do not fit neatly into existing models of ASD and FXS, then highlights the gaps in the literature and recommends future avenues of inquiry.

Task-Rate-Related Neural Dynamics Using Wireless EEG to Assist Diagnosis and Intervention Planning for Preschoolers with ADHD Exhibiting Heterogeneous Cognitive Proficiency

This study used a wireless EEG system to investigate neural dynamics in preschoolers with ADHD who exhibited varying cognitive proficiency pertaining to working memory and processing speed abilities. Preschoolers with ADHD exhibiting high cognitive proficiency (ADHD-H, n = 24), those with ADHD exhibiting low cognitive proficiency (ADHD-L, n = 18), and preschoolers with typical development (TD, n = 31) underwent the Conners’ Kiddie Continuous Performance Test and wireless EEG recording under different conditions (rest, slow-rate, and fast-rate task). In the slow-rate task condition, compared with the TD group, the ADHD-H group manifested higher delta and lower beta power in the central region, while the ADHD-L group manifested higher parietal delta power. In the fast-rate task condition, in the parietal region, ADHD-L manifested higher delta power than those in the other two groups (ADHD-H and TD); additionally, ADHD-L manifested higher theta as well as lower alpha and beta power than those with ADHD-H. Unlike those in the TD group, the delta power of both ADHD groups was enhanced in shifting from rest to task conditions. These findings suggest that task-rate-related neural dynamics contain specific neural biomarkers to assist clinical planning for ADHD in preschoolers with heterogeneous cognitive proficiency. The novel wireless EEG system used was convenient and highly suitable for clinical application.

Neurological state changes indicative of ADHD in children learned via EEG-based LSTM networks

Attention-deficit/hyperactivity disorder (ADHD) is a neurodevelopmental disorder that pervasively interferes with the lives of individuals starting in childhood.

OBJECTIVE

To address the subjectivity of current diagnostic approaches, many studies have been dedicated to efforts to identify the differences between ADHD and neurotypical (NT) individuals using EEG and continuous performance tests (CPT).

APPROACH

In this study, we proposed EEG-based long short-term memory (LSTM) networks that utilize deep learning techniques with learning the cognitive state transition to discriminate between ADHD and NT children via EEG signal processing. A total of thirty neurotypical children and thirty ADHD children participated in CPT tests while being monitored with EEG. Several architectures of deep and machine learning were applied to three EEG data segments including resting state, cognitive execution, and a period containing a fusion of those.

MAIN RESULTS

The experimental results indicated that EEG-based LSTM networks produced the best performance with an average accuracy of 90.50 ± 0.81 % in comparison with the deep neural networks, the convolutional neural networks, and the support vector machines with learning the cognitive state transition of EEG data. Novel observations of individual neural markers showed that the beta power activity of the O1 and O2 sites contributed the most to the classifications, subjects exhibited decreased beta power in the ADHD group, and had larger decreases during cognitive execution.

SIGNIFICANCE

These findings showed that the proposed EEG-based LSTM networks are capable of extracting the varied temporal characteristics of high-resolution electrophysiological signals to differentiate between ADHD and NT children, and brought a new insight to facilitate the diagnosis of ADHD. The registration numbers of the institutional review boards are 16MMHIS021 and EC1070401-F.

Associations of Hyperactivity and Inattention Scores with Theta and Beta Oscillatory Dynamics of EEG in Stop-Signal Task in Healthy Children 7-10 Years Old

Simple Summary

Most studies on ADHD have been focused on the comparisons between healthy subjects and clinical patients. The dimensional approaches propose that the main pathological behavioral domains are distributed in the normal population and not only in individual categories of people (as assumed in traditional schemes of comparisons between patients and controls). In the current study, we used a similar approach to identify potential markers of ADHD by studying the EEG dynamics of healthy children with a natural variability in hyperactivity and inattention scores during performance of the Stop-Signal task. We found that hyperactivity/inattention scores were positively associated with RT variability. Hyperactivity/inattention scores were negatively associated with an increase in beta spectral power in the first 200 ms and positively associated with an increase in theta rhythm at about 300 ms after presentation of the Go stimulus. It has been hypothesized that such results imply insufficient vigilance in the early stages of perception and subsequent compensatory enhancing of attention to the stimulus in children with higher hyperactivity and inattention scores.

Abstract

In the current study, we aimed to investigate the associations between the natural variability in hyperactivity and inattention scores, as well as their combination with EEG oscillatory responses in the Stop-Signal task in a sample of healthy children. During performance, the Stop-Signal task EEGs were recorded in 94 Caucasian children (40 girls) from 7 to 10 years. Hyperactivity/inattention and inattention scores positively correlated with RT variability. Hyperactivity/inattention and inattention scores negatively correlated with an increase in beta spectral power in the first 200 ms after presentation of the Go stimulus. Such results are in line with the lack of arousal model in ADHD children and can be associated with less sensory arousal in the early stages of perception in children with symptoms of inattention. The subsequent greater increase in theta rhythm at about 300 ms after presentation of the Go stimulus in children with higher inattention scores may be associated with increased attention processes and compensation for insufficient vigilance in the early stages of perception.

Clinical Application of Combined EEG-qEEG Functional Neuroimaging in the Practice of Pediatric Neuroscience: A Personal Perspective

This brief article is an overview of my personal experience over the past almost 10 years of the clinical use of EEG and quantitative EEG (qEEG) functional neuroimaging in a busy pediatric neurology practice. The concomitant use of surface EEG and functional electromagnetic EEG neuroimaging/qEEG in clinical practice provides significant additional clinical and neurophysiologic information. The qEEG is a noninvasive, inexpensive, portable technique with high temporal resolution (milliseconds) and improving spatial resolution (down to 3 mm³) and is an appropriate and validated tool for investigation of abnormal brain dynamics and connectivity of neuronal networks in clinical disorders of the brain. This article describes the daily applicability and utility of this modality in assisting diagnosis and clinical management of patients with a wide variety of presenting symptoms, including headaches, tics, autism spectrum disorder, inattention, sleep dysregulation, anxiety, and depression. The ease of data acquisition and analysis in clinical practices, coupled with skilled interpretation and clinical application, makes this tool one of the most valuable clinical tools to complement a thorough history and examination process.

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.

Frequency coupling of low and high frequencies in the EEG of ADHD children and adolescents in closed and open eyes conditions

The present report examines the possible differences in absolute Power Spectral Density (PSD), the topography of brain rhythms, and low frequency (delta and theta) vs. beta PSD when attention deficit disorder (ADHD) children and controls are compared. These results would potentially be useful to test the validity of the developmental lag and differential developmental models for ADHD. The EEG resting state under the experimental conditions of open and closed eyes were recorded in samples of control subjects and children with ADHD (6-17 years old). The PSD from 0 to 46 Hz was calculated and ANOVAs were performed to compare the groups of subjects in the two experimental conditions. To observe differences in the co-maturation of the brain rhythms between the groups of subjects, correlations of the PSD of all frequency ranges were computed. These results showed an increase in delta power in children with ADHD compared to control subjects. The topographies of the different brain rhythms were similar in children with ADHD and controls. The maturational power-to-power frequency-coupling between low frequencies and beta rhythms was lower in children with ADHD. The increased delta PSD in ADHD and the similar brain rhythms topographies in children with ADHD and controls support the developmental lag model, whereas the decreased co-maturation of low frequencies vs. beta PSD in children with ADHD suggests a differential maturation rate for low and beta frequencies in children with ADHD compared to controls.

EEG profiles and associated neurodevelopmental outcomes after very preterm birth

OBJECTIVES

To assess brain oscillations in very preterm and full-term born adolescents and explore subgroups based on integrative patterns of brain oscillations with different frequencies. Additionally, subgroups were related to functional outcomes and very preterm birth.

METHODS

A Dutch cohort of 53 very preterm and 61 full-term born adolescents aged 13 years participated. Resting-state electroencephalography was recorded. Absolute and relative delta, theta, alpha, and beta power were compared between groups. Latent class analysis (LCA) was used to identify subgroups with distinct activity patterns and to relate these patterns to intelligence, academic performance, motor skills, and very preterm birth.

RESULTS

Very preterm adolescents exhibited decreased relative beta activity. LCA with four classes showed the best model fit. The class with the highest level of delta and lowest levels of theta, alpha, and beta power was associated with lowest intelligence, academic, and motor estimates. Very preterm born adolescents were more likely than controls to be members of this class.

CONCLUSION

Very preterm born adolescents showed altered oscillatory activity, indicating long-lasting effects of very preterm birth on brain functioning. Distinct activity patterns were associated with both functional outcomes and very preterm birth.

SIGNIFICANCE

Specific patterns of brain oscillations may serve as biomarkers for poor functional outcome after very preterm birth.

EEG Frequency Bands in Psychiatric Disorders: A Review of Resting State Studies

A significant proportion of the electroencephalography (EEG) literature focuses on differences in historically pre-defined frequency bands in the power spectrum that are typically referred to as alpha, beta, gamma, theta and delta waves. Here, we review 184 EEG studies that report differences in frequency bands in the resting state condition (eyes open and closed) across a spectrum of psychiatric disorders including depression, attention deficit-hyperactivity disorder (ADHD), autism, addiction, bipolar disorder, anxiety, panic disorder, post-traumatic stress disorder (PTSD), obsessive compulsive disorder (OCD) and schizophrenia to determine patterns across disorders. Aggregating across all reported results we demonstrate that characteristic patterns of power change within specific frequency bands are not necessarily unique to any one disorder but show substantial overlap across disorders as well as variability within disorders. In particular, we show that the most dominant pattern of change, across several disorder types including ADHD, schizophrenia and OCD, is power increases across lower frequencies (delta and theta) and decreases across higher frequencies (alpha, beta and gamma). However, a considerable number of disorders, such as PTSD, addiction and autism show no dominant trend for spectral change in any direction. We report consistency and validation scores across the disorders and conditions showing that the dominant result across all disorders is typically only 2.2 times as likely to occur in the literature as alternate results, and typically with less than 250 study participants when summed across all studies reporting this result. Furthermore, the magnitudes of the results were infrequently reported and were typically small at between 20% and 30% and correlated weakly with symptom severity scores. Finally, we discuss the many methodological challenges and limitations relating to such frequency band analysis across the literature. These results caution any interpretation of results from studies that consider only one disorder in isolation, and for the overall potential of this approach for delivering valuable insights in the field of mental health.

Neuropsychological and Neurophysiological Indicators of General and Food-Specific Impulsivity in Children with Overweight and Obesity: A Pilot Study

Impulsivity, particularly towards food, is a potential risk factor for increased energy intake and the development and maintenance of obesity in children. However, neuropsychological and neurophysiological indicators of general and food-specific impulsivity and their association with children's weight status are poorly understood. This pilot study examined electroencephalography (EEG) frequency band profiles during eyes-closed and eyes-open resting state in n = 12 children with overweight or obesity versus n = 22 normal-weight controls and their link to child- and parent-reported and experimentally assessed impulsivity of children (e.g., risk-taking behavior, approach-avoidance behavior towards food). The main results indicated that children with overweight/obesity versus normal weight showed significantly increased delta and decreased alpha band activity during eyes-closed resting state. Across the total sample, EEG slow-wave band activity was particularly linked to self- and parent-reported impulsivity and greater risk-taking behavior, but not to approach behavior towards food, after controlling for children's age and weight status. The identification of specific EEG patterns in children with excess weight may provide a new basis for developing neurophysiological diagnostic and treatment approaches for childhood obesity. Future studies with larger samples and longitudinal designs are needed to replicate the present findings and test their stability over time.

EEG Dynamics of a Go/Nogo Task in Children with ADHD

Background: Studies investigating event-related potential (ERP) evoked in a Cue-Go/NoGo paradigm have shown lower frontal N1, N2 and central P3 in children with attention-deficit/hyperactivity disorder (ADHD) compared to typically developing children (TDC). However, the electroencephalographic (EEG) dynamics underlying these ERPs remain largely unexplored in ADHD. Methods: We investigate the event-related spectral perturbation and inter-trial coherence linked to the ERP triggered by visual Cue-Go/NoGo stimuli, in 14 children (7 ADHD and 7 TDC) aged 8 to 12 years. Results: Compared to TDC, the EEG dynamics of children with ADHD showed a lower theta-alpha ITC concomitant to lower occipito-parietal P1-N2 and frontal N1-P2 potentials in response to Cue, Go and Nogo stimuli; an upper alpha power preceding lower central Go-P3; a lower theta-alpha power and ITC were coupled to a lower frontal Nogo-N3; a lower low-gamma power overall scalp at 300 ms after Go and Nogo stimuli. Conclusion: These findings suggest impaired ability in children with ADHD to conserve the brain oscillations phase associated with stimulus processing. This physiological trait might serve as a target for therapeutic intervention or be used as monitoring of their effects.