Quantitative EEG in Children and Adults With Attention Deficit Hyperactivity Disorder: Comparison of Absolute and Relative Power Spectra and Theta/Beta Ratio

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.

Geraniol mitigates anxiety-like behaviors in rats by reducing oxidative stress, repairing impaired hippocampal neurotransmission, and normalizing brain cortical-EEG wave patterns after a single electric foot-shock exposure

Anxiety-like conditions can interfere with daily activities as the adaptive mechanism fails to cope with stress. These conditions are often linked with increased oxidative stress, and abrupt neurotransmission and electroencephalography (EEG) wave pattern. Geraniol, a monoterpenoid, has antioxidant and anti-inflammatory activities, as well as brain-calming effects. Therefore, in this study, geraniol was tested for the potential anxiolytic effects in a rat model of anxiety. The rats were exposed to an electric foot shock (1 mA for 1 s) to develop anxiety-like symptoms. Treatment was carried out using geraniol (10 and 30 mg/kg) and the standard diazepam drug. The behavior of the rats was analyzed using the open field test, light-dark test, and social interaction test. Afterward, the rats were decapitated to collect samples for neurochemical and biochemical analyses. The cortical-EEG wave pattern was also obtained. The study revealed that the electric foot shock induced anxiety-like symptoms, increased oxidative stress, and altered hippocampal neurotransmitter levels. The power of low-beta and high-beta was amplified with the increased coupling of delta-beta waves in anxiety group. However, the treatment with geraniol and diazepam normalized cortical-EEG wave pattern and hippocampal serotonin and catecholamines profile which was also reflected by reduced anxious behavior and normalized antioxidant levels. The study reports an anxiolytic potential of geraniol, which can be further explored in future.

Challenging the Diagnostic Value of Theta/Beta Ratio: Insights From an EEG Subtyping Meta-Analytical Approach in ADHD

The frequently reported high theta/beta ratio (TBR) in the electroencephalograms (EEGs) of children with attention-deficit/hyperactivity disorder (ADHD) has been suggested to include at least two distinct neurophysiological subgroups, a subgroup with high TBR and one with slow alpha peak frequency, overlapping the theta range. We combined three large ADHD cohorts recorded under standardized procedures and used a meta-analytical approach to leverage the large sample size (N = 417; age range: 6-18 years), classify these EEG subtypes and investigate their behavioral correlates to clarify their brain-behavior relationships. To control for the fact that slow alpha might contribute to theta power, three distinct EEG subgroups (non-slow-alpha TBR (NSAT) subgroup, slow alpha peak frequency (SAF) subgroup, not applicable (NA) subgroup) were determined, based on a halfway cut-off in age- and sex-normalized theta and alpha, informed by previous literature. For the meta-analysis, Cohen's d was calculated to assess the differences between EEG subgroups for baseline effects, using means and standard deviations of baseline inattention and hyperactivity-impulsivity scores. Non-significant, small Grand Mean effect sizes (-0.212 < d < 0.218) were obtained when comparing baseline behavioral scores between the EEG subgroups. This study could not confirm any association of EEG subtype with behavioral traits. This confirms previous findings suggesting that TBR has no diagnostic value for ADHD. TBR could, however, serve as an aid to stratify patients between neurofeedback protocols based on baseline TBR. A free online tool was made available for clinicians to calculate age- and sex-corrected TBR decile scores (Brainmarker-IV) for stratification of neurofeedback protocols.

Aperiodic and periodic components of oscillatory brain activity in relation to cognition and symptoms in pediatric ADHD

Children with attention-deficit/hyperactivity disorder show deficits in processing speed, as well as aberrant neural oscillations, including both periodic (oscillatory) and aperiodic (1/f-like) activity, reflecting the pattern of power across frequencies. Both components were suggested as underlying neural mechanisms of cognitive dysfunctions in attention-deficit/hyperactivity disorder. Here, we examined differences in processing speed and resting-state-Electroencephalogram neural oscillations and their associations between 6- and 12-year-old children with (n = 33) and without (n = 33) attention-deficit/hyperactivity disorder. Spectral analyses of the resting-state EEG signal using fast Fourier transform revealed increased power in fronto-central theta and beta oscillations for the attention-deficit/hyperactivity disorder group, but no differences in the theta/beta ratio. Using the parameterization method, we found a higher aperiodic exponent, which has been suggested to reflect lower neuronal excitation-inhibition, in the attention-deficit/hyperactivity disorder group. While fast Fourier transform-based theta power correlated with clinical symptoms for the attention-deficit/hyperactivity disorder group only, the aperiodic exponent was negatively correlated with processing speed across the entire sample. Finally, the aperiodic exponent was correlated with fast Fourier transform-based beta power. These results highlight the different and complementary contribution of periodic and aperiodic components of the neural spectrum as metrics for evaluation of processing speed in attention-deficit/hyperactivity disorder. Future studies should further clarify the roles of periodic and aperiodic components in additional cognitive functions and in relation to clinical status.

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.

Novel pharmacological targets for GABAergic dysfunction in ADHD

Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopment disorder that affects approximately 5% of the population. The disorder is characterized by impulsivity, hyperactivity, and deficits in attention and cognition, although symptoms vary across patients due to the heterogenous and polygenic nature of the disorder. Stimulant medications are the standard of care treatment for ADHD patients, and their effectiveness has led to the dopaminergic hypothesis of ADHD in which deficits in dopaminergic signaling, especially in cortical brain regions, mechanistically underly ADHD pathophysiology. Despite their effectiveness in many individuals, almost one-third of patients do not respond to stimulant treatments and the long-term negative side effects of these medications remain unclear. Emerging clinical evidence is beginning to highlight an important role of dysregulated excitatory/inhibitory (E/I) balance in ADHD. These deficits in E/I balance are related to functional abnormalities in glutamate and Gamma-Aminobutyric Acid (GABA) signaling in the brain, with increasing emphasis placed on GABAergic interneurons driving specific aspects of ADHD pathophysiology. Recent genome-wide association studies (GWAS) have also highlighted how genes associated with GABA function are mutated in human populations with ADHD, resulting in the generation of several new genetic mouse models of ADHD. This review will discuss how GABAergic dysfunction underlies ADHD pathophysiology, and how specific receptors/proteins related to GABAergic interneuron dysfunction may be pharmacologically targeted to treat ADHD in subpopulations with specific comorbidities and symptom domains. This article is part of the Special Issue on "PFC circuit function in psychiatric disease and relevant models".

Tools for the Diagnosis of ADHD in Children and Adolescents: A Systematic Review

CONTEXT

Correct diagnosis is essential for the appropriate clinical management of attention-deficit/hyperactivity disorder (ADHD) in children and adolescents.

OBJECTIVE

This systematic review provides an overview of the available diagnostic tools.

DATA SOURCES

We identified diagnostic accuracy studies in 12 databases published from 1980 through June 2023.

STUDY SELECTION

Any ADHD tool evaluation for the diagnosis of ADHD, requiring a reference standard of a clinical diagnosis by a mental health specialist.

DATA EXTRACTION

Data were abstracted and critically appraised by 1 reviewer and checked by a methodologist. Strength of evidence and applicability assessments followed Evidence-based Practice Center standards.

RESULTS

In total, 231 studies met eligibility criteria. Studies evaluated parental ratings, teacher ratings, youth self-reports, clinician tools, neuropsychological tests, biospecimen, EEG, and neuroimaging. Multiple tools showed promising diagnostic performance, but estimates varied considerably across studies, with a generally low strength of evidence. Performance depended on whether ADHD youth were being differentiated from neurotypically developing children or from clinically referred children.

LIMITATIONS

Studies used different components of available tools and did not report sufficient data for meta-analytic models.

CONCLUSIONS

A valid and reliable diagnosis of ADHD requires the judgment of a clinician who is experienced in the evaluation of youth with and without ADHD, along with the aid of standardized rating scales and input from multiple informants across multiple settings, including parents, teachers, and youth themselves.

Adult ADHD: it is old and new at the same time - what is it?

Even though the number of studies aiming to improve comprehension of ADHD pathology has increased in recent years, there still is an urgent need for more effective studies, particularly in understanding adult ADHD, both at preclinical and clinical levels, due to the increasing evidence that adult ADHD is highly distinct and a different entity from childhood ADHD. This review paper outlines the symptoms, diagnostics, and neurobiological mechanisms of ADHD, with emphasis on how adult ADHD could be different from childhood-onset. Data show a difference in the environmental, genetic, epigenetic, and brain structural changes, when combined, could greatly impact the behavioral presentations and the severity of ADHD in adults. Furthermore, a crucial aspect in the quest to fully understand this disorder could be through longitudinal analysis. In this way, we will determine if and how the pathology and pharmacology of ADHD change with age. This goal could revolutionize our understanding of the disorder and address the weaknesses in the current clinical classification systems, improving the characterization and validity of ADHD diagnosis, specifically those in adults.

Characteristics of ADHD Symptoms and EEG Theta/Beta Ratio in Children With Sleep Disordered Breathing

Objectives. This study aimed to explore parent-reported symptoms of attention deficit-hyperactivity disorder (ADHD) and sleep electroencephalogram (EEG) theta/beta ratio (TBR) characteristics in children with sleep disordered breathing (SDB). Methods. The parents of children (aged 6-11 years) with SDB (n = 103) and healthy controls (n = 28) completed the SNAP-IV questionnaire, and children underwent overnight polysomnography. Children with SDB were grouped according to obstructive apnea/hypopnea index: primary snoring, mild, and moderate-severe obstructive sleep apnea (OSA) groups. The TBR in non-rapid eye movement (NREM) periods in three sleep cycles was analyzed. Results. Children with SDB showed worse ADHD symptoms compared with the healthy control. There was no intergroup difference in TBR. The time-related decline in TBR observed in the control, primary snoring and mild OSA groups, which was not observed in the moderate-severe OSA group. Overnight transcutaneous oxygen saturation was negatively associated with the hyperactivity/impulsivity score of ADHD symptom. The global TBR during the NREM period in the first sleep cycle was positively correlated with inattention score. Conclusion. Children with SDB showed more ADHD inattention symptoms than the healthy control. Although we found no difference in TBR among groups, we found significant main effect for NREM period. There existed a relationship between hypoxia, TBR, and scores of ADHD symptoms. Hence, it was speculated that TBR can reflect the nocturnal electrophysiological manifestations in children with SDB, which may be related to daytime ADHD symptoms.

Variations in Theta/Beta Ratio and Cognitive Performance in Subpopulations of Subjects with ADHD Symptoms: Towards Neuropsychological Profiling for Patient Subgrouping

ADHD is a neurodevelopmental disorder appearing in childhood but remaining in many cases in adults. There are both pharmacological and non-pharmacological approaches to treating ADHD, but they do not have the same efficacy in all subjects. Better knowledge of the neurophysiological basis of this disorder will allow for the design of more effective treatments. Studies performing qEEG analysis in children suggest the existence of subgroups of ADHD patients with different neurophysiological traits. There are fewer studies in adults, who might have undergone plastic changes allowing them to cope with ADHD symptoms along with brain maturation. Herein, we study cognitive performance and the theta/beta ratio in young adults with ADHD symptoms. We found that subjects with ADHD symptoms and low working memory performance (n = 30) present higher theta/beta ratios than controls (n = 40) at O2 and T6 in the eyes-closed condition, as well as a tendency toward a higher theta/beta ratio at O1 and Cz. Subjects with ADHD and high working memory performance (n = 50) do not differ from the controls in their theta/beta ratios at any derivation. Our results suggest that neuropsychological profiling could be useful for patient subgrouping. Further research will allow for the distinction of neuropsychological profiles and their neurophysiological correlates, leading to a better classification of ADHD subtypes, thus improving treatment selection.

Electroencephalogram (EEG) based prediction of attention deficit hyperactivity disorder (ADHD) using machine learning

"Attention-Deficit Hyperactivity Disorder (ADHD)" is a neuro-developmental disorder in children under 12 years old. Learning deficits, anxiety, depression, sensory processing disorder, and oppositional defiant disorder are the most frequent comorbidities of ADHD. This research focuses on ADHD in children, considering its common occurrence and frequent coexistence with other mental disorders. The study utilizes the resting-state open-eye "Electroencephalogram" (EEG) signals of 61 children with ADHD and 60 healthy children. Morphological and "Power Spectral Density" (PSD) features associated with ADHD are analysed and "Principal Component Analysis" (PCA) is employed to reduce data dimensionality. Classification algorithms including AdaBoost, "K-Nearest Neighbour" (KNN) classifier, Naive Bayes, and random forest are utilized, with the Bernoulli Naive Bayes classifier achieving the highest accuracy of 96%. This study found some relevant characteristics for classification at the frontal (F), central (C), and parietal (P) electrode placement sites. Finally, this reveals distinct EEG patterns in children with ADHD and the study provides a potential supplementary method for ADHD diagnosis.

Transcranial random noise stimulation combined with cognitive training for treating ADHD: a randomized, sham-controlled clinical trial

Non-invasive brain stimulation has been suggested as a potential treatment for improving symptomology and cognitive deficits in Attention-Deficit/Hyperactivity Disorder (ADHD), the most common childhood neurodevelopmental disorder. Here, we examined whether a novel form of stimulation, high-frequency transcranial random noise stimulation (tRNS), applied with cognitive training (CT), may impact symptoms and neural oscillations in children with ADHD. We conducted a randomized, double-blind, sham-controlled trial in 23 unmedicated children with ADHD, who received either tRNS over the right inferior frontal gyrus (rIFG) and left dorsolateral prefrontal cortex (lDLPFC) or sham stimulation for 2 weeks, combined with CT. tRNS + CT yielded significant clinical improvements (reduced parent-reported ADHD rating-scale scores) following treatment, compared to the control intervention. These improvements did not change significantly at a 3-week follow-up. Moreover, resting state (RS)-EEG periodic beta bandwidth of the extracted peaks was reduced in the experimental compared to control group immediately following treatment, with further reduction at follow-up. A lower aperiodic exponent, which reflects a higher cortical excitation/inhibition (E/I) balance and has been related to cognitive improvement, was seen in the experimental compared to control group. This replicates previous tRNS findings in adults without ADHD but was significant only when using a directional hypothesis. The experimental group further exhibited longer sleep onset latencies and more wake-up times following treatment compared to the control group. No significant group differences were seen in executive functions, nor in reported adverse events. We conclude that tRNS + CT has a lasting clinical effect on ADHD symptoms and on beta activity. These results provide a preliminary direction towards a novel intervention in pediatric ADHD.

EEG repetition and change detection responses in infancy predict adaptive functioning in preschool age: a longitudinal study

Neurodevelopmental disorders (NDDs) are mostly diagnosed around the age of 4-5 years, which is too late considering that the brain is most susceptive to interventions during the first two years of life. Currently, diagnosis of NDDs is based on observed behaviors and symptoms, but identification of objective biomarkers would allow for earlier screening. In this longitudinal study, we investigated the relationship between repetition and change detection responses measured using an EEG oddball task during the first year of life and at two years of age, and cognitive abilities and adaptive functioning during preschool years (4 years old). Identification of early biomarkers is challenging given that there is a lot of variability in developmental courses among young infants. Therefore, the second aim of this study is to assess whether brain growth is a factor of interindividual variability that influences repetition and change detection responses. To obtain variability in brain growth beyond the normative range, infants with macrocephaly were included in our sample. Thus, 43 normocephalic children and 20 macrocephalic children were tested. Cognitive abilities at preschool age were assessed with the WPPSI-IV and adaptive functioning was measured with the ABAS-II. Time-frequency analyses were conducted on the EEG data. Results indicated that repetition and change detection responses in the first year of life predict adaptive functioning at 4 years of age, independently of head circumference. Moreover, our findings suggested that brain growth explains variability in neural responses mostly in the first years of life, so that macrocephalic children did not display repetition suppression responses, while normocephalic children did. This longitudinal study demonstrates that the first year of life is an important period for the early screening of children at risk of developing NDDs.

Quantitative assessment of cognitive profile and brain asymmetry in the characterization of autism spectrum in children: A task-based EEG study

Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by learning, attention, social, communication, and behavioral impairments. Each person with Autism has a different severity and level of brain functioning, ranging from high functioning (HF) to low functioning (LF), depending on their intellectual/developmental abilities. Identifying the level of functionality remains crucial in understanding the cognitive abilities of Autistic children. Assessment of EEG signals acquired during specific cognitive tasks is more appropriate in identifying brain functional and cognitive load variations. The spectral power of EEG sub-band frequency and parameters related to brain asymmetry has the potential to be employed as indices to characterize brain functioning. Thus, the objective of this work is to analyze the cognitive task-based electrophysiological variations in autistic and control groups, using EEG acquired during two well-defined protocols. Theta to Alpha ratio (TAR) and Theta to Beta ratio (TBR) of absolute powers of the respective sub-band frequencies have been estimated to quantify the cognitive load. The variations in interhemispheric cortical power measured by EEG were studied using the brain asymmetry index. For the arithmetic task, the TBR of the LF group was found to be considerably higher than the HF group. The findings reveal that the spectral powers of EEG sub-bands can be a key indicator in the assessment of high and low-functioning ASD to facilitate appropriate training strategies. Instead of depending solely on behavioral tests to diagnose autism, it could be a beneficial approach to use task-based EEG characteristics to differentiate between the LF and HF groups.

Dexmedetomidine alleviates host ADHD-like behaviors by reshaping the gut microbiota and reducing gut-brain inflammation

Attention-deficit/hyperactivity disorder (ADHD) is one of the most prevalent psychiatric disorders that affects children and even continues into adulthood. Dexmedetomidine (DEX), a short-term sedative, can selectively activate the α2-adrenoceptor. Treatment with α2-adrenergic agonists in patients with ADHD is becoming increasingly common. However, the therapeutic potential of DEX for the treatment of ADHD is unknown. Here, we evaluated the effect of DEX on ADHD-like behavior in spontaneously hypertensive rats (SHRs), a widely used animal model of ADHD. DEX treatment ameliorated hyperactivity and spatial working memory deficits and normalized θ electroencephalogram (EEG) rhythms in SHRs. We also found that DEX treatment altered the gut microbiota composition and promoted the enrichment of beneficial gut bacterial genera associated with anti-inflammatory effects in SHRs. The gut pathological scores and permeability and the level of inflammation observed in the gut and brain were remarkably improved after DEX administration. Moreover, transplantation of fecal microbiota from DEX-treated SHRs produced effects that mimicked the therapeutic effects of DEX administration. Therefore, DEX is a promising treatment for ADHD that functions by reshaping the composition of the gut microbiota and reducing inflammation in the gut and brain.

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.

Neurological Mechanisms of Diagnosis and Therapy in School Children with ADHD in Poland

The paper aims to present a holistic view of attention deficit hyperactivity disorder (ADHD) in pedagogical, psychological, legal, and social dimensions in Polish schools. The authors present the benefits of neurofeedback therapy for elementary school pupils. In order to verify the validity, the paper compares the concordance of a medical diagnosis confirming ADHD syndrome with the occurrence of abnormal electrical brain function recording and abnormalities therein as well as the effectiveness of the neurofeedback therapy. The study confirms that the reported problems faced by pupils and affecting their emotional functioning are reflected in their EEG records. Conclusions from the study lead to the proposal that the neurofeedback assessment should be performed at schools, which should result in the implementation of effective therapy. Moreover, the neurofeedback method should be promoted in Polish schools as an alternative to pharmacological therapy, which, as the research proves, is not always effective. Neurofeedback therapy, similarly to behavioral therapy, is very much needed and useful because it provides optimal conditions for the child’s development and shapes their relations with the environment effectively and harmlessly.

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).

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.

Machine learning models effectively distinguish attention-deficit/hyperactivity disorder using event-related potentials

Accurate diagnosis of Attention-Deficit/Hyperactivity Disorder (ADHD) is a significant challenge. Misdiagnosis has significant negative medical side effects. Due to the complex nature of this disorder, there is no computational expert system for diagnosis. Recently, automatic diagnosis of ADHD by machine learning analysis of brain signals has received an increased attention. This paper aimed to achieve an accurate model to discriminate between ADHD patients and healthy controls by pattern discovery. Event-Related Potentials (ERP) data were collected from ADHD patients and healthy controls. After pre-processing, ERP signals were decomposed and features were calculated for different frequency bands. The classification was carried out based on each feature using seven machine learning algorithms. Important features were then selected and combined. To find specific patterns for each model, the classification was repeated using the proposed patterns. Results indicated that the combination of complementary features can significantly improve the performance of the predictive models. The newly developed features, defined based on band power, were able to provide the best classification using the Generalized Linear Model, Logistic Regression, and Deep Learning with the average accuracy and Receiver operating characteristic curve > %99.85 and > 0.999, respectively. High and low frequencies (Beta, Delta) performed better than the mid, frequencies in the discrimination of ADHD from control. Altogether, this study developed a machine learning expert system that minimises misdiagnosis of ADHD and is beneficial for the evaluation of treatment efficacy.

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.

A Systematic Review of Sleep and Circadian Rhythms in Children with Attention Deficit Hyperactivity Disorder

OBJECTIVE

Children and adults with ADHD often report sleep disturbances that may form part of the etiology and/or symptomatology of ADHD. We review the evidence for sleep changes in children with ADHD.

METHODS

Systematic review with narrative synthesis assessing sleep and circadian function in children aged 5 to 13 years old with a diagnosis of ADHD.

RESULTS

148 studies were included for review, incorporating data from 42,353 children. We found that sleep disturbances in ADHD are common and that they may worsen behavioral outcomes; moreover, sleep interventions may improve ADHD symptoms, and pharmacotherapy for ADHD may impact sleep.

CONCLUSION

Sleep disturbance may represent a clinically important feature of ADHD in children, which might be therapeutically targeted in a useful way. There are a number of important gaps in the literature. We set out a manifesto for future research in the area of sleep, circadian rhythms, and ADHD.

P300 Modulation via Transcranial Alternating Current Stimulation in Adult Attention-Deficit/Hyperactivity Disorder: A Crossover Study

OBJECTIVE

A repeated finding regarding event-related potentials (ERPs) is that patients with ADHD show a reduced P300 amplitude. This raises the question of whether the attention of ADHD patients can be increased by stabilizing the P300. Assuming that the P300 is generated by event-related oscillations (EROs) in the low frequency range (0-8 Hz), one approach to increase the P300 could be to stimulate the patient's P300 underlying ERO by means of transcranial alternating current stimulation (tACS). The aim of this follow-up study was to investigate this hypothesized mechanism of action in adult ADHD patients.

MATERIALS AND METHODS

Undergoing a crossover design, 20 adult ADHD patients (10 female) received an actual stimulation via tACS on one day and a sham stimulation on another day. Before and after each intervention, EEG characteristics (P300 amplitudes, low frequency power) and attention performances (d2 attention test, visual oddball task (VOT)) were recorded.

RESULTS

Electrophysiological analyses revealed no evidence for an enhanced P300 amplitude or low frequency power increase after actual stimulation compared to sham stimulation. Instead, a significant effect was found for a stronger N700 amplitude increase after actual stimulation compared to sham stimulation. Consistent with the P300 null results, none of the examined neuropsychological performance measures indicated a tACS-induced improvement in attentional ability.

CONCLUSION

Contrary to a previous study using tACS to modulate the P300 in adult ADHD patients, the current study yields no evidence that tACS can increase the P300 amplitude in adult ADHD patients and that such P300 enhancement can directly improve neuropsychological parameters of attention.

Characteristics of Attention-Deficit/Hyperactivity Disorder Subtypes in Children Classified Using Quantitative Electroencephalography

PURPOSE

This study used quantitative electroencephalography (QEEG) to investigate the characteristics of attention-deficit/hyperactivity disorder (ADHD) subtypes in children.

PATIENTS AND METHODS

There were 69 subjects (42 with ADHD and 27 neurotypical (NT)) in this study. A semi-structured interview was conducted with each participant for psychiatric diagnostic evaluation. We measured the absolute and relative power in 19 channels and analyzed QEEG using the following frequency ranges: delta (1-4 Hz), theta (4-8 Hz), alpha 1 (8-10 Hz), alpha 2 (10-12 Hz), beta 1 (12-15 Hz), beta 2 (15-20 Hz), beta 3 (20-30 Hz), and gamma (30-45 Hz). Group analyses and EEG noise preprocessing were conducted using iSyncBrain, a cloud-based, artificial intelligence EEG analysis platform. Analysis of covariance adjusted for IQ, age, and sex was used.

RESULTS

QEEG analysis revealed three ADHD subtypes, characterized by (A) elevated relative fast alpha and beta power, (B) elevated absolute slow frequency (delta and theta power), or (C) elevated absolute and relative beta power. A significant difference was found in the Korean ADHD Rating Scale (K-ARS) among the four groups (df=3, F=8.004, p<0.001); group C had the highest score (25.31±11.16), followed by group A (21.67±13.18). The score of group B (12.64±7.84) was similar to that of the NT group (11.07±6.12) and did not reach the cut-off point of the K-ARS. In the Wender-Utah Rating Scale (WURS), group B score (55.82±23.17) was significantly higher than the NT group score (42.81±13.26).

CONCLUSION

These results indicate that children with ADHD do not constitute a neurophysiologically homogenous group. Children with QEEG subtype B (elevated slow frequency) may be difficult to distinguish from normal children using the K-ARS, which is the most common screening tool for ADHD. Moreover, parents of children with this subtype may be less sensitive to observing ADHD symptoms.

Detection of ADHD From EEG Signals Using Different Entropy Measures and ANN

Attention deficit hyperactivity disorder (ADHD) is a prevalent behavioral, cognitive, neurodevelopmental pediatric disorder. Clinical evaluations, symptom surveys, and neuropsychological assessments are some of the ADHD assessment methods, which are time-consuming processes and have a certain degree of uncertainty. This research investigates an efficient computer-aided technological solution for detecting ADHD from the acquired electroencephalography (EEG) signals based on different nonlinear entropy estimators and an artificial neural network classifier. Features extracted through fuzzy entropy, log energy entropy, permutation entropy, SURE entropy, and Shannon entropy are analyzed for effective discrimination of ADHD subjects from the control group. The experimented results confirm that the proposed techniques can effectively detect and classify ADHD subjects. The permutation entropy gives the highest classification accuracy of 99.82%, sensitivity of 98.21%, and specificity of 98.82%. Also, the potency of different entropy estimators derived from the t-test reflects that the Shannon entropy has a higher P-value (>.001); therefore, it has a limited scope than other entropy estimators for ADHD diagnosis. Furthermore, the considerable variance found from potential features obtained in the frontal polar (FP) and frontal (F) lobes using different entropy estimators under the eyes-closed condition shows that the signals received in these lobes will have more significance in distinguishing ADHD from normal subjects.

Electrophysiological Brain Changes Associated With Cognitive Improvement in a Pediatric Attention Deficit Hyperactivity Disorder Digital Artificial Intelligence-Driven Intervention: Randomized Controlled Trial

BACKGROUND

Cognitive stimulation therapy appears to show promising results in the rehabilitation of impaired cognitive processes in attention deficit hyperactivity disorder.

OBJECTIVE

Encouraged by this evidence and the ever-increasing use of technology and artificial intelligence for therapeutic purposes, we examined whether cognitive stimulation therapy implemented on a mobile device and controlled by an artificial intelligence engine can be effective in the neurocognitive rehabilitation of these patients.

METHODS

In this randomized study, 29 child participants (25 males) underwent training with a smart, digital, cognitive stimulation program (KAD_SCL_01) or with 3 commercial video games for 12 weeks, 3 days a week, 15 minutes a day. Participants completed a neuropsychological assessment and a preintervention and postintervention magnetoencephalography study in a resting state with their eyes closed. In addition, information on clinical symptoms was collected from the child´s legal guardians.

RESULTS

In line with our main hypothesis, we found evidence that smart, digital, cognitive treatment results in improvements in inhibitory control performance. Improvements were also found in visuospatial working memory performance and in the cognitive flexibility, working memory, and behavior and general executive functioning behavioral clinical indexes in this group of participants. Finally, the improvements found in inhibitory control were related to increases in alpha-band power in all participants in the posterior regions, including 2 default mode network regions of the interest: the bilateral precuneus and the bilateral posterior cingulate cortex. However, only the participants who underwent cognitive stimulation intervention (KAD_SCL_01) showed a significant increase in this relationship.

CONCLUSIONS

The results seem to indicate that smart, digital treatment can be effective in the inhibitory control and visuospatial working memory rehabilitation in patients with attention deficit hyperactivity disorder. Furthermore, the relation of the inhibitory control with alpha-band power changes could mean that these changes are a product of plasticity mechanisms or changes in the neuromodulatory dynamics.

TRIAL REGISTRATION

ISRCTN Registry ISRCTN71041318; https://www.isrctn.com/ISRCTN71041318.

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.

Machine-learning-based diagnosis of drug-naive adult patients with attention-deficit hyperactivity disorder using mismatch negativity

Relatively little is investigated regarding the neurophysiology of adult attention-deficit/hyperactivity disorder (ADHD). Mismatch negativity (MMN) is an event-related potential component representing pre-attentive auditory processing, which is closely associated with cognitive status. We investigated MMN features as biomarkers to classify drug-naive adult patients with ADHD and healthy controls (HCs). Sensor-level features (amplitude and latency) and source-level features (source activation) of MMN were investigated and compared between the electroencephalograms of 34 patients with ADHD and 45 HCs using a passive auditory oddball paradigm. Correlations between MMN features and ADHD symptoms were analyzed. Finally, we applied machine learning to differentiate the two groups using sensor- and source-level features of MMN. Adult patients with ADHD showed significantly lower MMN amplitudes at the frontocentral electrodes and reduced MMN source activation in the frontal, temporal, and limbic lobes, which were closely associated with MMN generators and ADHD pathophysiology. Source activities were significantly correlated with ADHD symptoms. The best classification performance for adult ADHD patients and HCs showed an 81.01% accuracy, 82.35% sensitivity, and 80.00% specificity based on MMN source activity features. Our results suggest that abnormal MMN reflects the adult ADHD patients' pathophysiological characteristics and might serve clinically as a neuromarker of adult ADHD.

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.

Resting state EEG in youth with ASD: age, sex, and relation to phenotype

BACKGROUND

Identification of ASD biomarkers is a key priority for understanding etiology, facilitating early diagnosis, monitoring developmental trajectories, and targeting treatment efforts. Efforts have included exploration of resting state encephalography (EEG), which has a variety of relevant neurodevelopmental correlates and can be collected with minimal burden. However, EEG biomarkers may not be equally valid across the autism spectrum, as ASD is strikingly heterogeneous and individual differences may moderate EEG-behavior associations. Biological sex is a particularly important potential moderator, as females with ASD appear to differ from males with ASD in important ways that may influence biomarker accuracy.

METHODS

We examined effects of biological sex, age, and ASD diagnosis on resting state EEG among a large, sex-balanced sample of youth with (N = 142, 43% female) and without (N = 138, 49% female) ASD collected across four research sites. Absolute power was extracted across five frequency bands and nine brain regions, and effects of sex, age, and diagnosis were analyzed using mixed-effects linear regression models. Exploratory partial correlations were computed to examine EEG-behavior associations in ASD, with emphasis on possible sex differences in associations.

RESULTS

Decreased EEG power across multiple frequencies was associated with female sex and older age. Youth with ASD displayed decreased alpha power relative to peers without ASD, suggesting increased neural activation during rest. Associations between EEG and behavior varied by sex. Whereas power across various frequencies correlated with social skills, nonverbal IQ, and repetitive behavior for males with ASD, no such associations were observed for females with ASD.

CONCLUSIONS

Research using EEG as a possible ASD biomarker must consider individual differences among participants, as these features influence baseline EEG measures and moderate associations between EEG and important behavioral outcomes. Failure to consider factors such as biological sex in such research risks defining biomarkers that misrepresent females with ASD, hindering understanding of the neurobiology, development, and intervention response of this important population.

Neural Dynamics for Facilitating ADHD Diagnosis in Preschoolers: Central and Parietal Delta Synchronization in the Kiddie Continuous Performance Test

The present study aimed to characterize children at risk of attention-deficit/hyperactivity disorder (ADHD) during preschool age and provide early intervention. The continuous performance test (CPT) and electroencephalography (EEG) can contribute additional valuable information to facilitate diagnosis. This study measured brain dynamics at slow and fast task rates in the CPT using a wireless wearable EEG and identified correlations between the EEG and CPT data in preschool children with ADHD. Forty-nine preschool children participated in this study, of which 29 were diagnosed with ADHD and 20 exhibited typical development (TD). The Conners Kiddie Continuous Performance Test (K-CPT) and wireless wearable EEG recordings were employed simultaneously. Significant differences were observed between the groups with ADHD and TD in task-related EEG spectral powers (central as well as parietal delta, P < 0.01), which were distinct only in the slow-rate task condition. A shift from resting to the CPT task condition induced overall alpha powers decrease in the ADHD group. In the task condition, the delta powers were positively correlated with the CPT perseveration scores, whereas the alpha powers were negatively correlated with specific CPT scores mainly on perseveration and detectability (P < 0.05). These results, which complement the findings of other sparse studies that have investigated within-task-related brain dynamics, particularly in preschool children, can assist specialists working in early intervention to plan training and educational programs for preschoolers with ADHD.

Peripheral biomarkers of attention-deficit hyperactivity disorder: Current status and future perspective

Attention-deficit hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders, characterized by a persistent pattern of inattention, hyperactivity, and impulsivity. Since the diagnosis of ADHD is defined by operational diagnostic criteria consisting of several clinical symptoms, a number of heterogeneous mechanisms have been considered to be implicated in its pathophysiology. Although no clinically reliable biomarkers are available for the diagnosis of ADHD, several plausible candidate biomarkers have been proposed based on recent advances in biochemistry and molecular biology. This review article summarizes potential peripheral biomarkers associated with ADHD, mainly from recently published case-control studies. These include 1) biochemical markers: neurotransmitters and their receptors, neurotrophic factors, serum electrolytes, and inflammation markers; 2) genetic and epigenetic markers: microRNA, mRNA expression, and peripheral DNA methylation; 3) physiological markers: eye movement and electroencephalography. It also discusses the limitations and future directions of these potential biomarkers for application in clinical practice.

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.

ADHD: Reviewing the Causes and Evaluating Solutions

Attention deficit hyperactivity disorder (ADHD) is a neurodevelopmental disorder in which patients present inattention, hyperactivity, and impulsivity. The etiology of this condition is diverse, including environmental factors and the presence of variants of some genes. However, a great diversity exists among patients regarding the presence of these ADHD-associated factors. Moreover, there are variations in the reported neurophysiological correlates of ADHD. ADHD is often treated pharmacologically, producing an improvement in symptomatology, albeit there are patients who are refractory to the main pharmacological treatments or present side effects to these drugs, highlighting the importance of developing other therapeutic options. Different non-pharmacological treatments are in this review addressed, finding diverse results regarding efficacy. Altogether, ADHD is associated with different etiologies, all of them producing changes in brain development, leading to the characteristic symptomatology of this condition. Given the heterogeneous etiology of ADHD, discussion is presented about the convenience of personalizing ADHD treatment, whether pharmacological or non-pharmacological, to reach an optimum effect in the majority of patients. Approaches to personalizing both pharmacological therapy and neurofeedback are presented.

Classifying ADHD subtypes/presentations considering the joint effect of three levels of investigation

AIM

Discriminant validity of the Attention Deficits/Hyperactive Disorders (ADHD) subtypes/presentations is not yet clear. The purpose of this study was to investigate joint contribution of the strongest factors of the three dimensions, namely psychopathology, neuropsychology and electrophysiology for subtyping of presentations.

METHOD

A sample of 104 boys aged 7-12 years was subdivided into three groups with ADHD combined (n = 22), inattentive (n = 25) and hyperactive/impulsive subtype (n = 14), and 43 typically developing controls (TDC). Children were investigated regarding the Child Behavior Checklist (CBCL), the Integrated Visual and Auditory Test (IVA), and EEG spectral power during eyes closed resting state. Subsequently, statistical analysis included discriminant functional analysis and principle component analysis.

RESULTS

Neuropsychological parameters had the highest contribution in classifying of the groups. EEG parameters had no effect on differentiation of the groups, and among the psychopathological parameters, only the oppositional behavioral disorder score contributed to correctly classify 74.3% of the groups. Furthermore, we found four factors with eigenvalues higher than 1 in the ADHD and typical groups, with one factor characterized by four CBCL scales, another one by auditory and visual vigilance, speed and beta band power, the third by auditory and visual prudence, and forth by theta band power.

CONCLUSIONS

Our results demonstrated that ADHD subtypes/presentations can be differentiated from each other at different levels of investigation despite some clinical symptoms overlap. The results suggested that not only psychopathology but also the impairment of sensory processing should be assessed in children with ADHD in order to use this additional information for a jointly multilevel clinical intervention, which may improve treatment success.

Diagnose ADHD disorder in children using convolutional neural network based on continuous mental task EEG

BACKGROUND AND OBJECTIVE

Attention-Deficit/Hyperactivity Disorder (ADHD) is a chronic behavioral disorder in children. Children with ADHD face many difficulties in maintaining their concentration and controlling their behaviors. Early diagnosis of this disorder is one of the most important challenges in its control and treatment. No definitive expert method has been found to detect this disorder early. Our goal in this study is to develop an assistive tool for physicians to recognize ADHD children from healthy children using electroencephalography (EEG) based on a continuous mental task.

METHODS

We used EEG signals recorded from 31 ADHD children and 30 healthy children. In this study, we developed a deep learning model using a convolutional neural network that have had significant performance in image processing fields. For this purpose, we first preprocessed EEG signals to eliminate noise and artifacts. Then we segmented preprocessed samples into more samples. We extracted the theta, alpha, beta, and gamma frequency bands from each segmented sample and formed a color RGB image with three channels. Eventually, we imported the resulting images into a 13-layer convolutional neural network for feature extraction and classification.

RESULTS

The proposed model was evaluated by 5-fold cross validation for train, evaluation, and test data and achieved an average accuracy of 99.06%, 97.81%, 97.47% for segmented samples. The average accuracy for subject-based test samples was 98.48%. Also, the performance of the model was evaluated using the confusion matrix with precision, recall, and f1-score metrics. The results of these metrics also confirmed the outstanding performance of the model.

CONCLUSIONS

The accuracy, precision, recall, and f1-score of our model were better than all previous works for diagnosing ADHD in children. Based on these prominent and reliable results, this technique can be used as an assistive tool for the physicians in the early diagnosis of ADHD in children.

Arousal and Executive Alterations in Attention Deficit Hyperactivity Disorder (ADHD)

Attention deficit hyperactivity disorder (ADHD) is the most common neurobehavioral disorder in childhood and can significantly affect a child's personal and social development and academic achievement. Taking into account the model of attentional networks proposed by Posner et al., the aim of the present study was to review the literature regarding two main explicative models of ADHD, i.e., the inhibition model and the cognitive-energetic model, by discussing behavioral and neurological evidence of both models and the limitations of each model. The review highlights evidence that favors the energetic model and points to an unstable arousal as a potential pathogenetic factor in ADHD.

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

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

The Theta/Beta Ratio as an Index of Cognitive Processing in Adults With the Combined Type of Attention Deficit Hyperactivity Disorder

An elevated theta/beta ratio in the EEG has long been observed among individuals with Attention Deficit Hyperactivity Disorder (ADHD). The theta/beta ratio was previously hypothesised to be an index of arousal, but a number of studies failed to find any association between the ratio and indices of arousal, instead proposing that the theta/beta ratio may actually be indicative of cognitive processing. This hypothesis was tested by Clarke et al using a sample of healthy adults, with results indicating that the theta/beta ratio correlated with a marker of cognitive processing (P300 latency in an auditory oddball task), while P300 amplitude correlated with an arousal marker (alpha power). The aim of this study was to test whether similar results could be found in a sample of 41 adults with the combined type of ADHD. EEGs were recorded during an eyes-closed resting condition and an auditory oddball task. Results demonstrated that the theta/beta ratio correlated significantly with P300 latency. Absolute alpha power did not correlate significantly with P300 amplitude or P300 latency. These results support the hypotheses that the theta/beta ratio is a marker of cognitive processing capacity in both the general population and in participants with ADHD, and that the alpha/arousal linkage is anomalous in ADHD.

Sex Differences in QEEG in Psychopath Offenders

Introduction. Functional brain differences related to sex in psychopathic behavior represent an important field of neuroscience research; there are few studies on this area, mainly in offender samples. Objective. The aim of this study was to investigate the presence of electrophysiological differences between male and female psychopath offenders; specifically, we wanted to assess whether the results in quantitative EEG, low-resolution electromagnetic tomography (LORETA), and changes in synchronous brain activity could be related to sex influence. Sample and Methods. The study included 31 male and 12 female psychopath offenders, according to the Hare Psychopathy Checklist-Revised criteria from 2 prisons located in Havana City. The EEG visual inspection characteristics and the use of frequency domain quantitative analysis techniques are described. Results. The resting EEG visual analyses revealed a high percentage of EEG abnormalities in both studied groups. Significant statistical differences between the mean parameters of cross spectral measures between psychopathic offender groups were found in the beta band at bilateral frontal derivation and centroparietal areas. LORETA showed differences especially in the paralimbic and parieto-occipital areas Synchronization likelihood revealed a significant group effect in the 26 to 30 Hz band. These results indicate that combining quantitative EEG, LORETA analysis, and synchronization likelihood may improve the neurofunctional differentiation between psychopath offenders of both sexes.

Brain Mapping Performance as an Occupational Therapy Assessment Aid in Attention Deficit Hyperactivity Disorder

IMPORTANCE

Brain mapping performance (BMP) may provide strong predictors to analyze primary functional outcomes and support occupational therapy with clients with attention deficit hyperactivity disorder (ADHD).

OBJECTIVE

To clarify the value of quantitative electroencephalography to indicate BMP in children with ADHD.

DESIGN

One-year cross-sectional study.

SETTING

Brain Computer Interface Laboratory, Mahidol University, Salaya, Nakhon Pathom, Thailand.

PARTICIPANTS

Thai school-age children with and without ADHD (N = 305).

OUTCOMES AND MEASURES

We used θ relative power in concordance with stepwise multiple regression analysis. Outcomes included measures of 12 brain locations that were compared between children with and without ADHD.

RESULTS

Significant differences were found between the groups, especially for Cz, T3, Fp1, Fz, F4, and F7. According to BMP, the group with ADHD had higher emotional awareness and language comprehension than the group without ADHD.

CONCLUSIONS AND RELEVANCE

Occupational therapy practitioners can use BMP as a valuable tool for setting occupational goals to help children with ADHD improve their social-emotional learning performance in school and in the community. BMP may provide an evaluation to support occupational therapy services for clients with ADHD. The result can be applied in clinical settings by quantitative electroencephalography training.

WHAT THIS ARTICLE ADDS

BMP can be used as a neuropsychological and behavioral assessment tool for setting SMART (specific, measurable, attainable, relevant, and time-oriented) goals for occupational therapy services for clients with ADHD.

Excessive Daytime Sleepiness Measurements in Children With Attention Deficit Hyperactivity Disorder

Attention deficit hyperactivity disorder (ADHD) is the most commonly diagnosed neurodevelopmental disorder in childhood. It is a heterogeneous disorder in terms of clinical presentation that is probably due to the frequent occurrence of comorbidity. Children with ADHD more frequently report sleep disorders (notably delayed sleep phase syndrome) and excessive daytime sleepiness (EDS) than typically developing children. The aim of this article is to propose a narrative review of the assessment of EDS in the context of ADHD with first a summary of the subjective and objective tools used to measure it. Secondly, perspectives in terms of electroencephalogram (EEG) markers and neurofeedback are proposed. Then, possibilities for new kinds of evaluation are discussed (virtual reality, ecological momentary assessment, etc.). Lastly, we discuss specific clinical situations with EDS in the context of ADHD as links with narcolepsy, the comorbidity with other psychiatric disorders, and the context of sluggish cognitive tempo.

Neuropsychological classification based on brain mapping performance in Thai children with and without ADHD

This study investigated the cognitive strengths and weaknesses of Attention Deficit Hyperactivity Disorder (ADHD) patients by using quantitative electroencephalography (QEEG) to analyze brain mapping outcomes in relation to neuropsychological assessments. A total of 305 participants with and without ADHD were recruited. The theta relative power of QEEG was analyzed using stepwise multiple regression, and twelve scalp regions were compared between groups using independent t-tests. Increased power was found at the T5 scalp region in the ADHD group and at the F4 region in the non-ADHD group. Decreased power was found at the F7 region in the ADHD group and at the F3 region in the non-ADHD group. Six of the twelve brain locations had significantly higher theta relative power in the ADHD group than in the non-ADHD group. These brain mapping outcomes can be easily translated to neuropsychological functions, such as attention, executive function, memory, spatial ability, and language, to better understand or predict the potential behavior of ADHD patients.

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.

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 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.

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.