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

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.

Diagnosis of attention deficit hyperactivity disorder using non-linear analysis of the EEG signal

Attention deficit hyperactivity disorder (ADHD) is a common behavioural disorder that may be found in 5%-8% of the children. Early diagnosis of ADHD is crucial for treating the disease and reducing its harmful effects on education, employment, relationships, and life quality. On the other hand, non-linear analysis methods are widely applied in processing the electroencephalogram (EEG) signals. It has been proved that the brain neuronal activity and its related EEG signals have chaotic behaviour. Hence, chaotic indices can be employed to classify the EEG signals. In this study, a new approach is proposed based on the combination of some non-linear features to distinguish ADHD from normal children. Lyapunov exponent, fractal dimension, correlation dimension and sample, fuzzy and approximate entropies are the non-linear extracted features. For computing, the chaotic time series of obtained EEG in the brain frontal lobe (FP1, FP2, F3, F4, and Fz) need to be analysed. Experiments on a set of EEG signal obtained from 50 ADHD and 26 normal cases yielded a sensitivity, specificity, and accuracy of 98, 92.31, and 96.05%, respectively. The obtained accuracy provides a significant improvement in comparison to the other similar studies in identifying and classifying children with ADHD.

A systematic review of quantitative EEG as a possible biomarker in child psychiatric disorders

Quantitative EEG (qEEG) has emerged as a potential intermediate biomarker for diagnostic clarification in mental illness. This systematic review examines published studies that used qEEG in youth with psychiatric illness between 1996 and 2017. We conducted a comprehensive database search of CINAHL, PubMed, and Cochrane using the following keywords: "quantitative EEG" and depression (MDD), anxiety, attention-deficit hyperactivity disorder (ADHD), autism spectrum disorder (ASD), eating disorder, conduct, substance use, schizophrenia, post-traumatic stress disorder, and panic disorder. Our search yielded 516 titles; 33 met final inclusion criteria, producing a total of 2268 youth aged 4-18. qEEG was most frequently studied as a potential diagnostic tool in pediatric mental illness; few studies assessed treatment response. Studies show higher theta/beta ratio in ADHD vs healthy controls (HC). The most consistent finding in ASD was decreased coherence in ASD vs HC. Studies show MDD has lower temporal coherence and interhemispheric coherence in sleep EEGs than HC. Further research is needed in the areas of mood, anxiety, ASD, and relationship to treatment. It remains unknown if abnormalities in qEEG are nonspecific markers of pediatric psychiatric illness or if they have the potential to differentiate types of psychopathology.

Predictive Value of Slow and Fast EEG Oscillations for Methylphenidate Response in ADHD

Attention-deficit/hyperactivity disorder (ADHD) is the most common neurodevelopmental disorder and is characterized by symptoms of inattention and/or hyperactivity and impulsivity. In the current study, we obtained quantitative EEG (QEEG) recordings of 51 children aged between 6 and 12 years before the initiation of methylphenidate treatment. The relationship between changes in the scores of ADHD symptoms and initial QEEG features (power/power ratios values) were assessed. In addition, the children were classified as responder and nonresponder according to the ratio of their response to the medication (>25% improvement after medication). Logistic regression analyses were performed to analyze the accuracy of QEEG features for predicting responders. The findings indicate that patients with increased delta power at F8, theta power at Fz, F4, C3, Cz, T5, and gamma power at T6 and decreased beta powers at F8 and P3 showed more improvement in ADHD hyperactivity symptoms. In addition, increased delta/beta power ratio at F8 and theta/beta power ratio at F8, F3, Fz, F4, C3, Cz, P3, and T5 showed negative correlations with Conners' score difference of hyperactivity as well. This means, those with greater theta/beta and delta/beta powers showed more improvement in hyperactivity following medication. Theta power at Cz and T5 and theta/beta power ratios at C3, Cz, and T5 have significantly classified responders and nonresponders according to the logistic binary regression analysis. The results show that slow and fast oscillations may have predictive value for treatment response in ADHD. Future studies should seek for more sensitive biomarkers.

Resting-state alpha and gamma activity in affective disorder with ADHD symptoms: Comparison between bipolar disorder and major depressive disorder

Although comorbid attention deficit/hyperactivity disorder (ADHD) symptoms are very common in mood disorder, its neurophysiological correlates have not been explored. This study aimed to examine clinical and neurophysiological correlates of ADHD symptoms in major depressive disorder (MDD) and bipolar disorder (BP). A total of 67 subjects with mood disorder, current depressive episode (38 subjects with MDD and 29 subjects with BP depression) were included in the analysis. Resting quantitative electroencephalography (qEEG) recordings were collected under eyes closed condition. ADHD symptoms, depression, anxiety, and lifetime hypomania were evaluated using self-report questionnaires. In MDD, ADHD symptoms did not show significant associations with anxiety and depression. In BP, ADHD symptoms showed significant associations with depression, anxiety and lifetime hypomania. Significant correlations with Adult ADHD self-report scales (ASRS) inattention score and total score were detected in left and right frontal alpha powers in MDD while significant correlation with ASRS hyperactivity score and ASRS total score were detected in right frontal gamma power in BP. Linear regression analyses revealed that left and right frontal alpha powers, depression and lifetime hypomania showed significant association with ASRS inattention score and ASRS total score in MDD. In BP, linear regression analysis showed ASRS hyperactivity score was associated with lifetime hypomania and the right frontal gamma power. MDD and BP showed different correlation patterns between frontal qEEG measures and ADHD symptoms. This might be associated with distinct neurobiological underpinnings of co-occurring ADHD symptoms in MDD and BP.

Delayed cortical maturation at the centrotemporal brain regions in patients with benign childhood epilepsy with centrotemporal spikes (BCECTS)

Benign childhood epilepsy with centrotemporal spikes (BCECTS) is an epilepsy syndrome commonly found in child and adolescent. Although the prognosis is mostly favorable as long as the seizure is well controlled. However, they are often suffering from the cognitive and behavioral problems which might be the consequences of the initial insults. It is still not clear whether the initial epileptiform discharges has long term impact on the resting-state brain activities at later ages. This study investigated the resting-state brain activities in BCECTS patients with clinical seizure remission stage (n = 16; 11 males) and compared with the non-epileptic, age-matched control subjects. Quantitative electroencephalography (qEEG) revealed a significantly higher absolute power of the theta and alpha waves in BCECTS patients with clinical seizure remission as compared with the non-epileptic control subjects. Interestingly, the differences were observed mainly over the centrotemporal electrodes which are the common sites of the initial epileptiform discharges. The differences were more significant in patients with bilateral epileptiform discharges than those with the unilateral epileptic activities. Typically, the brain wave power continuously decreases with increasing ages. Therefore, higher absolute powers of the brain waves indicate more delayed in cortical maturation compared with the non-epileptic control group. These findings indicated that BCECTS patients have delay cortical maturation at the centrotemporal brain regions even at the clinical seizure remission phase.

EEG characteristics of children with attention-deficit/hyperactivity disorder

The electroencephalogram (EEG) is an informative neuroimaging tool for studying attention-deficit/hyperactivity disorder (ADHD); one main goal is to characterize the EEG of children with ADHD. In this study, we employed the power spectrum, complexity and bicoherence, biomarker candidates for identifying ADHD children in a machine learning approach, to characterize resting-state EEG (rsEEG). We built support vector machine classifiers using a single type of feature, all features from a method (relative spectral power, spectral power ratio, complexity or bicoherence), or all features from all four methods. We evaluated effectiveness and performance of the classifiers using the permutation test and the area under the receiver operating characteristic curve (AUC). We analyzed the rsEEG from 50 ADHD children and 58 age-matched controls. The results show that though spectral features can be used to build a convincing model, the prediction accuracy of the model was unfortunately unstable. Bicoherence features had significant between-group differences, but classifier performance was sensitive to brain region used. rsEEG complexity of ADHD children was significantly lower than controls and may be a suitable biomarker candidate. Through a machine learning approach, 14 features from various brain regions using different methods were selected; the classifier based on these features had an AUC of 0.9158 and an accuracy of 84.59%. These findings strongly suggest that the combination of rsEEG characteristics obtained by various methods may be a tool for identifying ADHD.

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.

Originally Adapted Mobile Application Used for Neuropsychiatric Patients

The potential use of modern mobile devices for medical purposes is huge. Digital mental health tools have mostly tended to use psycho-educational strategies based on treatment orientations developed and validated outside digital health.

The aim of this study was to test the availability of our own original app named “Neuro-game” for evaluation of reaction time in different neuropsychiatric patients. Reaction time is strongly related to the executive brain functions.

The examined sample comprised of 135 neuropsychiatric patients (with epilepsy, depression, general anxiety, psychosis and ADHD) compared with matched 50 healthy persons.

We showed that the average reaction time in neuropsychiatric patients compared with healthy people is not notably different. However, we found significant differences in total hits, total misses and total tries in the performances of ill persons.

The crucial differences in obtained scores are confirmed for age and gender issues.

The most important differences are found in the number of hits, misses and tries in the group of depressed, followed by psychotic and ADHD patients, while anxious ones showed pretty normal parameters.

All tested parameters are remarkably different for the epileptic group vs. healthy people.

The T-test for epileptic vs. healthy people showed noteworthy differences for total tries, total misses, and total hits, but the average time reaction did not differ significantly.

In comparison with other psychometric assessments, this approach by using mobile phones seemed more practical, available anywhere (not only in medical settings), less time consuming and quite interesting for all ages.

Viral encephalitis in quantitative EEG

OBJECTIVE

Our aim was to study the character of quantitative EEG of viral encephalitis.

METHOD

Collect the EEG data of hospitalized children with viral encephalitis diagnosed by pediatricians from January 2013 to September 2016, and EEG data of normal cases at the same age were control group. Using quantitative EEG analysis technologies to obtain power spectrum value, power spectrum value, 1 power spectrum value, 12 power spectrum value, 21 power spectrum value, and 12 power spectrum value. Relative power spectrum values of 2 and were obtained by calculation. All the cases were divided into 5 groups according to the EEG character: age 3 group, age 4 group, age 5-6 group, age 7-9-year group, and age 10-14-year group. Viral encephalitis group and normal cases group were statistically compared to obtain characters of quantitative EEG with viral encephalitis.

RESULTS

Power spectrum values and power spectrum values of 3-14-year-old cases with encephalitis increased. 1 power spectrum values existed in age 3 group with viral encephalitis and declined at the post-head lead, while 11 and 12 power spectrum values existed in age 4-14 group with viral encephalitis declined at the post-head lead. The value of 2 Power spectrum values of age 3-9 group was limited in diagnosing viral encephalitis. 1 and 12 power spectrum values decrease in age 10-14 group with viral encephalitis. Relative power spectrum values of 2 and increased in age 3-14 group with viral encephalitis; Relative power spectrum values of decreased in age 3-14 group with viral encephalitis, most lead of relative power spectrum decreased in age 3-14 group with viral encephalitis.

CONCLUSION

The character of quantitative EEG of cases with viral encephalitis is similar to EEG, but more detailed, more precise, more intuitive and can be used for clinical diagnose of viral encephalitis.

Increased EEG Theta Spectral Power in Sleep in Myotonic Dystrophy Type 1

STUDY OBJECTIVES

Myotonic dystrophy type 1 (DM1) is a multisystemic disorder that involves the central nervous system (CNS). Individuals with DM1 commonly present with sleep dysregulation, including excessive daytime sleepiness and sleep-disordered breathing. We aim to characterize electroencephalogram (EEG) power spectra from nocturnal polysomnography (PSG) in patients with DM1 compared to matched controls to better understand the potential CNS sleep dysfunction in DM1.

METHODS

A retrospective, case-control (1:2) chart review of patients with DM1 (n = 18) and matched controls (n = 36) referred for clinical PSG at the Stanford Sleep Center was performed. Controls were matched based on age, sex, apnea-hypopnea index (AHI), body mass index (BMI), and Epworth Sleepiness Scale (ESS). Sleep stage and respiratory metrics for the two groups were compared. Power spectral analysis of the EEG C3-M2 signal was performed using the fast Fourier transformation.

RESULTS

Patients with DM1 had significantly increased theta percent power in stage N2 sleep compared to matched controls. Theta/beta and theta/alpha percent power spectral ratios were found to be significantly increased in stage N2, N3, all sleep stages combined, and all wake periods combined in patients with DM1 compared to controls. A significantly lower nadir O2 saturation was also found in patients with DM1 versus controls.

CONCLUSIONS

Compared to matched controls, patients with DM1 had increased EEG theta spectral power. Increased theta/beta and theta/alpha power spectral ratios in nocturnal PSG may reflect DM1 pathology in the CNS.

An Integrated Model of Emotional Problems, Beta Power of Electroencephalography, and Low Frequency of Heart Rate Variability after Childhood Trauma in a Non-Clinical Sample: A Path Analysis Study

Childhood trauma is known to be related to emotional problems, quantitative electroencephalography (EEG) indices, and heart rate variability (HRV) indices in adulthood, whereas directions among these factors have not been reported yet. This study aimed to evaluate pathway models in young and healthy adults: (1) one with physiological factors first and emotional problems later in adulthood as results of childhood trauma and (2) one with emotional problems first and physiological factors later. A total of 103 non-clinical volunteers were included. Self-reported psychological scales, including the Childhood Trauma Questionnaire (CTQ), State-Trait Anxiety Inventory, Beck Depression Inventory, and Affective Lability Scale were administered. For physiological evaluation, EEG record was performed during resting eyes closed condition in addition to the resting-state HRV, and the quantitative power analyses of eight EEG bands and three HRV components were calculated in the frequency domain. After a normality test, Pearson's correlation analysis to make path models and path analyses to examine them were conducted. The CTQ score was significantly correlated with depression, state and trait anxiety, affective lability, and HRV low-frequency (LF) power. LF power was associated with beta2 (18-22 Hz) power that was related to affective lability. Affective lability was associated with state anxiety, trait anxiety, and depression. Based on the correlation and the hypothesis, two models were composed: a model with pathways from CTQ score to affective lability, and a model with pathways from CTQ score to LF power. The second model showed significantly better fit than the first model (AICmodel1 = 63.403 > AICmodel2 = 46.003), which revealed that child trauma could affect emotion, and then physiology. The specific directions of relationships among emotions, the EEG, and HRV in adulthood after childhood trauma was discussed.

An endophenotype approach to the genetics of alcohol dependence: a genome wide association study of fast beta EEG in families of African ancestry

Fast beta (20-28 Hz) electroencephalogram (EEG) oscillatory activity may be a useful endophenotype for studying the genetics of disorders characterized by neural hyperexcitability, including substance use disorders (SUDs). However, the genetic underpinnings of fast beta EEG have not previously been studied in a population of African-American ancestry (AA). In a sample of 2382 AA individuals from 482 families drawn from the Collaborative Study on the Genetics of Alcoholism (COGA), we performed a genome-wide association study (GWAS) on resting-state fast beta EEG power. To further characterize our genetic findings, we examined the functional and clinical/behavioral significance of GWAS variants. Ten correlated single-nucleotide polymorphisms (SNPs) (r2>0.9) located in an intergenic region on chromosome 3q26 were associated with fast beta EEG power at P<5 × 10-8. The most significantly associated SNP, rs11720469 (β: -0.124; P<4.5 × 10-9), is also an expression quantitative trait locus for BCHE (butyrylcholinesterase), expressed in thalamus tissue. Four of the genome-wide SNPs were also associated with Diagnostic and Statistical Manual of Mental Disorders Alcohol Dependence in COGA AA families, and two (rs13093097, rs7428372) were replicated in an independent AA sample (Gelernter et al.). Analyses in the AA adolescent/young adult (offspring from COGA families) subsample indicated association of rs11720469 with heavy episodic drinking (frequency of consuming 5+ drinks within 24 h). Converging findings presented in this study provide support for the role of genetic variants within 3q26 in neural and behavioral disinhibition. These novel genetic findings highlight the importance of including AA populations in genetics research on SUDs and the utility of the endophenotype approach in enhancing our understanding of mechanisms underlying addiction susceptibility.

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

Preterm birth has been associated with an increased risk for ADHD-like behavioural symptoms and cognitive impairments. However, direct comparisons across ADHD and preterm-born samples on neurophysiological measures are limited. The aim of this analysis was to test whether quantitative EEG (QEEG) measures identify differences or similarities in preterm-born adolescents, compared to term-born adolescents with and without ADHD, during resting-state and cognitive task conditions. We directly compared QEEG activity between 186 preterm-born adolescents, 69 term-born adolescents with ADHD and 135 term-born control adolescents during an eyes-open resting-state condition (EO), which previously discriminated between the adolescents with ADHD and controls, and during a cued continuous performance task (CPT-OX). Absolute delta power was the only frequency range to demonstrate a significant group-by-condition interaction. The preterm group, like the ADHD group, displayed significantly higher delta power during EO, compared to the control group. In line with these findings, parent-rated ADHD symptoms in the preterm group were significantly correlated with delta power during rest. While the preterm and control groups did not differ with regard to absolute delta power during CPT-OX, the ADHD group showed significantly higher absolute delta power compared to both groups. Our results provide evidence for overlapping excess in the absolute delta range in preterm-born adolescents and term-born adolescents with ADHD during rest. During CPT-OX, preterm-born adolescents resembled controls. Increased delta power during rest may be a potential general marker of brain trauma, pathology or neurotransmitter disturbances.

Investigation of attention deficit hyperactivity disorder (ADHD) sub-types in children via EEG frequency domain analysis

AIM OF THE STUDY

To investigate the frequency domain effects and changes in electroencephalography (EEG) signals in children diagnosed with attention deficit hyperactivity disorder (ADHD).

PATIENTS AND METHODS

The study contains 40 children. All children were between the ages of 7 and 12 years. Participants were classified into four groups which were ADHD (n=20), ADHD-I (ADHD-Inattentive type) (n=10), ADHD-C (ADHD-Combined type) (n=10), and control (n=20) groups. In this study, the frequency domain of EEG signals for ADHD, subtypes and control groups were analyzed and compared using Matlab software. The mean age of the ADHD children's group was 8.7 years and the control group 9.1 years.

RESULTS

Spectral analysis of mean power (μV²) and relative-mean power (%) was carried out for four different frequency bands: delta (0--4 Hz), theta (4--8 Hz), alpha (8--13 Hz) and beta (13--32 Hz). The ADHD and subtypes of ADHD-I, and ADHD-C groups had higher average power value of delta and theta band than that of control group. However, this is not the case for alpha and beta bands. Increases in delta/beta ratio and statistical significance were found only between ADHD-I and control group, and in delta/beta, theta/delta ratio statistical significance values were found to exist between ADHD-C and control group.

CONCLUSION

EEG analyzes can be used as an alternative method when ADHD subgroups are identified.

Childhood Trauma Associated with Enhanced High Frequency Band Powers and Induced Subjective Inattention of Adults

Childhood trauma can lead to various psychological and cognitive symptoms. It has been demonstrated that high frequency electroencephalogram (EEG) powers could be closely correlated with inattention. In this study, we explored the relationship between high frequency EEG powers, inattention, symptoms of adult attention deficit hyperactivity disorder (ADHD), and childhood traumatic experiences. A total of 157 healthy Korean adult volunteers were included and divided into two groups using the Childhood Trauma Questionnaire (CTQ) score. The subjective inattention scores, ADHD scale, and anxiety and depression symptom were evaluated. EEG was recorded and quantitative band powers were analyzed. The results were as follows: (1) the high CTQ group showed significantly increased delta, beta1, beta2, beta3 and gamma, and significantly decreased low alpha power compared to the low CTQ group; (2) the high CTQ group had higher inattention score compared to the low CTQ group; (3) the high CTQ group had higher adult ADHD scores; (4) CTQ scores showed significant positive correlations with inattention scores, and adult ADHD scores; (5) unexpectedly, the inattention scores showed significant positive correlations with beta powers and a negative correlation with low alpha power; and (6) the moderated mediation model was confirmed: the depression fully mediated the path from state anxiety to inattention, and the CTQ significantly moderated the pathway between anxiety and depression. Our results show the possibility that childhood adversity may cause subjective inattention and adult ADHD symptoms. Depressive symptoms fully mediated the path from anxiety to inattention, especially in those who report severe childhood traumatic experiences.