Investigating electrophysiological measures during resting-state might be useful to investigate brain functioning and responsivity in individuals under diagnostic assessment for attention deficit hyperactivity disorder (ADHD) and autism. EEG was recorded in 43 children with or without ADHD and autism, during a 4-min-long resting-state session which included an eyes-closed and an eyes-open condition. We calculated and analyzed occipital absolute and relative spectral power in the alpha frequency band (8–12 Hz), and alpha reactivity, conceptualized as the difference in alpha power between eyes-closed and eyes-open conditions. Alpha power was increased during eyes-closed compared to eyes-open resting-state. While absolute alpha power was reduced in children with autism, relative alpha power was reduced in children with ADHD, especially during the eyes-closed condition. Reduced relative alpha reactivity was mainly associated with lower IQ and not with ADHD or autism. Atypical brain functioning during resting-state seems differently associated with ADHD and autism, however further studies replicating these results are needed; we therefore suggest involving research groups worldwide by creating a shared and publicly available repository of resting-state EEG data collected in people with different psychological, psychiatric, or neurodevelopmental conditions, including ADHD and autism. Attention deficit hyperactivity disorder (ADHD) affects about 5% of children worldwide, and it is characterized by symptoms of inattention and hyperactivity/impulsivity, which are associated with difficulties in regulating behavior and reduced adaptive functioning . The dev“Resting-state” is the term which refers to situations when a person is not involved in any mentally challenging or physical activity. During resting-state, attention is less focused on external sensory information  and moreDifferent theoretical models and previous empirical studies have proposed that the autonomic nervous system might be under-active in people with ADHD and this might be associated with chronic states of hypo-arousal and reduced vigilance at rest  and an “autism-factor” . We therefore tested the presence of effects associated with a specific condition (ADHD or autism) and the comorbid presence of ADHD and autism, although the size of the comorbid group was small. Sample characteristics and significant between-groups differences on demographic and clinical variables, are presented in Data from 43 children, including 20 typically developing controls, 9 children with ADHD-only, 6 children with autism-only and 8 with comorbid ADHD + autism, were used for the present study and are publicly available at the following link: Electroencephalography (EEG) was recorded during a 4-min resting-state session, after participants completed an attentional task . The rehttp://neuroimage.usc.edu/brainstorm). Flat or noisy channels were rejected, before being re-referenced to the average of the remaining channels and being filtered with 0.5 Hz high-pass, 70 Hz low-pass and 50 Hz notch filters. Signal Space Projection  with 128 silver/silver chloride (Ag/AgCl) electrodes positioned according to an extended 10–20 montage, using a 500-Hz sampling-rate and impedances under 10 kΩ. During recording, signals were referenced to a common mode sensor to the left of Cz. Additional electrodes were placed at the inner orbital ridge and the outer canthus of each eye to record eye movements and on the left and right mastoids to record other artefacts. Pre-processing of EEG data was performed with Brainstorm , which ion  was usehttps://jasp-stats.org/. Gender and IQ were included as covariates in the models. Bayesian statistical analyses have been used to test the main hypotheses of the present study. Bayesian statistic is a data-focused approach that investigates the probabilities of different hypotheses or models, investigating how much the data fit with each [https://osf.io/f8krs/.All the analyses were carried out in JASP , a softwith each . More spith each . We usedith each  to calcuith each . FurtherWe investigated electrophysiological oscillatory patterns of alpha activity and reactivity in children with ADHD or autism. Separate repeated measures Bayesian ANCOVAs were carried out on absolute and relative alpha spectral power measured at the central-occipital scalp region, which were compared across the two Conditions  and in relation to ADHD- and autism-diagnoses , controlling for gender and IQ. Further, two Bayesian ANCOVAs were carried out on alpha reactivity (based on absolute and relative power) with ADHD and autism as between-groups factors and controlling for the effects of gender and IQ.model = 6.415; error % = 3.635; R2 = 0.690). We found strong evidence for the presence of an effect of Condition on absolute alpha power , indicating that absolute alpha power was increased during eyes-closed compared to eyes-open , indicating that children with autism (autism-only and ADHD + autism) had reduced absolute alpha power, compared to children without autism  . Overall, these findings are in line with our primary hypotheses and suggest the presence of increased absolute alpha power during eyes-closed than eyes-open resting-state, and reduced absolute alpha power during resting-state in children with autism.We found evidence that the model which included (Condition + autism + Gender) as factors, best predicted the data on absolute alpha power . We therefore further investigated each predictive factor or interaction, which was added to this model.When investigating relative alpha power, the following model was the best to predict the data: , so that relative alpha power was increased during eyes-closed compared to eyes-open resting-state  and anecdotal evidence in support of the presence of an interaction ADHD * Condition (BFinclusion = 1.792). More specifically, post-hoc tests on ADHD-factor revealed that relative alpha power was reduced in children with ADHD (ADHD-only and ADHD + autism) compared to children without ADHD  , and anecdotal evidence in support of the presence of a between-groups difference during eyes-open resting-state . As shown in As suggested by van den Bergh and colleagues , we invemodel = 2.650; error % = 0.662; R2 = 0.063), we found anecdotal evidence in support of the absence of a predictive effect of each of these variables on absolute alpha reactivity , suggesting that neither Autism nor Gender were strong predictors of absolute alpha reactivity.Although the model which best predicted the data on absolute alpha reactivity included the factors “Autism” and “Gender”  and strong evidence was found in support of a predictive effect of IQ on relative alpha reactivity (BFinclusion = 6.370). We followed-up this effect by carrying out a Bayesian correlation analysis. Strong evidence was found in support of the presence of a positive correlation between IQ and relative alpha reactivity . More specifically, as evidenced in Conversely, when investigating relative alpha reactivity, the model including only “full scale IQ” best fit with the data  and ADHD . Our study and findings from Newson and Thiagarajan  might thOur findings might have some implications for future research studies investigating arousal in children with ADHD and autism. Reduced relative alpha power in ADHD might be a sign of reduced functional organization of cortical networks during resting-state, especially during eyes-closed, while reduced absolute alpha power in autism might be interpreted as an index of increased sensitivity to sensory information. In a recent study (manuscript in preparation ), we havUnexpectedly, despite the strong evidence found for reduced relative alpha power during eyes-closed resting-state in children with ADHD, we could not replicate previous findings of reduced alpha reactivity in ADHD , but we There are several limitations in the present study. Data were collected in quite a small sample and during quite short resting-state conditions; we maximized power to investigate effects specific to ADHD and to autism by using Bayesian statistics. Future studies should investigate comorbidity between these conditions and focus on observing dynamic changes in oscillatory patterns over longer periods of resting-state, to determine whether individuals with different conditions differ on these. It is also important to consider that a cognitive task preceded the resting-state session in the present study, and this might have indirectly influenced our resting-state findings.https://osf.io/azkhs/, under the section “Files”.Despite these limitations, the present study has demonstrated how atypical resting-state oscillatory patterns of alpha activity might be differently associated with ADHD and autism based on the investigated resting-state condition . In order to promote collaborations between researchers and research teams, and with the long-term aim of replicating these findings and advancing our knowledge of patterns of electrophysiological oscillatory activity during resting-state in ADHD, we would like to ask individual researchers and research teams to share their EEG data collected during resting-state in individuals with different psychological, psychiatric and neurodevelopmental conditions, including ADHD and autism. In this way, we would be able to create a publicly available repository of resting-state EEG data for further analysis. Full details about this can be found at the following link:


Virtual reality (VR) neuropsychological tests have emerged as a method to explore drug effects in real-life contexts in attention deficit hyperactivity disorder (ADHD) children. Functional near-infrared spectroscopy (fNIRS) is a useful tool to measure brain activity during VR tasks in ADHD children with motor restlessness. The present study aimed to explore the acute effects of methylphenidate (MPH) on behavioral performance and brain activity during a VR-based working memory task simulating real-life classroom settings in ADHD children. In total, 23 children with ADHD performed a VR n-back task before and 2 h after MPH administration concurrent with measurements of oxygenated hemoglobin signal changes with fNIRS. Altogether, 12 healthy control (HC) subjects participated in the same task but did not receive MPH treatment. Reaction time (RT) was shortened after MPH treatment in the 1-back condition, but changes in brain activation were not observed. In the 2-back condition, activation of the left dorsolateral prefrontal cortex (DLPFC) and bilateral medial prefrontal cortex (mPFC) was decreased alongside behavioral changes such as shorter RT, lower RT variability, and higher accuracy after MPH administration. Bilateral mPFC activation in the 2-back condition inversely correlated with task accuracy in the pre-MPH condition; this inverse correlation was not observed after MPH administration. In ADHD children, deactivation of the default mode network mediated by mPFC reduced during high working memory load, which was restored through MPH treatment. Our results suggest that the combination of VR classroom tasks and fNIRS examination makes it easy to assess drug effects on brain activity in ADHD children in settings simulating real-life. Attention-deficit/hyperactivity disorder (ADHD) is one of the most common neurodevelopmental disorders in children. ADHD is defined by age-inappropriate symptoms of inattention, impulsivity, and hyperactivity. Patients with ADHD exhibit complex multisystem impairments in fronto-cingulo-striato-thalamic and fronto-parieto-cerebellar networks that mediate attention, inhibition, working memory, and timing . In addiTo date, administration of psychostimulant drugs, especially methylphenidate (MPH), has been a treatment of choice for ADHD children . HoweverTo overcome these limitations, the utility of virtual reality (VR) has been recognized in terms of diagnosis and treatment of ADHD. VR facilitates the creation of dynamic, immersive environments with three-dimensional stimuli in which attention can be tested in an environment comparable to that experienced in the real world, improving ecological validity . In the However, few studies have evaluated brain activity during VR tasks in ADHD patients. One of the reasons for the paucity of research on brain activity during VR tasks is due to difficulties in examination. It is physically challenging to perform functional magnetic resonance imaging (fMRI) or single-photon emission computed tomography (SPECT) scanning while using VR devices, especially for young ADHD patients with motor restlessness. Moreover, research on drug effects requires repeated pre- and post-administration imaging, which necessitates employment of a simple and easy tool to measure brain function. In this context, research using functional near-infrared spectroscopy (fNIRS) has been growing. fNIRS is a non-invasive imaging technique that uses near-infrared light to measure functional brain activity through changes in concentration of oxygenated hemoglobin (HbO) and deoxygenated hemoglobin (Hb). The main advantage of fNIRS over other functional neuroimaging modalities such as fMRI, SPECT, or magnetoencephalography (MEG) is its portability . The fMRNevertheless, over the last few years, fNIRS has been used extensively to investigate cortical alterations in patients with various psychiatric disorders, such as schizophrenia; mood, anxiety, and eating disorders; and substance use disorder . For exaVarious studies using fNIRS have been conducted in ADHD patients. In most studies using tasks for evaluating attention or inhibition, ADHD patients exhibited lower prefrontal activity than that of healthy control (HC) subjects during the task –20 althoHowever, there has been limited research investigating the effects of medication on brain activity using fNIRS in VR tasks which simulates real-life classroom settings. As cognitive skills are ultimately applied in the classroom setting, especially in school aged children, attention and executive function can be better encapsulated in the virtual classroom environment than using traditional computerized neuropsychological tests. Furthermore, previous studies used the Go/No-go and oddball tasks mainly to explore inhibitory function. However, inhibition alone is insufficient to explain the pathophysiological mechanisms of ADHD. Working memory (WM) impairment is considered a core deficit of ADHD associated with prefrontal dysfunction.WM is defined as the ability to maintain information in an easily accessible state for a short period of time. According to the state-based model, the working memory contents are determined by perceptual & long-term memory representations being in a particular state of accessibility, maintained by neural activities controlled by the attentional processes  25). In. In25). The N-back task is a well-known working memory paradigm which has been used extensively in functional neuroimaging studies on ADHD . A few sBased on these findings, we aimed to investigate the acute effects of MPH on behavioral performance and brain activity of children with ADHD during a VR n-back task in a virtual classroom setting. To the best of our knowledge, this is the first study using a VR-based working memory task and fNIRS to explore the effects of MPH in ADHD children.Altogether, 23 right-handed Korean children with ADHD  and 12 healthy control (HC) children  participated in this study. The number of participants required for adequate statistical power was based on previous studies that investigated drug effects in ADHD patients through fNIRS –42 and aSeveral measurements were conducted to assess the psychological state of participants. The ADHD Rating Scales (ADHD-RS), an 18-question parent rating scale, was used to identify the presence of ADHD in children. Behavioral problems were assessed with the Korean version of the Child Behavior Checklist (CBCL), an 118-item parent-rated scale which queries behavioral problems in the past 6 months ; ChildreThe protocol used for this study was approved by the Institutional Review Board of Yonsei University College of Medicine Gangnam Severance Hospital. Written informed consent and assent were obtained from all participants and one of their parents.We investigated the effects of ADHD medication in a controlled pre- and post-MPH study design, whereby participants performed n-back tasks with the 1-back and 2-back conditions. The experimental protocol is summarized in The background of this VR task was a virtual classroom. The participants began by finding themselves in a typical classroom in a Korean school with desks facing ahead and blackboards in front of them. The participants' point of view was of the first person, facing the teacher, with other avatar classmates seated nearby . The mesThe n-back task consisted of three block sets. Each block set contained alternating 1-back (low WM load) and 2-back (high WM), and in-between 0-back (control) conditions . Each stimulus was presented for 500 ms with an interstimulus interval of 1.5 s. Overall block-set time was 160 s, and total session time was 8 min. The total number of trials in experimental conditions was 120. Subjects were instructed to press the button with their right index finger as quickly as possible, when the current stimulus was the same as the previously shown letter (1-back), or with the letter shown two screens back (2-back). Since it is extremely difficult for young ADHD patients to remain still when not performing a task, our baseline (control) task required participants to respond to each stimulus with a button press to rule out motion artifacts and equalize the motion load with the experimental task. To diminish habituation or practice effects in the post-MPH session, two task versions with different stimuli were employed. These two versions were randomly assigned to each subject.The software was written in Visual Studio 2017(C#) and designed on Unity 2018.2. The avatars and structures comprising the virtual environment were built using a 3Ds Max 2014. We used the 3D development platform  to develop the virtual classroom environment. Our VR classroom was implemented in the VR theater which provides a semi-immersive environment with a 2.18-m radius curved screen, providing 150° field-of-view . The averaged oxy-Hb concentration changes (avgΔHbO2) during the task period baselined from 5 s before task initiation was calculated in each channel after block averaging of multiple trials. Finally, the regional representative value of avgΔHbO2 was extracted by averaging categorized channels based on the specified region of interest (ROI). The selection of the brain ROI was completed before data analysis. The 48 channels were categorized as right and left dorsolateral prefrontal cortex (DLPFC), ventrolateral prefrontal cortex (VLPFC), medial prefrontal cortex (mPFC), and orbitofrontal cortex (OFC), which constituted eight ROIs. The channels corresponding to each region are shown in 2 per channel of each group according to 1-back and 2-back tasks.We used a multichannel high density fNIRS device , which consisted of 24 laser diodes emitting two wavelengths (780/850 nm) and 32 photodetectors separated by a 1.5 cm unit distance. The laser and detector pairs were separated at a 3 cm distance. Sampling rate was 8.138 Hz. The alignment of 48 channels is shown in For n-back task results, the total reaction time (RT), RT variability, and accuracy were used as dependent variables for analysis. RT variability was calculated by dividing the standard deviation of the individual RT by the mean value, as reported previously . We compt-test for numerical variables or Chi square (χ2) test for categorical variables. The means and standard deviations of avgΔHbO2 were calculated for each ROI and in each group to compare group differences and verify the effects of pre- and post-MPH effects on fNIRS results. For comparison of behavioral performance and fNIRS data between pre- and post-treatment conditions in ADHD participants, we used a two-tailed paired t-test. An independent two-sample two-tailed t-test was used for comparing variables between ADHD and HC groups. The normality of the data was evaluated by visual inspection of quantile-quantile plots and the Shapiro-Wilk test. To examine the association between behavioral performance and fNIRS data, we conducted correlation analysis using the Pearson's method. The statistical threshold was set at p < 0.05. All statistical analyses were completed with IBM SPSS version 25 .Group differences in clinical characteristics between ADHD and HC groups were compared using an independent sample t = −4.64, p < 0.001), ADHD-RS-inattention and hyperactive-impulsive subscales scores , CBCL total and attention problem subscale scores . The mean ADHD_RS score of the ADHD patients was 20.96, which indicates relatively mild level of ADHD severity. The SSQ score was low in both groups  with few symptoms. The typical mean MPH dose of ADHD subjects was 29.35 mg .Baseline characteristics of the study participants are presented in The average accuracy rates and RTs in each n-back task for HC and ADHD participants are summarized in 2 measured using fNIRS are presented in 2 changes were observed in any area when comparing pre- and post-MPH conditions  and mPFC activation. There was a negative correlation between accuracy and avgΔHbOThe present study aimed to investigate the feasibility of using fNIRS to investigate the neural substrates of single-dose MPH effects in children with ADHD during a VR working memory task. The combination of VR and fNIRS in this study revealed that this model was able to easily measure the effects of various drugs and interventions on children with ADHD in an environment simulating a real-world setting. Furthermore, it enables a setting that explores changes in brain activity during a neuro-rehabilitation program using VR environments. To our knowledge, this is the first study using a VR environment to measure the impact of MPH on working memory with fNIRS in ADHD subjects.In the current study, task performance improved after MPH treatment; this was verified by shorter RT in the 1-back condition and shorter RT, lower RT variability, and higher accuracy in the 2-back condition compared to that in pre-medicated ADHD subjects. This result is generally consistent with previous studies reporting performance enhancing effects of MPH in ADHD patients –55. ConvWe observed increased activation in the left DLPFC and bilateral mPFC in pre-medicated ADHD subjects during the VR 2-back task, which decreased after MPH administration. However, there were no significant differences between HC and ADHD children. In most NIRS studies comparing children with ADHD to HCs in different executive functioning tasks, altered prefrontal activity was reported: some studies reported reduced activity in ADHD –19, wherIncreased activation in bilateral mPFC was negatively correlated with accuracy of the 2-back task in pre-medicated ADHD subjects, whereas this association disappeared after MPH treatment. This result implies that mPFC was abnormally hyper-activated in ADHD subjects during the 2-back task, which was accompanied by low performance. The mPFC is a brain region that constitutes the default mode network (DMN) along with the medial and lateral parietal and temporal cortices . The DMNBy contrast, in the 1-back condition, we found no difference in brain activation between pre- and post-MPH conditions. Given that only RT was shorter after MPH treatment for behavioral performance, and there was no significant difference in accuracy or RT variability, it can be assumed that the difference before and after drug was minimal due to the low level of 1-back difficulty, reflected by a ceiling effect from the pre-test. The only study that explored the effect of MPH during the n-back task in ADHD children reported no differences in brain function in the 1-back condition between pre- and post-drug administration, which is concordant with our study . In addiIn the present study, the VR classroom environment provided a more ecologically valid and motivating task than that of traditional computerized cognitive tasks, suggested by the improved task performance of ADHD children. We propose several advantages of using a VR task over traditional computerized WM tasks. Previous studies have indicated that ADHD children find digital technology environments more enjoyable and are more immersed in the task , 68. NonOur study has several limitations which we hope to address in future studies. First, the study design was not optimized for neuropharmacological analysis. A double-blind placebo-controlled or a cross-over design with drug-naive ADHD children should be conducted. Since we did not include a placebo group, the superior task performance in post-MPH ADHD subjects could be due to a repeat effect. In addition, unlike the ADHD patients, the HC did not repeat the tests, making it difficult to compare the HC group with the post-MPH group or to eliminate the time effect. Therefore, it is not entirely clear whether the changes in brain activation in the ADHD group were truly induced by the treatment or were simply a function of time. However, considering the NIRS imaging results, the improved behavioral performance was accompanied by changes in brain activity such as reduced hyperactivity of bilateral mPFC in post-MPH ADHD subjects, making it difficult to fully explain solely based on repeat effects. Further, WM tasks are generally considered to have strong test-retest reliability and to be relatively unaffected by practice effects . In addiTo our knowledge, this is the first study to explore the effects of MPH on brain activity during a VR-based WM task reproducing real-classroom settings in ADHD children. We observed that activation of bilateral mPFC decreased after MPH treatment in a high-load WM task. Further, bilateral mPFC activation was negatively correlated with task accuracy in pre-MPH condition; this correlation disappeared after MPH administration. These findings suggest that mPFC-mediated inappropriately excessive mind-wandering during a high-load WM task in ADHD children may have disappeared after MPH administration. Taken together, these results suggest that the combination of VR tasks and fNIRS examination is a technique that enables examination of the effects of interventions within a real-life setting in ADHD children and adolescents.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving human participants were reviewed and approved by Institutional Review Board of Yonsei University College of Medicine Gangnam Severance Hospital. Written informed consent to participate in this study was provided by the participants' legal guardian/next of kin. Written informed consent was obtained from the minor(s)' legal guardian/next of kin for the publication of any potentially identifiable images or data included in this article.EK and NL devised the project, the main conceptual ideas, and proof of the outline. EK, NL, and JY designed the detailed study design. JY, NH, JK, and JH examined participants, performed the experiments, and acquired and organized the data. SJ and JC conducted analyses of the experimental data, drafted the manuscript, and designed the figures with supervision from EK. JO and J-jK contributed to interpreting the results and worked on the manuscript. All authors discussed the results and commented on the manuscript. EK supervised the project. All authors contributed to the article and approved the submitted version.JC was employed by OBELAB Inc. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.


U = 22,642.0, p = 0.81, r = 0.01; log rank: p = 0.81). Adolescents with ADHD  did not take longer than those without ADHD  to return to sports . Medication status and concussion history were not associated with longer recovery times. Adolescents with ADHD did not take longer to functionally recover following concussion. Recovery times did not differ based on whether adolescents with ADHD reported taking medication to treat their ADHD or whether they reported a prior history of concussion.The objective of this study was to determine whether adolescents with attention-deficit/hyperactivity disorder (ADHD) have prolonged return to school and sports following concussion compared to those without ADHD and whether medication status or concussion history is associated with recovery time. We hypothesized that having ADHD would not be associated with longer recovery time. This prospective observational cohort study, conducted between 2014 and 2019, examined concussion recovery among school sponsored athletics throughout Maine, USA. The sample included 623 adolescents, aged 14–19 years , 43.8% girls, and 90 (14.4%) reported having ADHD. Concussions were identified by certified athletic trainers. We computed days to return to school (full time without accommodations) and days to return to sports (completed return to play protocol) following concussion. Adolescents with ADHD  did not take longer than those without ADHD  to return to school ( A concussion is a mild traumatic brain injury . PrimaryMost concussed children and adolescents experience rapid symptom improvement during the first 2 weeks after injury, and symptoms lasting longer than 1 month are considered “persistent” –20, the This is a prospective observational cohort study of adolescent student athletes throughout the state of Maine, USA, conducted between 2014 and 2019 (5 academic years). Athletic trainers or another school official used the Head Injury Tracker (HIT), a free injury surveillance application created by the Maine Concussion Management Initiative, to monitor concussion recovery. In the first year, the HIT was deployed to 4 schools, 28 schools were enrolled during the second year, and by the final year, it was used in 10 schools. The HIT database includes 673 adolescents aged 14–19 years who sustained a sport-related concussion between September 2014 and June 2019. From this original sample, 30 were excluded because dates were missing for both return to school and return to sports, and 20 were excluded because of problematic dates that, because of data deidentification procedures, could not be confirmed/checked for accuracy and had a high probability of being data entry errors.n = 273, 43.8%) and boys . Of these athletes, 90 (14.4%) self-reported a preinjury history of ADHD. A higher proportion of boys reported having preinjury ADHD compared to girls . For boys, the sports played at the time of injury were football (36.9%), soccer (20%), basketball (9.1%), lacrosse (8.6%), ice hockey (6.9%), and several other sports (18.5%). For girls, the sports played at the time of injury were soccer (34.8%), basketball (12.1%), spirit squad (12.1%), field hockey (8.1%), ice hockey (5.1%), and several other sports (27.8%). Among the students with ADHD, 37 (41.1%), self-reported taking medication to treat their ADHD.The final sample included 623 adolescents aged 14–19 years . The sample was almost equally split between girls , and there were no differences in rates of missing outcome data based on ADHD status .Date of return to school was not available for 12 participants (1.9%), and date of return to sports was not available for 35 participants (5.6%). Rates of missing outcome data did not differ between sexes .Athletic trainers or other school officials entered the date students returned to school (full time without accommodations) and the date they returned to sports (completed return to play protocol) following their concussion. Recovery time was calculated as the number of days between the injury date and the date of return to school and the date of return to sports.The HIT application is an online injury surveillance platform. When an adolescent sustained a concussion, an athletic trainer or school official entered information about the injury and their recovery via smartphone or webpage. All athletic trainers/school officials involved in data collection completed an online training about the HIT application format and the process for entering information. Adolescents and schools were not compensated for their participation. A dedicated HIT project coordinator provided technical assistance and data collection oversight. Institutional review board approval for the creation of the deidentified database and its use for research was obtained.U tests were employed to assess whether adolescents with ADHD took longer to return compared to those without ADHD. Survival analysis (Kaplan–Meier with log rank tests) was used to compare the recovery times of adolescents with and without ADHD (censored at 28 days). To maximize the clinical relevance of these findings, each adolescent's return to school/sports status was also dichotomized  at various recovery benchmarks  and χ2 tests compared the proportion of those with and without ADHD who had not yet returned to school or sports at these various time points. Cumulative recovery curves were constructed to visually display the proportion of adolescents who returned to school or sports over time. The Mann–Whitney U-test Z-values were used to calculate a non-parametric effect size r, where r=r = 0.1 , r = 0.3 (medium), and r = 0.5 (large)  were computed as effect sizes (The outcome variables (days to return to school and days to return to sports) were non–normally distributed; thus, Mann-Whitney re r=Z√N , which w (large) . For χ2 ct sizes  and intect sizes , i.e., Op = 0.14) or days to return to sports . Days to return to school was significantly positively correlated with days to return to sports . The ADHD group contained a significantly greater proportion of boys (76.7%) compared to the no-ADHD group (52.7%), p < 0.001. However, among the full sample, girls and boys did not differ on days to return to school  or sports . Youth with ADHD (41.1%) were more likely than those without ADHD (30.4%) to report having a prior concussion, p = 0.04. A greater proportion of youth with ADHD (18.9%) self-reported a history of depression compared to youth without ADHD (6.4%), p < 0.001. Among youth reporting a history of depression, rates of medication to treat depression were similar between youth with ADHD (64.7% reporting medication) and without ADHD (61.8% reporting medication).Demographic characteristics of the sample are presented in U = 22,642.0, p = 0.81, r = 0.01). The survival distributions for days to return to school did not differ between students with or without ADHD (log rank: p = 0.81). Adolescents with ADHD were not more likely to remain out of school at 3, 5, 7, 10, 14, 21, or 28 days following injury . The survival distributions for days to return to sports did not differ between those with and without ADHD (log rank: p = 0.48). Adolescents with ADHD were not more likely to remain out of sports at 7, 10, 14, 21, or 28 days following injury . Adolescents with ADHD who were not taking medications (median = 14) did not take longer to return to sports than those with ADHD who reported taking medication . Rates of adolescents with ADHD who remained out of school at 3, 5, 7, 10, 14, 21, or 28 days and sports at 7, 10, 14, 21, or 28 days following injury did not differ between those who did and did not report taking ADHD-medication .Adolescents with ADHD who were not taking medication (median = 6) did not take significantly longer to return to school than those with ADHD who reported taking medication . Adolescents with ADHD and a history of prior concussion (median = 13) did not take longer to return to sports than those with ADHD and no history of prior concussions . Rates of adolescents with ADHD who remained out of school at 3, 5, 7, 10, or 14 days following injury did not differ between those with and without a history of prior concussion (p's > 0.05). By 21 days following injury, all students with ADHD and prior concussions (100%) had returned to school, compared to 84.6% of students with ADHD and no prior concussions at 21 days (p = 0.01) and 88.5% of these students at 28 days (p = 0.04). Rates of adolescents with ADHD who remained out of sports at 7, 10, 14, 21, or 28 days following injury did not differ between those who did and did not report a history of prior concussion .Adolescents with ADHD and a history of prior concussion (median = 6.5) did not take longer to return to school than those with ADHD and no history of prior concussion , the largest study to date examining whether youth with ADHD are at risk of worse outcome following sport-related concussion and the first to examine days to return to school as an outcome. We leveraged data from a statewide injury surveillance platform that was integrated into school-sponsored athletics to examine 90 adolescents with ADHD. There were no differences between adolescents with ADHD and those without ADHD in days to return to school full time without accommodations or days to return to sports following concussion. Nearly all available studies have also found no statistically significant association between ADHD and worse clinical outcome from concussion, although many were hampered methodologically by small or very small sample sizes , 28–38, not take longer to recover compared to those with ADHD and no prior concussions.This study is also novel in that it is the first to examine whether youth with “treated” vs. “untreated” ADHD experience different concussion recovery. Among adolescents with ADHD, recovery times did not differ based on whether students reported taking medication to treat their ADHD. Additionally, youth with ADHD were more likely than those without ADHD to report having sustained a prior concussion, which is consistent with multiple prior studies –16. HoweThis study includes a comprehensive investigation of functional recovery, investigating how long it took for adolescents to return to school and to return to sports. Some prior studies define recovery in terms of symptom reporting and/or medical clearance , 39, 40.International Classification of Diseases, 10th Revision symptom criteria for postconcussional syndrome , including symptoms that “overlap” with ADHD, such as difficulty concentrating, but also symptoms that are not necessarily reflective of ADHD, such as headaches, dizziness, fatigue, and light sensitivity , 45–50. syndrome , 46. Secsyndrome –53 and bsyndrome  concussisyndrome , and thesyndrome , 34, 38.syndrome , especiaThe health history information, including ADHD status, ADHD medication status, and concussion history, was self-reported. We were not able to verify the accuracy of adolescent self-reported health history, nor did we have details about their diagnoses, such as by whom their ADHD was diagnosed  or medication treatment . This limitation is common in sport concussion research. Notably, adolescent athletes asked about their health history an average of 2 years apart are highly consistent in their report of their concussion history and whether they have ADHD . Future Adolescents with ADHD did not take longer to functionally recover following concussion. Among adolescents with ADHD, taking ADHD medication was not associated with recovery time or having a prior concussion history. These findings suggest that a preexisting history of ADHD, in and of itself, is not a risk factor for prolonged recovery or worse outcome following concussion. Additional research is needed to determine if there are other vulnerability factors in youth with ADHD that confer risk of worse outcome.The original contributions presented in the study are included in the article, further inquiries can be directed to the corresponding author. The statistical code, syntax, output, and analyses are available to qualified researchers upon request.The studies involving human participants were reviewed and approved by Colby College Institutional Review Board (IRB). Written informed consent from the participants' legal guardian/next of kin was not required to participate in this study in accordance with the national legislation and the institutional requirements.NC and GI contributed conception and design of the study. BM helped develop the injury surveillance application and organized the database. NC performed the statistical analyses and wrote the first draft of the manuscript. GI wrote sections of the manuscript. BM and PB helped design and coordinate data collection. RZ critically reviewed and edited the manuscript. PB wrote the IRB, conceptualized the overall project. All authors contributed to manuscript revision, read, and approved the submitted version.® Applications Systems, Psychological Assessment Resources, and CNS Vital Signs. He has received research support from the Harvard Integrated Program to Protect and Improve the Health of NFLPA Members, and a grant from the National Football League. He serves as a scientific advisor for BioDirection, Inc, Sway Medical, Inc., and Highmark, Inc. RZ has received salary support from the Harvard Integrated Program to Protect and Improve the Health of National Football League Players Association Members. He serves on the Scientific Advisory Board of Myomo, Oxeia Pharma, and ElMInda. The authors declare that this study received funding from the National Football League and ImPACT® Applications, Inc. The funders were not involved in the study design, collection, analysis, interpretation of data, the writing of this article, or the decision to submit it for publication. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.GI has been reimbursed by the government, professional scientific bodies, and commercial organizations for discussing or presenting research relating to MTBI and sport-related concussion at meetings, scientific conferences, and symposiums. He has a clinical practice in forensic neuropsychology, including expert testimony, involving individuals who have sustained mild TBIs (including athletes). He has received honorariums for serving on research panels that provide scientific peer review of programs. He is a co-investigator, collaborator, or consultant on grants relating to mild TBI funded by the federal government and other organizations. He has received research support from test publishing companies in the past, including ImPACT


Actigraphy, an objective measure of motor activity, reliably indexes increased movement levels in attention-deficit/hyperactivity disorder (ADHD) and may be useful for diagnosis and treatment-monitoring. However, actigraphy has not been examined in complex neurodevelopmental conditions. This study used actigraphy to objectively measure movement levels in individuals with a complex neurodevelopmental genetic disorder, tuberous sclerosis (TSC). Thirty participants with TSC  underwent brief (approximately 1 h) daytime actigraph assessment during two settings: movie viewing and cognitive testing. Multiple linear regressions were used to test associations between movement measurements and parent-rated ADHD symptoms. Correlations were used to examine associations between actigraph measures and parent-rated ADHD symptoms and other characteristics of TSC (symptoms of autism spectrum disorder (ASD), intellectual ability (IQ), epilepsy severity, cortical tuber count). Higher movement levels during movies were associated with higher parent-rated ADHD symptoms. Higher ADHD symptoms and actigraph-measured movement levels during movies were positively associated with ASD symptoms and negatively associated with IQ. Inter-individual variability of movement during movies was not associated with parent-rated hyperactivity or IQ but was negatively associated with ASD symptoms. There were no associations with tuber count or epilepsy. Our findings suggest that actigraph-measured movement provides a useful correlate of ADHD in TSC. Attention-deficit/hyperactivity disorder (ADHD) is a common neurodevelopmental condition characterised by developmentally inappropriate and impairing symptoms of inattention, hyperactivity, and impulsivity . ExcessiTSC1 or TSC2 genes, whose proteins form an essential complex for regulating development [However, there are limited data using objectively measured activity to assess ADHD symptoms in more complex presentations of the disorder, such as in young people with developmental genetic disorders such as tuberous sclerosis (TSC). TSC is characterised by the growth of hamartomas in multiple organs, including the kidneys, lungs, heart, liver, and brain . These lelopment . Brain pelopment . In addielopment . Epidemielopment ,18,19,20elopment .There are a number of important reasons for investigating objective measures of activity levels in complex developmental disorders. First, actigraphs may be useful for diagnosis and treatment-monitoring of ADHD in these settings, as has been proposed in idiopathic ADHD ,9. AssesIn the current study, we aimed to investigate these potential benefits by firstly assessing whether objective, actigraph-measured movement levels and variability of movement (movement IIV) would be associated with parent-rated ADHD symptoms in a sample of young people with TSC and varying levels of intellectual ability, epilepsy, and symptoms of ASD. Actigraph measurements were obtained in two situational contexts, movie viewing and cognitive testing, during a short (approximately 1 h) daytime testing battery. Parent-rated ADHD symptoms were measured with the Strengths and Difficulties Questionnaire (SDQ) , which hThis study utilised a subsample of the Tuberous Sclerosis 2000 (TS2000) study, a longitudinal investigation that has collected prospective data on a cohort of 125 individuals with TSC in the United Kingdom since 2005 . Thirty ADHD symptoms: Parent-rated ADHD symptoms were measured using the SDQ Hyperactivity/Inattention subscale, which consists of 5 questions assessing hyperactivity, impulsivity, and inattention [ttention . Higher Intellectual ability: IQ was measured with the two-subtest version of the Wechsler Abbreviated Scale of Intelligence–2nd Edition (WASI-II) [N = 20). Age- and sex-normed full-scale intelligence quotients  were used in analysis. For participants who could not complete the WASI-II due to intellectual disability (N = 10), the Vineland Adaptive Behaviour Scales–2nd Edition (VABS-II) [WASI-II) , a standVABS-II)  was compVABS-II) ,43,44.ASD symptoms: Symptoms of ASD were assessed using the Autism Diagnostic Interview-Revised (ADI-R), a comprehensive, structured interview conducted with a parent/guardian of each participant [ticipant . The totGenotype: Determination of participants’ TSC mutations was carried out by either the East Anglian Medical Genetics Service (Cambridge) or the Institute of Medical Genetics (Cardiff). Multiplex ligation-dependent probe amplification was used to assay mutation status, with additional testing for whole exon deletions [eletions . ParticiEpilepsy: The Early Childhood Epilepsy Severity Scale (E-Chess) was used to give a current index of epilepsy severity over the 3 months prior to testing [ testing . The E-CBrain imaging: Copies of clinical brain scans were procured from participants’ physicians. Clinical MRI or CT scans were assessed by two independent neuroradiologists, using a previously described system for coding the number and location  of cortical tubers and SENs [and SENs ,43. In tParticipants wore two Move 3 actigraphs , one at their right hip and one on the wrist of their non-dominant hand . Actigraph data were collected while participants completed two cognitive tests: the Test for Reception of Grammar (TROG-2)  and the mean movement  and threshold movement . The coefficient of variation (CoV) (mean/standard deviation * 100) for these measurements was computed for each participant to provide a measure of IIV. As mean movement and threshold movement were highly correlated within both task and movie settings , the two measures were standardised using z-scores and averaged to yield a single actigraph-measured movement measure during cognitive testing and another during movie viewing. CoVs were standardised and averaged in the same manner to yield an actigraph-measured movement IIV during movies and cognitive testing.Activity levels were initially computed in units of α = 0.05. To test the hypothesis that actigraph-measured movement and movement IIV would be positively associated with parent-rated ADHD symptoms, multiple linear regression models were constructed with actigraph variables (actigraph-measured movement and actigraph-measured movement IIV) as predictors and SDQ Hyperactivity/Inattention scores as the outcome; separate models were used for actigraph-measured movement and for actigraph-measured movement IIV. Age and testing location (home versus lab) were controlled for in these models in a second block. In addition, to check whether the fact that four participants would only tolerate a movie of their choosing influenced the findings, regression models examining the prediction of SDQ Hyperactivity/Inattention from actigraph variables during movie viewing were repeated with these participants omitted.All statistical analyses were conducted in Jamovi , with α TSC1 mutations (n = 3), associations between TSC genotype and actigraph measures and parent-rated ADHD symptoms were not examined.Next, to explore which features of TSC would be associated with actigraph measurements and parent-rated ADHD symptoms, Spearman correlations were computed between actigraph measures and SDQ Hyperactivity/Inattention and the variables IQ, ASD symptom scores, tuber counts, SENs, and epilepsy severity scores. Partial correlations were used to include adjustment for age and testing location. Due to the small number of participants with TSC2 were the most common mutation type (18/30). The average IQ of the sample was 70.6, denoting borderline intellectual impairment. Individuals ranged from having severe IQ deficits to having a normal IQ (range = 35–108); 14 participants had an IQ < 70. Due to issues of tolerability and intellectual impairment, some participants did not complete all assessments (see n = 28) than with cognitive testing (n = 20).Thirty individuals with TSC were assessed with actigraphs; characteristics of the sample and assessments are presented in ents see . More paR2 = 0.106, adj. R2 = 0.056, F = 2.1, p = 0.161) or after  adjustment for age and testing site  or after adjustment for age and testing site   B.R2 = 0.310, adj. R2 = 0.276, F = 9.0, p = 0.007; actigraph-measured movement during movies: β = 0.557, p = 0.007)  and actigraph-measured movement remained a significant predictor (β = 0.566 p = 0.011). Movement IIV during movies trended towards negatively predicting ADHD symptom ratings  .Actigraph-measured movement during movies, on the other hand, was positively associated with ADHD symptoms (= 0.007) C. After = 0.054) D, yet thR2 = 0.333, adj. R2 = 0.296, F = 9.0, p = 0.008; actigraph-measured movement during movies: β = 0.577, p = 0.008), and this association became marginal after adjusting for age and testing location . Actigraph-measured movement IIV was also significantly negatively associated with ADHD symptoms , but this association became non-significant after adjustment for age and testing site .The pattern of results were similar when omitting participants who only tolerated movies of their choosing; actigraph-measured movement during movies was significantly positively associated with parent-rated ADHD symptoms  and actigraph-measured movement during movies . These associations were maintained after partialling out the effects of age and testing site  , but this association became marginal after adjustment for age and testing site   and parent-rated ADHD symptoms and actigraph measures. Actigraph measurements during cognitive testing were not included in this analysis, as these variables showed no association with parent-rated ADHD symptoms. IQ was significantly negatively correlated with both parent-rated ADHD scores (< 0.001) A,B. IQ w= 0.057) C.rho = 0.403, p = 0.070), and this association became significant after adjustment for age  , and this relationship remained significant after adjustment for age and testing location   and after  adjustment for testing location and age (Parent-rated ADHD symptoms tended to be positively correlated with ASD symptoms (= 0.040) D. Actigr< 0.001) E. Actigr and age F.rho < 0.190, p > 0.05).Neither current epilepsy severity, total tubers, nor SENs were correlated with movie activity, movie activity IIV, or parent-rated ADHD symptoms  have, although these are only suitable for individuals with higher intellectual abilities. One study by Vries et al.  reportedWe found associations between actigraph-measured movement and parent-rated ADHD symptoms during movie viewing, but not during cognitive testing. This dissimilarity could stem from context-dependent differences in the presentation of hyperactive ADHD symptoms ,52. SituResults further indicated IQ and ASD symptoms to be correlates of actigraph-measured movement in TSC. Participants with lower IQs exhibited higher movement levels during movies as well as more ADHD symptoms. This finding resonates with previous cross-sectional studies that documented a higher prevalence of ADHD or its symptoms  in children with ID  or lowerWe found weak evidence that participants with higher ADHD symptom ratings had lower actigraph-measured movement IIV. We also found that movement IIV was negatively associated with ASD symptoms, and movement IIV also trended towards being positively associated with IQ. Interestingly, the direction of these correlations was opposite to that of actigraph measured-movement; i.e., actigraph-measured movement being positively correlated with ADHD and ASD symptoms but movement IIV being negatively correlated with the two symptom measures. We had expected elevated movement IIV to be associated with more severe ADHD symptoms, given previous results indicating behavioural variability to be a hallmark of ADHD ,31 as weTSC2 mutations are associated with more severe pathology in general [This study did not find evidence of associations between biological factors of TSC  and actigraph measurements. Previous investigations into the biological correlates of ADHD in TSC have been limited and inconclusive. While one epidemiological study reported a correlation between SENs and ADHD symptoms , another general , but the general ; similarThere are some limitations to this study that should be noted. There was variability in the manner by which participants underwent actigraph assessment, e.g., testing was done in two locations (home and lab), and participants did not all see the same movie clips, as some children would only tolerate movies of their choosing. We addressed these issues by statistically adjusting for the testing location and rerunning analyses with some participants excluded, which did not alter the associations with ADHD symptoms. We also did not control for the time of day when actigraph assessments were collected, which is known to affect the presentation of ADHD ,66 and hThis preliminary study found that actigraph-measured movement was significantly associated with parent-rated ADHD symptoms in a sample of young people with TSC and varying levels of ADHD symptoms as well as intellectual ability and autism symptoms. Actigraphy provided an objective measure of hyperactivity that was appropriate for individuals with diverse abilities and difficulties. Further development of the actigraph method in TSC may be useful for the study and clinical evaluation of ADHD in complex neurodevelopmental conditions.


Previous studies suggest that childhood attention deficit hyperactivity disorder (ADHD) may continue in adulthood, producing adverse effects. Therefore, identifying factors that help to differentiate characteristics of ADHD persistence and remission has practical implications for evaluation and treatment. The first aim of this study was to analyze differences in executive functions , symptoms associated with ADHD , and functional impairments in adults with persistent ADHD (ADHD-P), with remittent ADHD (ADHD-R), and without ADHD (N-ADHD). The second aim was to study the contribution of functional impairments in these three groups based on executive functions and associated ADHD behaviors.Participants were 115 adults, 61 with a childhood ADHD diagnosis (40 persisters and 21 remitters) and 54 individuals with typical development. Self-reports were collected on executive functions, symptoms associated with ADHD, and functional impairments. Multivariate Analyses of Variance were conducted to test differences between the ADHD-P, ADHD-R, and N-ADHD groups on the evaluated variables. In addition, analyses were performed using two structural equation models with observed variables .The results indicated that significant executive and behavioral impairments and adverse functional outcomes in different life domains are related to the diagnostic persistence of ADHD. Recovery from the disorder is associated with better results, although hyperactivity/restlessness behaviors and plan/organize deficits continue to be present in remitter individuals.The ADHD-P and ADHD-R groups showed some differences in their executive, behavioral, and functional impairments. Furthermore, the impairments in each group can be predicted by different executive functions and other symptoms associated with the disorder. These results should be taken into account in order to improve clinical practice. ADHD is a disorder that frequently continues in adulthood. For many people, it is chronic, even though the data on its persistence from follow-up studies are not congruent, with percentages ranging from 4 to 77%. This great variability may be due, above all, to the variety of methods and cut-off points established to diagnose ADHD, the assessment procedures used, the age when beginning the study and follow-up, and the requirement (or not) of the presence of impairments. A recent systematic review concluded that, although few persistence studies have applied strict criteria, those that have done so found ADHD persistence rates close to 50% , which cAdults with ADHD suffer from a pattern of functional impairment in a wide variety of daily work and academic activities, multiple risky behaviors , financiThe executive system includes a broad range of processes associated with the prefrontal and thalamic-reticular areas of the brain, responsible for directing and regulating cognitions, emotions, and behavior in order to reach a desired goal. There is evidence that EF deficits may be core components of the complex neuropsychology of ADHD . SupportAn analysis focusing on the role of the executive processes that have more discriminatory power  in the pOn the other hand, without a doubt, adults with ADHD commonly have additional problems, such as feelings of restlessness, unfocused mental activity and memory problems, emotional dysregulation, or low self-esteem –22. ThesIn summary, in the past decade, evidence has been accumulated about the differences between adults with a childhood ADHD diagnosis and N-ADHD in EF , 7 and pThe specific aims were: (1) to analyze differences in EF , behaviors associated with ADHD , and general functional impairments in ADHD-P, ADHD-R, and N-ADHD adults; and (2) to examine the contribution of EF and ADHD associated behaviors to the functional impairments of adults with ADHD-P and ADHD-R. We expected that the ADHD-P group would exhibit greater EF deficits and severity of behavioral symptoms linked to the disorder than the ADHD-R and N-ADHD groups. On the other hand, the ADHD-R group would present better EF and fewer ADHD associated behaviors than the ADHD-P, although they would present more deficits than the N-ADHD group. We also expected that the EF and behaviors associated with ADHD would contribute to the general functional impairment of the two groups with ADHD and the N-ADHD group.This is a descriptive cross-sectional design between a group of adults with a childhood ADHD diagnosis twelve years after the initial diagnosis and a N-ADHD group, that were matched on sex, age and IQ estimated Participants with ADHD came from the Spanish sample from the International Multicenter ADHD Genetics (IMAGE) study, a prospective study of children with ADHD with combined subtype (ADHD-C), recruited between 2003 and 2006. Clinical diagnosis was based on combining information from the Parental Account of Childhood Symptoms  interviet (79) = − 0.60, p = .549) or teachers’ (t (79) = 0.37, p = .712) ratings on the DSM-total, the gender  or educational level of the parents (t = (79) = −.970, p = .334).On average, 12 years later, from 2013 to 2017, contact was again made with the families to request their collaboration. Youths with ADHD and a family informant were given verbal and written information about the study to be carried out. Sixty-one individuals gave their consent to participate before beginning the first evaluation session in the present follow-up phase . The retention rate was 75.31% (61 from 81): thirteen subjects (16.05%) did not participate because we could not locate them, and seven declined the invitation to attend the evaluations. There were no differences in ADHD severity between the 61 children who continued in the follow-up and the 20 who did not participate, based on the parents’ , with IQs within the average range . Of them, 95.1% were men, and 4.9% were women. Most of the subjects (> 80%) had taken medication, mainly stimulants, at some point in time.ADHD symptoms were measured with the Conners Adult Rating Scale  (CAARS),The N-ADHD group was composed of 54 young adults who were selected according to the criteria of the Spanish National Institute of Statistics for the distribution of the population between 18 and 24 years old, based on their grade level and employment status. We contacted them by spreading information about this research project in universities, vocational training schools, and secondary schools, and participation was voluntary. All the individuals met the following criteria: a) no history of significant inattention or hyperactivity-impulsivity problems; b) T scores below 65 on Conners’ ADHD subscales; c) absence of neurological disorders, sensory or motor impairments, autism, or psychosis; d) IQ equal to or greater than 70.2 = 2.81, p = 0.24), age  = 2.85, p = 0.07), and estimated IQ  = 1.62, p = 0.20).The three groups, ADHD-P, ADHD-R, and N-ADHD, were matched on sex χnot at all, never, and 3 = very much, very frequently. Three of the eight subscales correspond exactly to the DSM-IV diagnostic criteria for ADHD and its subtypes . Post hoc group comparisons showed statistically significant values for inhibition, shift, working memory, and plan/organize  = .57, 293 F2,112) = 8.69, 12 = 8.69 = 15.82, p < .001, η2 p = .36]. Post-hoc analysis showed statistically significant differences in inattention/memory, hyperactivity/restlessness, impulsivity/emotional lability, and self-concept problems. The two ADHD-P and ADHD-R groups presented inattention/memory problems that were statistically higher than the N-ADHD group. The ADHD-P group presented greater problems than the other two groups, ADHD-R and N-ADHD, on hyperactivity/restlessness and impulsivity/emotional lability, and it obtained significantly higher scores than the ADHD-R group on self-concept problems. However, the ADHD-R group was only statistically different from the N-ADHD group on hyperactivity/restlessness.The MANOVA performed to evaluate the differences in ADHD associated behaviors among the three groups was statistically significant . According to the results of the post-hoc analyses  = .50, F,112 = 7.Analyzing functional impairment with EF of Inhibition, shift, working memory, and plan/organize.2(1) = .761, p = .38, CFI = 1, SRMR = .008.First, a path analysis was estimated to explore functional impairment in the whole sample, in order to establish a model that fit the data. This model fit the data very well: χ2(3) = .796, p = .85, CFI = 1, SRMR = .01. Then, all the effects of the predictors on total functional impairment were constrained to be equal to those of the N-ADHD group. That is, the four effects of the predictors were estimated in the N-ADHD group and then fixed to those values in the other groups. Model fit deteriorated: χ2(9) = 6.66, p = .67, CFI = .98, SRMR = .049. Therefore, a sequence of models was estimated in which one parameter at a time was unconstrained until a model with the same (or better) fit as the baseline model (unconstrained) was found. The best fitting model showed the moderation of the effects of working memory on total functional impairment (χ2(7) = 2.47, p = .92, CFI = 1, SRMR = .02.The multi-group routine starts by estimating the model simultaneously in the three groups , but without constraints, where all the parameters in each group are free. This model adequately fit the data: χp > .05 and β = .103, p > .05, respectively. The effect of inhibition was positive and statistically significant . The effect of plan/organize on functional impairment was group-specific (a moderation effect of group). Specifically, the effect of this function on impairment was .013 (p > .05) in the N-ADHD group, .292 (p = .012) in the ADHD-R group, and .357 (p < .001) in the ADHD-P group. In sum, plan/organize affected the total impairment more in the ADHD-P group than in the ADHD-R group, and this effect was not statistically significant in the N-ADHD group. R-squares in the three groups  were, respectively: .18, .34, and .28.In this model, the effects of inhibition, shift, and working memory on functional impairment were equal across groups. The effects of shift and working memory were not statistically significant: β = .132, Analyzing functional impairment with ADHD behaviors of inattention, hyperactivity/ restlessness, impulsivity/emotional lability, and self-concept problems.2(1) = 9.55, p = .002, CFI = .91, SRMR = .087.A second path analysis to examine functional impairment using new predictors  was estimated in the whole sample, in order to establish a model that fit the data. This model fit the data well: χ2(3) = 10.11, p = .017, CFI = .92, SRMR = .10. Then, all the effects of the predictors on functional impairment were constrained to be equal to those in the N-ADHD group. That is, the four effects of the predictors were estimated in the N-ADHD group and then fixed to those values in the other groups. Model fit considerably deteriorated: χ2(9) = 28.34, p < .001, CFI = .76, SRMR = .13. Accordingly, a sequence of models was estimated in which one parameter at a time was unconstrained until a model with the same (or better) fit as the baseline model (unconstrained) was found. The model with the best fit showed the moderation of the effects of inattention and impulsivity/lability on total functional impairment (χ2(7) = 6.35, p = .49, CFI = 1, SRMR = .046.The multi-group routine starts with the model estimated simultaneously in the three groups , but without constraints, where all the parameters in each group are free. This model adequately fit the data: χp > .05), whereas the effect of self-concept was positive and statistically significant . However, the effects of inattention and impulsivity/emotional lability on functional impairment were group-specific (moderation effect of group). Specifically, the effect of inattention on impairment was .292 (p = .009) in the N-ADHD group, −.108 (p > .05) in the ADHD-R group, and .384 (p < .001) in the ADHD-P group. In sum, inattention affected functional impairment more in the ADHD-P group than in the N-ADHD group, and this effect was not statistically significant in the ADHD-R group. Regarding the effect of impulsivity/emotional lability on total impairment, the effect was .286 (p = .039) in the N-ADHD group, .611 (p < .001) in the ADHD-R group, and .225 (p < .001) in the ADHD-P group. In summary, the effect of impulsivity/emotional lability was much larger in the ADHD-R group than in the other two groups, which did not significantly differ on this effect. R-squares in the three groups  were .43, .55, and .41, respectively.In this model, the effects of hyperactivity/restlessness and self-concept on impairment were equal across groups. The effect of hyperactivity/restlessness was not statistically significant . A first objective, comparing ADHD-P, ADHD-R, and N-ADHD, was to identify which executive and behavioral problems are present in adults with persistent and remittent ADHD and determine whether recovery is associated with a better development. It was hypothesized that ADHD-P individuals would display more executive impairments, more severe problems commonly associated with the disorder, and more functional impairments than the ADHD-R and N-ADHD groups. It was also hypothesized that ADHD-R individuals would present better functioning in different areas than ADHD-P, although they would display some deficiencies compared to the N-ADHD group.As expected, our results indicated that the ADHD-P group, in comparison with the N-ADHD group, showed differences on all the executive functions measured by self-reported EF ratings: inhibition, shift, working memory, and plan/organize, coinciding with findings from another previous study17]. By contrast, the ADHD-R group only obtained significantly worse EF mean scores than the N-ADHD group on the plan/organize scale, which evaluates aspects related to self-organization and planning ahead for future activities. The presence of these kinds of deficits highlights the stability that characterizes general problems in individuals with a childhood diagnosis of ADHD related to work organization, prioritizing activities, or planning activities. There were no significant differences between ADHD-P and ADHD-R on inhibition, shift, or plan/organize, although when comparing the two ADHD groups, a worse level was found on these functions in the ADHD-P group.Another important point has to do with the presence of the working memory problems in adults with ADHD, which is consistent with the image provided by a complete meta-analytic review of experimental studies . The worRegarding behaviors associated with ADHD, as expected, ADHD-P individuals, compared to N-ADHD individuals, also showed greater severity in the behaviors of inattention, hyperactivity, emotional lability, and self-concept problems. Moreover, impaired emotional regulation, which has been proposed as an essential component of ADHD , also shThere is evidence that ADHD is associated with lower self-esteem in adulthood , 20, butUndoubtedly, the differences in the comparisons of the three groups, ADHD-P, ADHD-R, and N-ADHD, are fairly evident in different functional impairments –23. In aIn the first structural equation model used to investigate how EF predicted total functional impairments, the effect of inhibition was positive and statistically significant, whereas shift and working memory only marginally predicted impairments in all groups. Plan/organize showed a moderation effect of group, affecting total impairment more in the ADHD-P group than in the ADHD-R group; this effect was not statistically significant in the N-ADHD group. Therefore, as in other adult follow-up studies, EF ratings were good predictors of impairments in major life activities , 25. HowIn the second model examining functional impairment with associated ADHD behaviors, hyperactivity/restlessness and self-concept had equal effects across the three groups, ADHD-P, ADHD-R, and N-ADHD. In addition, the effect of hyperactivity was not statistically significant, whereas the effect of self-concept was positive and statistically significant. More importantly, inattention and impulsivity/emotional lability showed group-specific effects on total functional impairment. On the one hand, total functional impairments in ADHD-P individuals were more influenced by attention problems than in the N-ADHD group, whereas this effect was not statistically significant in the ADHD-R group. On the other hand, the effects of impulsivity/emotional lability were much larger in the ADHD-R group than in the other two groups, which did not significantly differ in these effects.Our study was uniquely suited to investigate the profile and functional impairments that characterize the persistence and remission of adult ADHD. The findings show that significant executive and behavioral impairments and, above all, adverse functional outcomes in family, school, life skills, social activities, and risky activities are related to the diagnostic persistence of ADHD. Recovery from the disorder is associated with better results on the EF, which are even more evident in the problems typically associated with ADHD. However, some deficits, such as plan/organize strategies, working memory and hyperactivity/restlessness, continue to be present in ADHD-R individuals, even though they no longer meet the criteria for the ADHD diagnosis. Thus, although the core ADHD symptoms may be in remission, other deficits that were not analyzed in sufficient depth in this study may negatively impact important outcomes Moreover, the results showed that some specific executive deficits and ADHD associated behavior problems contributed to the functional impairments in ADHD-R and ADHD-P. Thus, there was a higher group effect on plan/organize errors in the ADHD-P group than in the ADHD-R group, whereas the effect of the problems with impulsivity/emotional lability when examining functional impairments was greater in the ADHD-P group than in the ADHD-R group. In sum, the EF impairments in adult individuals with a diagnosis of ADHD in childhood are significant due to their presence in the persistence of the disorder, which is associated with functional impairments in domains of major life activities. Therefore, these processes are relevant from a practical point of view. Although they lack specificity and cannot strictly be considered diagnostic criteria for ADHD, behaviors reflecting executive problems in daily life activities must be taken into account by clinicians in the evaluation process to monitor adults who show weaknesses on these markers.This study presents some main limitations related to the characteristics of the sample and the evaluation procedure. The small sample size increases the probability of Type II errors, so that some null findings could be related to a lack of statistical power. Moreover, the sample was composed only of cases diagnosed with ADHD-C in childhood that were followed up until the young adulthood stage. Most of the participants were males with ages from 18 to 24 years old. For these reasons, the findings cannot be generalized to other presentations of ADHD, older adults, or females. Furthermore, in the identification of the ADHD-P group, the presence of impairment was not taken into account. According to a recent systematic review, impairment should be considered a factor when rigorously determining the persistence of ADHD . LikewisThis study provides evidence that persistence of ADHD in young adulthood is associated with severe executive, behavioral, and functional impairments in family, social, academic, and risky activities. The remission of ADHD manifested more subtle problems that were linked specifically to attention and hyperactivity/impulsivity behaviors. Structural equation models indicated that global functional impairment was predicted in the ADHD-P group by plan/organize and attentional problems. Finally, the impulsivity/emotional lability was found to be a very important predictive factor of global functional impairment in the ADHD-R group.In sum, the findings show that problems of adults with an ADHD childhood diagnosis do not usually disappear, and they encourage close collaboration between children’s and adults’ mental health services in performing the necessary follow-ups of this chronic disorder.


We recently reported increased mind wandering (MW) frequency in adults with attention-deficit/hyperactivity disorder (ADHD) relative to controls during high demands on sustained attention, reflecting deficient context regulation of MW. Studies on community samples previously linked context regulation of MW with attenuation in brain sensory processes, reflecting perceptual decoupling, and attentional processes during MW compared to task focus. However, the association between deficient context regulation of MW and these neural processes has not been studied in ADHD. We addressed this question by comparing adults with ADHD (N = 23) and controls (N = 25) on event-related potentials of early sensory processes (P1) and attention allocation (P3) during tasks manipulating cognitive demands (high vs low) on working memory and sustained attention, and during periods of MW and task focus measured through experience-sampling. Compared to controls, adults with ADHD showed reduced P1 during high sustained attention demands, as well as reduced P3 during high working memory demands. These group differences were no longer significant after adding MW frequency as a covariate. Across tasks, adults with ADHD showed no differences from controls on the P1 during MW episodes, but attenuated P1 during task focus. P3 was reduced in adults with ADHD compared to controls during MW, but not during task focus during the sustained attention task. These findings converge to indicate that impairments in early sensory processing in individuals with ADHD seem parallel to increased MW frequency and might reflect inefficient adjustments from periods of MW to task focus. Context regulation is the term used to describe a decrease in MW frequency as task demands increase to preserve task performance ; indicatNumerous previous studies have shown deficient context regulation of neural activity in ADHD compared to controls . We therAnother feature of MW is perceptual decoupling . This reThe role of early sensory processing and perceptual decoupling remain poorly understood in ADHD, as only a few studies have examined P1 components in ADHD samples. Available studies have reported attenuated P1 in individuals with ADHD compared to controls , but somAnother ERP component relevant to context regulation is the P3, which arises 250–300 ms after stimulus presentation and broadly reflects attention allocation  . P3 atteTaken together, the studies highlight reductions in both P1 and P3 during MW episodes in community samples, and during cognitive tasks in ADHD samples, but these neural processes have yet to be studied in the context of MW in ADHD. This study aimed to address this gap in the literature by investigating the association between context regulation of MW and ERPs of early sensory processing (P1) and attention allocation (P3) in adults with and without ADHD through two complementary analyses. Firstly, we examined differences between groups on P1 and P3, as well as within-group modulations of these ERPs with changing task demands, and whether these effects were explained by MW frequency . We predicted that P1 and P3 in individuals with ADHD would be reduced compared to controls across tasks. With regard to within-group effects, we predicted a within-group decrease in P1/P3 from high to low demands on working memory (1-back vs 0-back) and with longer delays between visual stimuli  in the ADHD group, but comparable ERPs across task conditions in controls. We also expected a within-group increase in sensory processing (P1) during the shortest and most frequent delays (1 s) in controls, but not in individuals with ADHD, as these delays place high demand on sensorimotor function . Based o2EEG analyses/data screening below for details), from an original sample of 27 adults with ADHD and 29 controls. Adults with ADHD were recruited from the South London and Maudsley NHS Trust and Barnet, Enfield and Haringey Mental Health Trust adult ADHD clinics and online advertisements via adult ADHD networks and primary care physicians. Age-matched controls with low levels of ADHD symptoms , and no prior diagnosis or treatment for any mental health condition were recruited via online recruitment advertisements from all over London. Participants in both groups were excluded if they reported a current or past diagnosis of major physical illness , severe recurrent mental health problems other than ADHD , current or past substance abuse , or an IQ < 80.Twenty-three participants with ADHD and 25 controls were included. This sample met quality control criteria for electroencephalography (EEG) data  condition measures general alertness and motor speed, whereas the 1-back condition measures visual working memory performance . In the The order of conditions was counterbalanced. For each trial, between 2 and 6 non-targets preceded the target. The non-targets lasted for 1 to 3 s with increasing steps of 0.1 s in each trial . The total number of stimuli was 128 targets (64 in each condition) and 580 non-targets (290 in each condition). Each target lasted for 4 s, allowing the participant 4 s to respond until their response ended it immediately. The fixation appeared before and after all task stimuli crosses ranged from 2 to 4 s with increasing steps of 0.1 s.There was a total of 8 trials in each block for each condition. There were 8 blocks, with a varying duration from 40 s to 120 s. At the end of each block, participants were informed that they were about to start a new block with either the same condition with the word “STAY” or that they were about to switch to the other condition with the word “SWITCH”. Both message words “SWITCH” and “STAY” appeared on the screen for 5 s. The total duration of task was approximately 30 min divided into two 15-min sessions.2.2.2The task is a modified version of the SAT . The SAT2.2.3Where was your attention just before this probe?” with two response options “On task” and “Off task”. If they had responded “Off task”, another question enquired “Were you aware of your attention drifting away from the task?” with two responses options “Aware” and “Unaware”. MW and task focus episodes were measured in the 15 s preceding each probe, consistent with previous work  at approximately 1-minute intervals. The probe appeared in the place of the targets in the MWT and in the place of the stimulus following the infrequent delays  in the SAT. We included 26 delays per session  contrasting 20 delays  in the original version of the SAT . Most ofous work .2.2.4Task performance measures and MW frequency during each task condition have been reported previously  and are 2.3The EEG was recorded from a 62-channel DC-coupled recording system (extended 10–20 montage) , using a 500 Hz sampling rate, impedances under 10 kΩ, and FCz as the recording reference. The electro-oculograms were recorded from electrodes above and below the left eye and at the outer canthi. The EEG data were analysed using EEGLAB . The raw2.4For Analysis 1, average ERPs were created separately for the working memory (1-back), choice reaction (0-back) and delay  conditions. The number of trials in each ERP by group are given in Supplementary Table S2. The trials in the 15 s preceding the MW/task focus probes were excluded from Analysis 1 to allow comparability with previous studies using these tasks that did not include thought probes, and because the 15 s period preceding probes was the focus of Analysis 2. For Analysis 2, ERPs were generated in trials included in the 15 s preceding the probe and split between task focus and MW (Supplementary Table S2).For both analyses, the data were segmented in epochs around the stimulus between −1000 and 1000 ms using the −200-ms pre-stimulus period for baseline correction. P1 and P3 were identified within the selected electrodes and latency windows for which effects were expected to be largest, based on previous ADHD and MW studies using attentional and working memory tasks . These p, additional participants were excluded due to not having sufficient trials for analyses contrasting MW and task focus periods. For the MWT, 4 additional controls had no MW episodes and 2 individuals with ADHD had no task focus episodes, resulting in 21 individuals with ADHD and 21 controls. For the SAT, 7 controls did not have enough MW episodes, resulting in 23 individuals with ADHD and 18 controls.Only participants with at least 20 artefact-free EEG segments in each condition or probe were included in the ERP analyses, since at least 20 artefact-free EEG segments are required to observe reliable neural effects and obtain valid ERP indices . For Ana2.5To study ERP components during task conditions , we tested the effects of condition , group (ADHD/controls) and condition-by-group interactions on each ERP in repeated measures general linear models. To test the effect of MW frequency on the ERP variables, we repeated these analyses adding MW frequency as a covariate. Controlling for the effect of MW in the model allowed us to directly assess whether group differences in ERPs and task performance could be attributed to the diagnosis of ADHD, or to the higher occurrence of MW frequency in the ADHD group. To understand the effect of MW and task focus on ERP components and task performance , we tested the effects of probe (MW/task focus), group (ADHD/Controls) and probe-by-group interactions on each ERP and performance measures in repeated measures general linear models. In both analyses, we ran post-hoc tests comparing groups in each condition/probe separately and comparing conditions in each group even in the absence of significant condition-by-group or probe-by-group interactions, which our sample may be underpowered to detect. In an additional analysis, due to a potential temporal relationship between P1 and P3, we entered P1 as a covariate in Analyses 1 and 2.In the MWT, we ran analyses across target and non-target trials, as there were large, positive correlations between the two stimulus types  and we expected that condition and MW would impact the ERPs in targets and non-target trials to a similar extent. Supplementary Analysis 2 and Supplementary Table S4 report analyses run in target and non-target trials for completeness, showing comparable results for both stimulus types.All ERP measures were normally distributed. Cohen’s d with correction for small sample sizes (n < 50) was computed for between-group and within-group comparisons . We usedGiven the novelty of the current study, formal a-priori power calculations indicate 80% power to detect medium effects sizes (d > 0.70) as statistically significant (α = 0.02) with the current sample (n = 48). The calculation refers to the statistical models used with and without covariates using the statistical software, G*Power .3All main and interaction effects are reported in 3.13.1.1P1 during the MWT  was atteDuring the SAT, individuals with ADHD had a significantly lower P1 amplitude in the 1 s, 5 s and 8 s delays compared to controls , but there were no group differences in the 2 s ; Table 33.1.2Individuals with ADHD had significantly smaller P3 in the 1-back condition compared to controls during the MWT , but there were no differences in the 0-back condition ; Table 3There were no group differences in P3 in any delay condition during the SAT , Table 33.23.2.1Both during the MWT and the SAT, individuals with ADHD had significantly smaller P1 compared to controls, which also survived FDR correction, during task focus, but not during MW episodes . Control3.2.2Individuals with ADHD showed smaller P3 compared to controls, although at trend level , in the MWT during both MW and task focus , Table 4During the SAT, individuals with ADHD had significantly smaller P3 than controls during MW episodes, but not during task focus  i.e., s. The gro3.2.3During the MWT, individuals with ADHD showed higher MRT during periods of both MW and task focus compared to controls, although this effect for MW periods did not survive FRD correction . RTV was4This is the first study to investigate modulations of neural activity of early sensory and attentional processes in relation to MW frequency, during varying task conditions, and periods of MW and task focus, in individuals with and without ADHD. Compared to controls, adults with ADHD showed attenuations in P1 during high demands on sustained attention, and attenuation in P3 during high demands on working memory. These group differences were explained by MW frequency, which was higher in adults with ADHD compared to controls. Individuals with ADHD also showed reduced P1 relative to controls during task focus, but not during MW episodes across tasks, and reduced P3 during MW, but not during task focus in the SAT. These findings show that differences between groups on modulations of early sensory processes are linked to modulations of MW frequency, whereas modulations in attention allocation appear task- and condition-dependent. Taken together, this study provides converging evidence that higher MW frequency and inefficient adjustment from MW episodes to task focus may contribute to deficient neural activity of sensory processing in individuals with ADHD compared to controls.Our first analysis sought to understand the relationship between MW frequency and sensory processing (P1) and attention allocation (P3) during varying task conditions in individuals with ADHD and controls . Results for P1 were largely consistent with our hypotheses. Across tasks, adults with ADHD compared to controls showed attenuated P1, although this effect survived multiple testing corrections only in the SAT, during conditions that we previously found associated with the highest level of MW frequency in the ADHD group  . RegardiWe also examined modulations of P1 and P3 within each group with changing task demands. In adults with and without ADHD, we found that neural activity  was higher during 1-back compared to the 0-back condition , consistent with previous findings on P1 . This fiOur second analysis further assessed the relationship of MW to neural activity  more directly by contrasting periods of MW and task focus . During both tasks, adults with and without ADHD showed comparably low P1 during MW, indicating perceptual decoupling. This result is in line with the findings of Analysis 1, showing that differences between ADHD and control groups on P1 are explained with MW frequency. Importantly, compared to controls, individuals with ADHD showed lower P1 than controls during task focus, suggesting that they remained in a state of perceptual decoupling during task focus. This key group difference suggests that poorer adaptation of sensory processing might be a primary deficit in individuals with ADHD. Individuals with ADHD further showed lower attention allocation (P3) than controls during both MW and task focus in the MWT, although at trend level. This trend-level pattern supports our interpretation of the findings contrasting task conditions  that the P3 is modulated by the cognitive demand evoked by the task condition and is unrelated to context regulation of MW. This finding suggests that individuals with ADHD, unlike controls, might have difficulty allocating additional attention during high working memory demands (1-back condition), which require continuous attention allocation to both non-targets  and targets . During the SAT, individuals with ADHD compared to controls had reduced attention allocation during MW, but not during task focus. These findings suggest that P3 reductions are malleable rather than fixed in individuals with ADHD and suggest that improvements might be possible with task manipulations that reduce MW frequency. In line with this pattern, it has been shown that P3 attenuations improve in individuals with ADHD under faster and rewarded conditions . After cWithin-group comparisons further showed an improvement in P1 from MW to task focus in controls across tasks, although at trend level in the MWT. Instead, individuals with ADHD did not show a difference in P1 between MW and task focus, indicating deficient context regulation of sensory processing. Together with the differences in P1 between groups, these findings in the ADHD group suggest a lack of neural adaption from conditions of low alertness, such as MW , to taskWith regard to task performance, our findings indicate that individuals with ADHD in the MWT showed comparable response variability (RTV) and error rate to controls during periods of task focus, but significantly worse performance during MW. This pattern in task performance appears parallel to context regulation of both neural activity  and MW frequency in both groups during the MWT. In contrast, compared to controls, individuals with ADHD had increased MRT during both task focus and MW during the MWT, although the latter effect was at trend level and requires replication. Compared to controls, individuals with ADHD also made more errors during MW, but not during task focus across tasks. This pattern further supports the detrimental impact of increased MW frequency on task accuracy in individuals with ADHD. During the SAT, individuals with ADHD performed worse  than controls during task focus, but not during MW. Both groups also showed similar reaction times during MW compared to task focus in the SAT, but not in the MWT, indicating that MW periods might be particularly impairing to performance during this task placing increasing demands on sustained attention. This finding supports the notion that MW reduces attentional resources at the cost of task performance  and conf5This study aimed to investigate the neural and cognitive mechanisms through which MW might play a role in ADHD symptoms and impairments. More specifically, the absence of improvement in basic, pre-attentive, perceptual processes  from episodes of MW to task focus might facilitate inattentive behaviours  interfering with daily function in adults with ADHD. Future work could therefore evaluate the impact of deficient early sensory processing and increased MW frequency on both experimental and everyday performance and suggest treatment strategies which target early perceptual processing in ADHD. For example, the use of stimulant medication has been linked to normalisation of neural activity from rest to task , suggest6d > 0.50 to d > 0.80). This likely explains why several interaction effects were non-significant and some post-hoc effects did not survive multiple testing corrections. Although MW frequency as a covariate might have driven some of the effects, the study may have been underpowered to detect small independent effects of MW and ADHD status. While our analysis did not directly test the mechanistic hypothesis, our findings provide convergent evidence for the association of MW with P1 in individuals with ADHD, and highlight the need for future research using causal modelling. Future research should confirm these findings in a larger sample and using tasks that generate greater variability in MW episodes, in order to detect subtle effects that could not be detected with the current study design. In addition, the MWT was relatively easy and future studies could examine the effect of higher demand on working memory  and lower demand on sustained attention  on the frequency of MW in individuals with and without ADHD. Another limitation is the lower number of artefact-free trials across conditions in individuals with ADHD compared to controls. Individuals with ADHD had a significantly lower number of trials across all conditions, but between and within-group effects emerged only for P3 in the 1-back, and for P1 in the 1 s, 5 s and 8 s, suggesting that the number of trials might not have impacted our results (Supplementary Table S2). Future work should aim to equate the number of trials across groups to avoid signal to noise ratio (SNR) effects, for example by using tasks with a greater number of trials. Future work may also benefit from using measures sensitive to the changes associated with the onset of MW and its progression during the task, such as pupil diameter  in response to task demands appear to parallel modulations in MW frequency . HoweverThe authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Professor Jonna Kuntsi has given talks at educational events sponsored by Medice: all funds are received by King’s College London and used for studies of ADHD. Professor Philip Asherson has received honoraria for consultancy to Shire/Takeda, Flynn-Pharma, Eli-Lilly, Janssen, Novartis, Lundbeck and Medice; educational/research awards from Janssen, Shire, Lilly, Novartis, Flynn Pharma, Vifor Pharma, GW Pharma and QbTech; speaker at sponsored events for Shire/Takeda, Lilly, Novartis, Medice, Janssen-Cilag and Flynn Pharma.Professor Katya Rubia has received a grant from Shire/Takeda for another project.