ASD with ADHD vs. ASD and ADHD alone: a study of the QbTest performance and single-dose methylphenidate responding in children and adolescents

FIGURE 1. Changes in cortical thickness provide one measure of brain maturation. A large longitudinal study found that for most areas of cortex, children with attention deficit hyperactivity disorder (ADHD) reach peak cortical thickness several years later than typically developing children, supporting presence of developmental delay. The rate of cortical thinning also differed between the group who continued to meet diagnostic criteria into adulthood (persistent ADHD) and those who did not (remitted ADHD). Areas of cortex in which the rate of thinning correlated with adult symptom level (green, more symptoms associated with more thinning) are approximated on medial and lateral simplified representations of cortex. An earlier study also identified multiple areas in which cortex was thinner in adults with persistent ADHD compared with controls (orange). In addition, this study noted some areas of thicker cortex in remitted ADHD when compared with persistent ADHD (blue).

Introduction Substantial overlap exists between autism spectrum disorder and attention deficit hyperactivity disorder at multiple levels. Aetiologically, similarity exists in genetic liability for the two disorders. Phenotypically, comorbidity exists between autism spectrum disorder and symptoms of attention deficit hyperactivity disorder with rates varying between 28% and 92% and both groups have similar problems with social cognition. The aim of this study was to discuss behaviour profiles of children with attention deficit hyperactivity disorder and autism spectrum disorder on the parent PDD Behaviour Inventory. Materials and methods Parent ratings of children with autism spectrum disorder (with and without attention deficit hyperactivity disorder behaviours) were compared with parent ratings of children with attention deficit hyperactivity disorder behaviours who did not have autism spectrum disorder (the attention deficit hyperactivity disorder group) using the PDD Behaviour Inventory, a rating instrument that is agestandardised on children with autism spectrum disorder and which assesses both maladaptive behaviours and adaptive skills. Results The attention deficit hyperactivity disorder group’s maladaptive behaviours were rated as more severe than the autism spectrum disorder group, especially on those domains assessing fears and aggression. Further, the attention deficit hyperactivity disorder group was rated as having greater severity of fears and aggression when compared with those in the autism spectrum disorder group who also had comorbid attention deficit hyperactivity disorder behaviours. By contrast, the attention deficit hyperactivity disorder group was rated as having better expressive language ability than the autism spectrum disorder group (especially when compared with those in the autism spectrum disorder group with comorbid attention deficit hyperactivity disorder behaviours). It is hypothesised that the increased severity of fears and aggression in the attention deficit hyperactivity disorder group may reflect their relatively increased ability to communicate these problems to others. Conclusion These data extend findings from previous studies and suggest that a unique attention deficit hyperactivity disorder profile may exist for children with attention deficit hyperactivity disorder on the PDD Behaviour Inventory.

Children with autism spectrum disorder (ASD) and those with attention deficit/hyperactivity disorder (ADHD) always show working memory deficits. However, research findings on the factors that affected the working memory in ASD and ADHD were inconsistent. Thus, we developed the present study to investigate the association of executive function (EF) with the visuospatial working memory (VSWM) in ASD and ADHD. Three groups of participants were examined: 21 children with ASD, 28 children with ADHD and 28 typically developing (TD) children as the controls. All participants completed two tests: the Wisconsin Card Sorting Test (WCST) and the Corsi Block Tapping Test for measuring EF and VSWM, respectively. The WCST included four domains: categories achieved (CA), perseverative errors (PE), failures to maintain set (FMS), and total errors (TE). The findings indicated that (1) the ASD group showed poorer performance in VSWM than the ADHD and TD groups; (2) for the ASD group, VSWM was positively correlated with CA, and was negatively correlated with PE and TE; (3) for the ADHD group, FMS showed a negative relationship with VSWM; and (4) TE predicted the performance of VSWM in ASD group, while FMS predicted VSWM in ADHD group. The study results suggested that VSWM was impaired in ASD but not in ADHD. Also, the EF domains were differently correlated with the VSWM performance in ASD and ADHD. Our study suggests that we should consider different intervention targets of working memory and EF contributions in improving the cognitive capacity of ASD and ADHD. Autism Res 2018, 11: 1148-1156. © 2018 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: The present study compared the visuospatial working memory (VSWM) in three groups of children: autism (ASD), attention deficit/hyperactivity disorder (ADHD), and typically developed children (TD). The ASD group showed poorer VSWM than the ADHD and TD groups. The total error of executive function predicted the performance of VSWM in ASD, while failures to maintain set predicted VSWM in ADHD . These findings suggested that we should consider the different working memory and executive function training targets to increase cognitive capacity of ASD and ADHD.

Objective:Autism Spectrum Disorders (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) are neurodevelopmental disorders with overlapping symptomatology and shared genetic makeup. Numerous previous studies have investigated ASD and ADHD using resting state functional networks. One functional network of particular interest is the Default Mode Network (DMN), as it has been shown to be abnormal in several mental disorders. Previous studies have investigated the DMN in ASD and ADHD separately but reported mixed trends of increased and decreased functional connectivity (FC) in the DMN in ASD and increased FC in ADHD. Additionally, little studies have investigated executive and attentional network dysfunction in the DMN for ASD and ADHD populations. To better understand the shared characteristics between ASD and ADHD, this study analyzed the DMN FC in children with ASD and ADHD.Participants and Methods:Archival datasets from Autism Brain Imaging Data Exchange (ABIDE)-I and ADHD-200 datasets were used, with 33 ADHD, 35 ASD, and 32 typically developing (TD) males (ages = 7-17 years). After applying a standard pre-processing pipeline, 11 regions of interest (ROIs) from the Dosenbach-160 atlas were examined with 55 ROI pairs generated for the 100 subjects.Results:Significant differences were noted between ASD-ADHD groups in attentional networks and executive functioning networks. Specifically, significant Group x VIQ interactions were noted for FC between the following pairs of regions: medial prefrontal cortex - ventromedial prefrontal cortex, anterior cingulate cortex -ventromedial prefrontal cortex, inferior temporal lobe - ventromedial prefrontal cortex, angular -ventromedial prefrontal cortex, angular -anterior cingulate cortex, inferior temporal lobe -ventrolateral prefrontal cortex, angular -superior frontal lobe, and intraparietal sulcus -superior frontal lobe. In the above FC pairs, FC in ADHD was negatively correlated with VIQ, with no correlation for ASD and positive correlation for TD. Previous literature has indicated that ADHD individuals demonstrate increased executive functioning deficits compared to ASD individuals. This study provides evidence at a neural level for these findings by demonstrating decreased FC trends in ADHD in attentional and executive functioning networks compared to ASD individuals. Group and VIQ main effects demonstrated mixed patterns across the three groups, as well as shared decreased FC in attention/executive networks for both ASD and ADHD groups.Conclusions:In summary, this study found similar findings from previous studies regarding mixed connectivity patterns, as well as shared dysfunction between ASD and ADHD groups. These results help in solidifying the theory that ASD and ADHD share clinical and neural patterns which need to be examined further. Future directions include utilizing more ASD+ADHD comorbid individuals in studies comparing ASD and ADHD FC trends as well as seeking to further understand the neuropsychological and neuroimaging profiles in ASD and ADHD.

BackgroundBoth autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are early neurodevelopmental disorders that present notable diagnostic problems and share clinical features. The current research intends to clarify the sensory profile, visual-evoked potential (VEP), and auditory-evoked potential of children diagnosed with autism spectrum disorder (ASD), ADHD, and typically developing children (TD). We have observed sensory processing problems in 42–88% of children diagnosed with autism and approximately 50% of children diagnosed with ADHD.ResultsThe parents of 37 children diagnosed with ASD, 41 children diagnosed with ADHD, and 43 children who were typically developing completed the short sensory profile (SSP) along with standardized questionnaires used to assess the symptoms and autistic behaviors. We assessed intellectual functioning and evoked potential in all the groups. There were more sensory problems in the ASD and ADHD groups than in the control group (P < 0.001); however, autism and ADHD differed in all subscales except unresponsiveness, auditory filtering, and visual/auditory subscales. Also, the ASD group and ADHD group showed a more significant delay in visual-evoked potential VEP than the control group (mean and SD of right eye p100 latency 150.85 ± 48.70 in ASD vs 119.28 ± 18.06 in ADHD vs 103.42 ± 5.19 in typically developing group, left p100 latency 141.09 in ASD ± 32.55 vs 116.51 ± 10.1 in ADHD vs 103.0 ± 5.91 typically developing group). Additionally, the ASD group significantly deviated from norms in the absolute latency of waves I, III, and V, as well as the inter-wave intervals of I–III and III–V in the auditory-evoked potential. Furthermore, there was a statistically significant distinction between the ADHD and the TD groups in terms of left wave III and V latency and left interpeak latency between I–III and III–V.ConclusionChildren diagnosed with ASD and ADHD have a greater likelihood than typically developing children to experience sensory processing abnormalities; as a result, we recommend basic assessment, follow-up, and designing the most appropriate intervention.

ABSTRACTChildren and adolescents with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) often present physical and motor challenges that may compromise health, yet direct comparisons between these neurodevelopmental conditions and typically developing (TD) peers remain limited. This study aimed to examine the physical fitness profiles of these three groups. A total of 1537 school‐aged participants were recruited from mainstream educational settings. The assessment included selected tests from the EUROFIT battery and body mass index (BMI). Composite indices of physical fitness and motor coordination were computed using age‐ and sex‐adjusted Z‐scores. Both the ADHD (n = 80) and ASD (n = 36) groups showed significantly lower cardiorespiratory fitness, balance, and upper‐body coordination compared with TD peers (n = 1413). Lower‐body muscular strength was reduced only in the ASD group, which also performed worse than the ADHD group. Flexibility and BMI distributions did not differ significantly across groups. Plate Tapping and Flamingo Balance test indices were markedly lower in both clinical groups relative to TD peers. Children and adolescents with ADHD and ASD had lower physical fitness than TD peers. Direct comparisons between ADHD and ASD revealed generally similar profiles, except for lower muscular strength in ASD. These findings highlight the need for early screening and tailored interventions to support healthier developmental trajectories and enhance functional outcomes in neurodevelopmental populations.

Autism-spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are early neurodevelopmental conditions that share clinical characteristics, raising important issues in clinical diagnosis. We aimed to compare (1) sensory processing in four groups of children: ASD alone, ASD + ADHD, ADHD alone, and typical development (TD) and (2) the association between sensory processing and attention in the three groups with neurodevelopmental disorders. Our sample included 120 children aged from 6 to 12years divided into four groups: ASD alone (N = 43), ASD + ADHD (N = 18), ADHD alone (N = 28), and TD (N = 31). Atypical sensory processing was more frequent in ASD and/or ADHD than in TD, without a significant difference between ASD and ADHD. However, the variance analysis of attention problems revealed differences between the ADHD and ASD groups. Thus, the rate of atypical sensory processing was comparable between the ASD and ADHD groups, suggesting that further studies are needed to explore atypical SP in all neurodevelopmental disorders.

Children with attention deficit/hyperactivity disorder (ADHD) combined with autism spectrum disorder (ASD) symptoms (ADHD + ASD) have poorer social and emotional functioning than those with ADHD alone. However, no studies have specifically examined the associations between ASD symptoms, measures of social and emotional functioning and limbic system white matter microstructure. Tractography on the cingulum, uncinate fasciculus and fornix were performed for 151 children with (N = 78) and without (N = 73) ADHD. Participants in the ADHD group who scored 11 or above on the Social Communication Questionnaire were classified as the ADHD + ASD group (N = 16). Significant differences in mean cingulum FA were present between the control group and the ADHD (all) group, however, no significant differences were seen between the ADHD and ADHD + ASD groups. Despite this, significant associations were seen between mean FA of the left cingulum and emotional problems for the ADHD + ASD group. Results give greater insights into the specific biological basis of emotional problems in the ADHD + ASD group, indicating that the cingulum may play a role.

Attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) have been related to an increased risk for behavioral addictions including online gaming. However, the relationship between these two conditions and Internet gaming disorder (IGD) is still debated. The aim of this study is to address this topic by exploring the prevalence of IGD in a consecutive sample of ASD youth and ADHD youth, compared with a normal control group, and by assessing selected psychopathological and neuropsychological features in ASD and ADHD patients with and without IGD. This study included 77 ASD patients (67 males, mean age 13.58 ± 2.75 years), 94 ADHD patients (79 males, mean age 11.46 ± 2.47 years), and 147 normal controls (NC) (mean age 13.9 ± 3.0 years, 114 males) that received structured measures for IGD (IAT, IGDS9-SF, and UADI). In the ADHD group, 72.34% of the sample were above the IGD cut-off, compared with 45.45% in the ASD group and 9.5% in the NC group. ASD patients with IGD presented with greater severity and more severe attention problems, with no difference in the ASD core symptoms between patients with and without IGD. In the comparison between the ASD and ADHD groups according to the presence of IGD, ASD patients with IGD were the most severe group according to the CGI (Clinical Global Impression) scale. The follow-up, conducted on 45 patients affected by ASD, showed an improvement in CGI and CGAS (Children's Global Assessment Scale) scores, but not in the IGD symptoms. These findings could place the diagnosis of ASD as a negative prognostic factor in the follow-up of aspects of video game addiction compared with ADHD.

Background Attention-Deficit/Hyperactivity Disorder (ADHD) is the most common neurodevelopmental disorder in children (Polanczyk, Willcutt, Salum, Kieling, &amp; Rohde, 2014) and is highly comorbid with Autism Spectrum Disorder (ASD) (Green et al., 2015; Kotte et al., 2013). Although it is well established that children with ADHD or ASD and their families experience poorer functioning including child and parent mental health problems, child peer problems, poorer family quality of life (FQoL) and parenting difficulties, it is unknown how comorbid ASD symptoms contribute to child and family functioning in children with ADHD. It is important to understand which comorbidities contribute to poorer child and family functioning to guide treatment planning. Aims This study aimed to examine the prevalence of ASD symptoms in children with ADHD and the association between ASD symptoms and child and family functioning across three connected studies. The specific aims of each study are outlined below. Study 1. To examine the prevalence and type of ASD symptoms (social interaction, communication and stereotyped behaviour) in children with ADHD and non-ADHD controls. Within the ADHD group only, we also examined the relationship between ADHD subtype, hyperactive/impulsive and inattentive symptoms, ADHD symptom severity and child gender and ASD symptom severity. Study 2. To examine the association between ASD symptoms and (a) social functioning; (b) mental health; (c) quality of life and (d) sleep, in children with and without ADHD. Study 3. To examine the association between ASD symptoms (measured dimensionally) in children with and without ADHD and a broad range of family functioning variables and to examine differences between ADHD+ASD, ADHD and control groups on family functioning variables. Methods Participants were 6-10 year old children (164 ADHD; 198 non-ADHD control) attending 43 schools in Melbourne, Australia, who were participating in the Children’s Attention Project. ADHD was assessed in two stages using the parent and teacher Conners’ 3 ADHD index and the Diagnostic Interview Schedule for Children IV (DISC-IV). ASD symptoms were identified using the Social Communication Questionnaire (SCQ). Child functioning measures were social functioning (Strengths and Difficulties Questionnaire (SDQ), mental health (DISC-IV, SDQ), quality of life (QoL: Pediatric Quality of Life Inventory 4.0) and sleep problem severity. Family functioning outcome variables were parent mental health, family quality of life (FQoL), and scales assessing couple conflict, couple support and parenting behaviours. Unadjusted and adjusted linear and logistic regression examined continuous and categorical outcomes, respectively. Results Study 1. Children with ADHD had more ASD symptoms than non-ADHD controls (adjusted mean difference = 4.0, 95% confidence interval (CI) 2.8; 5.3, p &lt; 0.001, effect size = 0.7). Boys with ADHD had greater ASD symptom severity than girls with ADHD (adjusted mean difference = 2.9, 95% CI 0.8; 5.2, p = 0.01, effect size = 0.4). Greater ADHD symptom severity was associated with greater ASD symptom severity (regression co-efficient = 1.6, 95% CI 1.2; 2.0, p &lt; 0.001). No differences were observed by ADHD subtype. Greater hyperactive/impulsive symptoms were associated with greater ASD symptoms (regression coefficient = 1.0; 95% CI 0.0; 2.0, p = 0.04) however, this finding attenuated in adjusted analyses, which accounted for parent educational attainment, socioeconomic status, child internalising and externalising comorbidities (p = 0.45). Study 2. Each standard deviation (SD) increase in SCQ scores was associated with a 6.7 unit reduction in QoL (p &lt; 0.001) and greater parent and teacher-reported peer problems, emotional and conduct problems. For every SD increase in SCQ scores, internalising (OR = 1.8, 95% CI 1.3, 2.6, p = 0.001) and externalising disorders (OR = 1.5, 95% CI 1.1, 2.1, p = 0.02) increased, as did moderate/severe sleep problems (OR = 1.5, 95% CI 1.0, 2.2, p = 0.04). Most findings held in analyses adjusting for socio-demographic factors, ADHD symptom severity, and comorbidities (when not the outcome), with the exception of externalising disorders and sleep problems. Study 3. In unadjusted dimensional analyses, higher ASD symptoms were associated with more couple conflict (p = 0.04) and poorer FQoL for all subscales (p ≤ 0.001), with non-significant trends for less couple support (R2 = 0.10, p = 0.06), more hostile parenting (R2 = 0.02, p = 0.06) and poorer parent mental health (R2 = 0.02, p = 0.07). In adjusted dimensional analyses, higher ASD symptoms were only associated with poorer FQoL, across all subscales only (p ≤ 0.01). The trend association between ASD symptoms and parent mental health attenuated due to meaningful associations with comorbid internalising disorder (p = 0.003) and ADHD symptom severity (p = 0.05). The trend association between ASD symptoms and hostile parenting attenuated due to significant associations with comorbid externalising disorders (p = 0.002), lower parent education attainment (p = 0.03) and greater ADHD symptom severity (p = 0.04). Less couple support attenuated due to a significant association with socioeconomic status (p = 0.004). In unadjusted categorical analyses, parents of children with ADHD+ASD reported more couple conflict (p = 0.04), less couple support (p = 0.001), poorer FQoL (p &lt;0.001) and a non-significant trend for greater mental health difficulties (p = 0.07), compared to the ADHD group. In adjusted categorical analyses, parents of children with ADHD+ASD had poorer parent self-efficacy (p = 0.02), poorer FQoL (p &lt; 0.05) (p &lt; 0.05) and a non-significant trend for less couple support (p = 0.06), compared to parents of children with ADHD. In unadjusted categorical analyses, family functioning was significantly poorer for the ADHD and ADHD+ASD groups, compared to controls for most outcomes (p &lt;0.001). In adjusted categorical analyses, all findings attenuated except FQoL was significantly poorer for the ADHD and ADHD+ASD groups, compared to controls. Conclusion ASD symptoms are common, and associated with poorer functioning in children with ADHD. It is important for clinicians working with children with ADHD to identify and manage ASD symptoms, given that they exacerbate functional impairments in this already vulnerable group. The relationship between ASD symptoms and broader family functioning appears to be largely driven by internalising and externalising disorders, ADHD severity, and socioeconomic status. Poorer FQoL appears to be independently associated with ASD symptoms in children with ADHD.

This study assessed the co-occurrence of attention deficit hyperactivity disorder (ADHD) and autism spectrum disorder (ASD) in newly diagnosed adults of normal intelligence and the contribution of trait-based dimensions deriving from the Barkley Adult ADHD Rating Scale-IV (BAARS-IV), the Autism-Spectrum Quotient (AQ), and the Empathy Quotient (EQ) to the differentiation of patients with ADHD, ASD, and ADHD/ASD. A total of 16.1% of patients with ADHD received a co-occurring ASD diagnosis, while 33.3% of patients with ASD received an ADHD diagnosis. Subjects with ADHD or ADHD/ASD had higher scores in all ADHD traits compared to ASD subjects. Compared to the ADHD group, the ASD group had AQ scores that were significantly greater, except for attention to detail. ADHD/ASD co-occurrence significantly increased the score of attention to detail. The total EQ score was greater in the ADHD group. In the stepwise logistic regression analyses, past hyperactivity, current inattention and impulsivity, attention switching, communication, imagination, and total EQ score discriminated ADHD patients from ASD patients. Attention to detail, imagination, and total EQ score discriminated ADHD cases from ADHD/ASD cases, while past hyperactivity and current impulsivity discriminated ASD subjects from ADHD/ASD subjects. Our findings highlight the importance of particular trait-based dimensions when discriminating adults with ADHD, ASD, and co-occurring ADHD/ASD.

BackgroundCo-occurring psychiatric disorders in adults with Attention Deficit Hyperactivity Disorder (ADHD) and/or Autism Spectrum Disorder (ASD) contribute to the burden of the healthcare and possibly to the delay of diagnosis. Aim of the study was to clinically assess the prevalence and compare lifetime co-occurring psychopathology in a sample of newly diagnosed ADHD and/or ASD adults and discuss the diagnostic challenges they pose.MethodsThe lifetime prevalence rates of ten of the most frequently co-occurring psychiatric diagnoses was registered in 336 adults of normal intelligence who underwent a thorough clinical evaluation for the diagnosis of ADHD and/or ASD for the first time in their lives. Four study groups were formed: the ADHD (n = 151), the ASD (n = 58), the ADHD+ASD (n = 28) and the nonADHD/nonASD (NN) (n = 88) group.ResultsAt least one co-occurring psychopathology was found in 72.8% of the ADHD group, in 50% of the ASD group, in 72.4% of the ADHD+ASD group and in 76.1% of the NN group (p = 0.004). In all groups the most frequent psychiatric disorder was depressive disorder. The only significant difference regarding the patterns of psychiatric co-occurrence between the ADHD and the nonADHD groups (ASD and NN groups) was found for SUD (p = 0.001). Also, the proportion of subjects with Bipolar Disorder was significantly greater in the NN group as compared to those with ASD (p = 0.025).ConclusionsOur results support the high prevalence of co-occurring psychiatric disorders in adults with ADHD and/or ASD with the ASD group presenting the lowest rate. The most marked difference between the ADHD and the nonADHD groups was found for SUD. Moreover, our findings highlight the need for a thorough clinical assessment of all referred patients both in the presence and absence of ADHD and/or ASD.

Background The study aimed to assess comorbidity of symptoms between autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) and explore the overlap between both disorders in Arabic-speaking children for further improvement of the intervention methods. Methodology The study included 33 children with delayed language development associated with ASD (group I) and 33 children with delayed language development associated with ADHD (group II). The age range of the subjects was 3–8 years. All children underwent comprehensive history taking, and diagnoses of ASD and ADHD were confirmed by using the criteria of the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5), Conners’ test, psychometric evaluation, and language assessment. Result 81.8% of the ASD group was accompanied by ADHD and 57.6% of the ADHD group was accompanied by ASD. The mean ± SD of the CARS test in the ASD group was 33.6 ± 4.2, while in the ADHD group it was 28.9 ± 5.9. The mean ± SD of Conners’ test in the ASD group was 69.9 ± 4.9 and was 66.9 ± 4.7 in the ADHD group. Conclusion A positive correlation was recorded between ADHD and ASD as regards their comorbidities. Both CARS and Conners’ tests demonstrated significant differences between both disorders, with higher scores in the ASD group.

Autism spectrum disorders (ASD) and attention deficit/hyperactivity disorder (ADHD) are very common developmental disorders which share some similar symptoms of social, emotional, and attentional deficits. This study is aimed to help understand the differences and similarities of these deficits using analysis of dense-array event-related potentials (ERP) during an illusory figure recognition task. Although ADHD and ASD seem very distinct, they have been shown to share some similarities in their symptoms. Our hypothesis was that children with ASD will show less pronounced differences in ERP responses to target and non-target stimuli as compared to typical children, and to a lesser extent, ADHD. Participants were children with ASD (N=16), ADHD (N=16), and controls (N=16). EEG was collected using a 128 channel EEG system. The task involved the recognition of a specific illusory shape, in this case a square or triangle, created by three or four inducer disks. There were no between group differences in reaction time (RT) to target stimuli, but both ASD and ADHD committed more errors, specifically the ASD group had statistically higher commission error rate than controls. Post-error RT in ASD group was exhibited in a post-error speeding rather than corrective RT slowing typical for the controls. The ASD group also demonstrated an attenuated error-related negativity (ERN) as compared to ADHD and controls. The fronto-central P200, N200, and P300 were enhanced and less differentiated in response to target and non-target figures in the ASD group. The same ERP components were marked by more prolonged latencies in the ADHD group as compared to both ASD and typical controls. The findings are interpreted according to the "minicolumnar" hypothesis proposing existence of neuropathological differences in ASD and ADHD, specifically minicolumnar number/width morphometry spectrum differences. In autism, a model of local hyperconnectivity and long-range hypoconnectivity explains many of the behavioral and cognitive deficits present in the condition, while the inverse arrangement of local hypoconnectivity and long-range hyperconnectivity in ADHD explains some deficits typical for this disorder. The current ERP study supports the proposed suggestion that some between group differences could be manifested in the frontal ERP indices of executive functions during performance on an illusory figure categorization task.

Autistic traits (ATs) are prevalent and clinically significant among children with Attention Deficit/Hyperactivity Disorder (ADHD); however, their specific behavioral correlates have not been fully characterized. This cross-sectional study investigated the presence of ATs and their relationship with behavioral profiles within this population. A total of 154 children were enrolled, including 48 healthy controls (HCs), 69 children with ADHD, and 37 children with comorbid ADHD and Autism spectrum disorder (ASD). The Autism Spectrum Screening Questionnaire (ASSQ) and the Child Behavior Checklist (CBCL-ASD), composed of Withdrawn, Thought Problems, and Social Problems subscales, were used to assess ASD symptoms and explore the structure of ATs. ATs were defined as a total score of ASSQ ≥ 12, leading to the subdivision of the ADHD group into ADHD without ATs (ADHD-ATs, n = 40) and ADHD with ATs (ADHD + ATs, n = 29). To characterize the non-ASD behavioral features associated with ATs, behavioral differences across HCs, ADHD-ATs, ADHD + ATs, and ADHD + ASD groups were compared using CBCL non-ASD scales. 1. ATs in ADHD: Compared to HCs, the ADHD group showed significantly higher scores on all ASSQ and CBCL-ASD measures except the ASSQ communication problems subscale (all P < 0.05). However, their scores were lower than those in the ADHD + ASD group (all P < 0.05). When further divided by ATs, the ADHD + ATs subgroup exhibited widespread ASD-related impairments. Their ASSQ scores and CBCL-ASD social problems scores exceeded those of both ADHD-ATs and HCs (all P < 0.05), and were comparable to the ADHD + ASD group. 2. Non-ASD Behaviors in ADHD + ATs subgroup: Apart from anxiety/depression, the ADHD + ATs group scored higher than both ADHD-ATs and HCs on all CBCL-non-ASD scales, and exceeded ADHD + ASD in aggressive behavior and rule-breaking (all P < 0.05). Multiple linear regression showed that aggressive behavior was predicted by social-interaction, withdrawn and thought problems scores; rule-breaking was predicted by communication problems scores, withdrawn and thought problems; attention problems was predicted by all CBCL-ASD scales; somatic complaints was predicted by social-interaction and thought problems. ATs may represent a clinically characterized subgroup within ADHD, characterized by global impairments across all core ASD symptom domains, alongside elevated non-ASD behavioral problems, particularly in externalizing behaviors. Notably, specific ASD symptom profiles differentially predict distinct patterns of non-ASD behaviors. Exploring the ATs subgroup can help elucidate the heterogeneity and complexity of ADHD, thereby contributing to precision treatment for the disorder. Not applicable.