Data-driven identification of subtypes of executive function across typical development, attention deficit hyperactivity disorder, and autism spectrum disorders

Does executive function moderate the spatial-math link in preschoolers?

In the present study, we examine if the spatial-math link is moderated by executive function in preschoolers, with a particular interest in which aspects of executive function may serve as moderators for this relation. We collected data from a sample of 242 preschoolers from the Midwest United States. Individual moderation analyses were run for each of the five executive function measures to assess whether various executive functions moderate the spatial-math link. We found that only planning (β = .13, p = .017) significantly moderated the association between spatial assembly and numeracy skills. Specifically, these results indicated that the association between spatial and math skills was stronger when children also had stronger planning skills. The findings from this study provide preliminary evidence that one aspect of executive function (planning) strengthens the spatial-math link. Implications for future research are discussed.

Attention and executive delays in early childhood: a meta-analysis of neurodevelopmental conditions

The objective of this review was to evaluate attention and executive function performance in children with neurodevelopmental conditions across the first 5 years of life, compared to neurotypical peers. MEDLINE, EMBASE, and PsycINFO databases were searched until June 30, 2023, and studies comparing attention or executive function between children with (or at risk for) neurodevelopmental conditions and neurotypical (or low risk) peers, 0 to 5 years old, were included. Of the 4338 studies identified, 111 studies with 12292 participants were included in the meta-analysis. The qualitative analysis of brain development included 5 studies. Primary outcomes were the standardised mean difference (Hedges' g) in attention and executive function between groups. Meta-regressions examined moderating effects of age, biological sex, diagnosis, and measure type. Children with neurodevelopmental conditions showed small delays in attention (n = 49 studies, k = 251 outcomes, g = 0.36, 95% CI 0.23-0.48, p < 0.001) and moderate delays in executive function (n = 64 studies, k = 368 outcomes, g = 0.64,95% CI 0.53-0.76, p < 0.001). Attention and executive function delays could not be identified in the first year (equivalence tests, p < 0.001), small to moderate delays were found in toddlerhood and moderate delays by preschool. Delays identified were largely transdiagnostic, although there was some evidence of diagnosis-specific delays for attention and moderation by measure type (informant rating vs performance-based vs physiological). Qualitative analysis described how delays were underpinned by a divergence of brain development in medial prefrontal regions. These findings highlight the potential of using attention and executive measures to detect delay and to intervene in neurodevelopmental conditions early in life.

The canonical correlation between executive function and social skills in children with autism spectrum disorder and potential pathways to physical fitness

Research on the relationship between core and comorbid features in children with Autism Spectrum Disorder (ASD), particularly executive function, remains limited. Additionally, the role of physical fitness in supporting ASD children's growth and development appears critical. This study investigates the relationship between executive function, social skills, and physical health in children with ASD. A total of 428 male participants were enrolled, including 117 diagnosed with ASD (mean age: 10.25 ± 1.481 years) and 311 with typical development (mean age: 9.56 ± 1.261 years). The results showed that children with ASD had significantly lower executive function and social interaction abilities than those with typical development (P < 0.05). A strong correlation was found between executive function and social skills (first canonical correlation coefficient: 0.641, P < 0.001), with 20.4% of the variation in social abilities explained by executive function. Specifically, emotional control, working memory, social perception, social cognition, and autistic behaviors influenced ASD children's development. While balance did not correlate significantly with physical fitness (P > 0.05), muscle strength showed a stronger effect (r = -0.485 to -0.535, P < 0.05). Improving physical fitness may help alleviate deficits in executive function and social skills. These findings provide early insights into the relationship between executive function and social skills in ASD, emphasizing the potential role of physical activity.

Multidimensional ADHD Symptom Profiles: Associations with Adverse Childhood Experiences

OBJECTIVE

Adverse childhood experiences (ACEs) are associated with a range of negative health outcomes, including attention-deficit/hyperactivity disorder (ADHD) and neurocognitive deficits. This study identified symptom profiles in adult patients undergoing neuropsychological evaluations for ADHD and examined the association between these profiles and ACEs.

METHODS

Utilizing unsupervised machine learning models, the study analyzed data from 208 adult patients.

RESULTS

The Gaussian Mixture Model revealed two distinct symptom profiles: "Severely Impaired" and "Moderately Impaired". The "Severely Impaired" profile, 23.6% of the sample, was characterized by more severe ADHD symptomatology in childhood and worse neurocognitive performance. The "Moderately Impaired" profile, 76.4% of the sample, had scores in the average range for self-reported internalizing and externalizing psychopathology and better neurocognitive performance. There was a greater number of ACEs reported by patients in the Severely Impaired profile than the Moderately Impaired profile (p = .022). Specifically, using an ACEs cutoff of ≥4, 53.1% of patients in the Severely Impaired profile reported four or more ACEs, compared with 34.6% in the Moderately Impaired profile (p = .020). Profiles were not related to clinician-ascribed diagnosis.

CONCLUSIONS

Findings underscore the association between ACEs and worse symptom profiles marked by impaired neurocognitive function, increased internalizing and externalizing psychopathology, and heightened perceived stress in adults with ADHD. Future research may explore the effect of ACEs on symptom profiles in diverse populations and potential moderators or mediators of these associations. Findings offers valuable insights for clinicians in their assessment and treatment planning.

Virtual reality-assisted prediction of adult ADHD based on eye tracking, EEG, actigraphy and behavioral indices: a machine learning analysis of independent training and test samples

Given the heterogeneous nature of attention-deficit/hyperactivity disorder (ADHD) and the absence of established biomarkers, accurate diagnosis and effective treatment remain a challenge in clinical practice. This study investigates the predictive utility of multimodal data, including eye tracking, EEG, actigraphy, and behavioral indices, in differentiating adults with ADHD from healthy individuals. Using a support vector machine model, we analyzed independent training (n = 50) and test (n = 36) samples from two clinically controlled studies. In both studies, participants performed an attention task (continuous performance task) in a virtual reality seminar room while encountering virtual distractions. Task performance, head movements, gaze behavior, EEG, and current self-reported inattention, hyperactivity, and impulsivity were simultaneously recorded and used for model training. Our final model based on the optimal number of features (maximal relevance minimal redundancy criterion) achieved a promising classification accuracy of 81% in the independent test set. Notably, the extracted EEG-based features had no significant contribution to this prediction and therefore were not included in the final model. Our results suggest the potential of applying ecologically valid virtual reality environments and integrating different data modalities for enhancing robustness of ADHD diagnosis.

Probing heterogeneity to identify individualized treatment approaches in autism: Specific clusters of executive function challenges link to distinct co-occurring mental health problems

LAY ABSTRACT

Many autistic people struggle with mental health problems like anxiety, depression, inattention, and aggression, which can be challenging to treat. Executive function challenges, which impact many autistic individuals, may serve as a risk factor for mental health problems or make treating mental health conditions more difficult. While some people respond well to medication or therapy, others do not. This study tried to understand if there are different subgroups of autistic young people who may have similar patterns of executive function strengths and challenges-like flexibility, planning, self-monitoring, and emotion regulation. Then, we investigated whether executive function subgroups were related to mental health problems in autistic youth. We found three different types of executive function subgroups in autistic youth, each with different patterns of mental health problems. This helps us identify specific profiles of executive function strengths and challenges that may be helpful with identifying personalized supports, services, and treatment strategies for mental health conditions.

Neuro connect: Integrating data-driven and BiGRU classification for enhanced autism prediction from fMRI data

Autism Spectrum Disorder (ASD) poses a significant challenge in early diagnosis and intervention due to its multifaceted clinical presentation and lack of objective biomarkers. This research presents a novel approach, termed Neuro Connect, which integrates data-driven techniques with Bidirectional Gated Recurrent Unit (BiGRU) classification to enhance the prediction of ASD using functional Magnetic Resonance Imaging (fMRI) data. This study uses both structural and functional neuroimaging data to investigate the complex brain underpinnings of autism spectrum disorder (ASD). They use an Auto-Encoder (AE) to efficiently reduce dimensionality while retaining critical information by learning and compressing important characteristics from high-dimensional data. We treat the feature-extracted data using a BiGRU model for the classification task of predicting ASD. They provide a new optimization strategy, the Horse Herd Algorithm (HHA), and show that it outperforms other established optimizers, such SGD and Adam, in order to improve classification accuracy. The model's performance is greatly enhanced by the HHA's novel optimization technique, which more precisely refines weight modifications made during training. The proposed ASD and EEG dataset accuracy value is 99.5%, and 99.3 compared to the existing method the proposed has a high accuracy value.

Longitudinal changes in executive function in autism spectrum disorder: A systematic review and meta-analyses

Individuals with an autism spectrum disorder (ASD) diagnosis show impairment in executive function (EF). However, findings are mixed regarding differences in the age effect on EF between autistic individuals and persons with typical development (TD). Questions remain regarding whether the age-related trajectories of EF in ASD are the same as or different from those in TD. To bridge this knowledge gap, we conducted a systematic review and meta-analyses of longitudinal studies that compared age-related changes in EF between ASD and TD groups (preregistration: osf.io/j5764). A literature search was conducted using PubMed, PsycINFO, and Web of Science on January 29, 2024. After screening by two independent reviewers, 14 longitudinal studies were included. Random-effects meta-analyses of studies involving a maximum total of 518 autistic and 3558 TD children and adolescents (mean baseline ages: 5.7-12.0 years) showed that ASD had significantly poorer EF than TD at both baseline and follow-up. However, there was no significant group difference in the age-related change in EF across domains, including working memory, inhibition, shifting, and planning. Robust Bayesian meta-analyses also provided substantial evidence in favor of the null hypothesis that ASD and TD groups showed similar changes over time for most EF processes. Limitations of the literature included the limited number of longitudinal studies and a narrow range of developmental stages and EF constructs analyzed across studies. Altogether, these findings suggest that autistic children and adolescents generally can improve in EF over time similarly to their neurotypical peers. This has important implications for parents and educators, encouraging appropriate EF training and intervention for autistic children and adolescents at an early stage.

The whole is greater than the sum of its parts: Using cognitive profiles to predict academic achievement

BACKGROUND

Executive functions (EFs) are thought to work in concert to support academic skill. However, EFs are often examined independently, obscuring their symbiotic contribution. We examined the relationship between students' holistic EF profiles and their academic success.

METHODS

We sampled over 1200 7-15 year old students from a diverse school district (16 % White; 32 % low income) in the United States. We used 9 EF assessments to construct cognitive profiles via self-organizing maps. We then related profiles to academic achievement scores from both laboratory-based assessments and state-administered standardized tests of reading and math.

RESULTS

Six profiles differed in EF performance, but their differences in academic achievement did not suggest a linear relationship between individual EFs and academic skill.

CONCLUSIONS

We show cognitive profiles based on individual strengths and weaknesses in EFs can reveal multiple cognitive paths to the same academic outcome.

Autistic Symptoms, Irritability, and Executive Dysfunctions: Symptom Dynamics from Multi-Network Models

Socio-cognitive difficulties in individuals with autism spectrum disorder (ASD) are heterogenuous and often co-occur with irritability symptoms, such as angry/grouchy mood and temper outbursts. However, the specific relations between individual symptoms are not well-represented in conventional methods analyzing aggregated autistic symptoms and ASD diagnosis. Moreover, the cognitive-behavioral mechanisms linking ASD to irritability are largely unknown. This study investigated the dynamics between autistic (Social Responsiveness Scale) and irritability (Affective Reactivity Index) symptoms and executive functions (Cambridge Neuropsychological Test Automated Battery) in a sample of children and adolescents with ASD, their unaffected siblings, and neurotypical peers (N = 345, aged 6-18 years, 78.6% male). Three complementary networks across the entire sample were computed: (1) Gaussian graphical network estimating the conditional correlations between symptom nodes; (2) Relative importance network computing relative influence between symptoms; (3) Bayesian directed acyclic graph estimating predictive directionality between symptoms. Networks revealed numerous partial correlations within autistic (rs = .07-.56) and irritability (rs = .01-.45) symptoms and executive functions (rs = -.83 to .67) but weak connections between clusters. This segregated pattern converged in all directed and supplementary networks. Plausible predictive paths were found between social communication difficulties to autism mannerisms and between "angry frequently" to "lose temper easily." Autistic and irritability symptoms are two relatively independent families of symptoms. It is unlikely that executive dysfunctions explain elevated irritability in ASD. Findings underscore the need for researching other mood and cognitive-behavioral bridge symptoms, which may inform individualized treatments for co-occurring irritability in ASD.

Moving Together: Social Motor Synchrony in Autistic Peer Partners Depends on Partner and Activity Type

Some suggest autistic people display impaired Interpersonal Synchrony. However, partners of different neurotypes can struggle to connect and empathise with one another. We used Motion Energy Analysis to examine Social Motor Synchrony (SMS) in familiar partners of the same neurotype: pairs of autistic and of neurotypical children. Partners played two shared tablet activities, one to support collaboration by facilitating engagement and other-awareness (Connect), and one with no additional design features to facilitate collaboration (Colours). The neurotypical group showed similar SMS to the autistic group in Colours but lower SMS in Connect. The autistic group displayed similar levels of SMS in each activity. Autistic children can synchronise to a similar, or greater, degree than neurotypical children when the social context and type of task are considered.

A clustering approach identifies an Autism Spectrum Disorder subtype more responsive to chronic oxytocin treatment

Over the last decade, a number of clinical trials have reported effects of chronic treatment with intranasal oxytocin on autistic symptoms but with inconsistent findings. Autism is a heterogeneous disorder and one factor which may influence treatment outcome is whether a subtype of individuals is more sensitive to oxytocin. In a recent cross-over trial on 41 young autistic children we reported that 44% showed a reliable improvement in clinical symptoms (Autism Diagnostic Observation Schedule, ADOS-2) after a placebo-controlled, 6-week intranasal oxytocin intervention where treatment was given every other day followed by a period of positive social interaction. In the current re-assessment of the data, we used an unsupervised data-driven cluster analysis approach to identify autism subtypes using 23 different demographic, social subtype, endocrine, eye-tracking and clinical symptom measures taken before treatment and this revealed an optimum of two different subtypes. We then assessed the proportion of identified responders to oxytocin and found that while 61.5% of one subtype included responders only 13.3% of the other did so. During the placebo phase there was no difference between the two subtypes for the small proportion of responders (19.2% vs 6.7%). This oxytocin-sensitive subtype also showed overall significant post-treatment clinical and eye-tracking measure changes. The oxytocin-sensitive subtype was primarily characterized at baseline by lower initial clinical severity (ADOS-2) and greater interest in the eye-region of emotional faces. These features alone were nearly as efficient in identifying the two subtypes as all 23 baseline measures and this easy-to-conduct approach may help rapidly and objectively screen for oxytocin responders. Future clinical trials using oxytocin interventions may therefore achieve greater success by focusing on children with this specific autism subtype and help develop individualized oxytocin intervention.

Empirically derived symptom profiles in adults with attention-Deficit/hyperactivity disorder: An unsupervised machine learning approach

BACKGROUND

Attention-deficit/hyperactivity disorder (ADHD) is associated with various cognitive, behavioral, and mood symptoms that complicate diagnosis and treatment. The heterogeneity of these symptoms may also vary depending on certain sociodemographic factors. It is therefore important to establish more homogenous symptom profiles in patients with ADHD and determine their association with the patient's sociodemographic makeup. The current study used unsupervised machine learning to identify symptom profiles across various cognitive, behavioral, and mood symptoms in adults with ADHD. It was then examined whether symptom profiles differed based on relevant sociodemographic factors.

METHODS

Participants were 382 adult outpatients (62% female; 51% non-Hispanic White) referred for neuropsychological evaluation for ADHD.

RESULTS

Employing Gaussian Mixture Modeling, we identified two distinct symptom profiles in adults with ADHD: "ADHD-Plus Symptom Profile" and "ADHD-Predominate Symptom Profile." These profiles were primarily differentiated by internalizing psychopathology (Cohen's d = 1.94-2.05), rather than by subjective behavioral and cognitive symptoms of ADHD or neurocognitive test performance. In a subset of 126 adults without ADHD who were referred for the same evaluation, the unsupervised machine learning algorithm only identified one symptom profile. Group comparison analyses indicated that female patients were most likely to present with an ADHD-Plus Symptom Profile (χ2 = 5.43, p < .001).

CONCLUSION

The machine learning technique used in this study appears to be an effective way to elucidate symptom profiles emerging from comprehensive ADHD evaluations. These findings further underscore the importance of considering internalizing symptoms and patients' sex when contextualizing adult ADHD diagnosis and treatment.

ASD and ADHD: Divergent activating patterns of prefrontal cortex in executive function tasks?

The functional Near-infrared Spectroscopy (fNIRS) has been more and more widely used to measure the activation state of prefrontal cortex when performing function-related tasks among children with various developmental disorders. Children with autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD) have shown obvious executive function defects. We aimed to summarize the studies with fNIRS, to summarize the activation patterns of prefrontal cortex (PFC) of participants with ASD or ADHD in performing functional tasks. We selected 630 articles according to PRISMA guidelines, and the eligibility criteria were: 6-16 years old individuals diagnosed with ASD or ADHD by DSM-4 or 5, using fNIRS, having executive function (EF) task, typical development (TD) control, and between-group comparison of PFC activation. Eleven studies were finally included in the quantitative analysis, and compared to TD, ASD and ADHD showed the opposite PFC activation patterns during n-back tasks. We discussed the task-specific PFC activation in young participants with ASD and ADHD, and provided some new ideas on that issue.

Delineating Transdiagnostic Subtypes in Neurodevelopmental Disorders via Contrastive Graph Machine Learning of Brain Connectivity Patterns

Neurodevelopmental disorders, such as Attention Deficit/Hyperactivity Disorder (ADHD) and Autism Spectrum Disorder (ASD), are characterized by comorbidity and heterogeneity. Identifying distinct subtypes within these disorders can illuminate the underlying neurobiological and clinical characteristics, paving the way for more tailored treatments. We adopted a novel transdiagnostic approach across ADHD and ASD, using cutting-edge contrastive graph machine learning to determine subtypes based on brain network connectivity as revealed by resting-state functional magnetic resonance imaging. Our approach identified two generalizable subtypes characterized by robust and distinct functional connectivity patterns, prominently within the frontoparietal control network and the somatomotor network. These subtypes exhibited pronounced differences in major cognitive and behavioural measures. We further demonstrated the generalizability of these subtypes using data collected from independent study sites. Our data-driven approach provides a novel solution for parsing biological heterogeneity in neurodevelopmental disorders.

Mapping neurodevelopmental diversity in executive function

Executive function, an umbrella term used to describe the goal-directed regulation of thoughts, actions, and emotions, is an important dimension implicated in neurodiversity and established malleable predictor of multiple adult outcomes. Neurodevelopmental differences have been linked to both executive function strengths and weaknesses, but evidence for associations between specific profiles of executive function and specific neurodevelopmental conditions is mixed. In this exploratory study, we adopt an unsupervised machine learning approach (self-organising maps), combined with k-means clustering to identify data-driven profiles of executive function in a transdiagnostic sample of 566 neurodivergent children aged 8-18 years old. We include measures designed to capture two distinct aspects of executive function: performance-based tasks designed to tap the state-like efficiency of cognitive skills under optimal conditions, and behaviour ratings suited to capturing the trait-like application of cognitive control in everyday contexts. Three profiles of executive function were identified: one had consistent difficulties across both types of assessments, while the other two had inconsistent profiles of predominantly rating- or predominantly task-based difficulties. Girls and children without a formal diagnosis were more likely to have an inconsistent profile of primarily task-based difficulties. Children with these different profiles had differences in academic achievement and mental health outcomes and could further be differentiated from a comparison group of children on both shared and profile-unique patterns of neural white matter organisation. Importantly, children's executive function profiles were not directly related to diagnostic categories or to dimensions of neurodiversity associated with specific diagnoses (e.g., hyperactivity, inattention, social communication). These findings support the idea that the two types of executive function assessments provide non-redundant information related to children's neurodevelopmental differences and that they should not be used interchangeably. The findings advance our understanding of executive function profiles and their relationship to behavioural outcomes and neural variation in neurodivergent populations.

Modified Meta Heuristic BAT with ML Classifiers for Detection of Autism Spectrum Disorder

ASD (autism spectrum disorder) is a complex developmental and neurological disorder that impacts the social life of the affected person by disturbing their capability for interaction and communication. As it is a behavioural disorder, early treatment will improve the quality of life of ASD patients. Traditional screening is carried out with behavioural assessment through trained physicians, which is expensive and time-consuming. To resolve the issue, several conventional methods strive to achieve an effective ASD identification system, but are limited by handling large data sets, accuracy, and speed. Therefore, the proposed identification system employed the MBA (modified bat) algorithm based on ANN (artificial neural networks), modified ANN (modified artificial neural networks), DT (decision tree), and KNN (k-nearest neighbours) for the classification of ASD in children and adolescents. A BA (bat algorithm) is utilised for the automatic zooming capability, which improves the system's efficacy by excellently finding the solutions in the identification system. Conversely, BA is effective in the identification, it still has certain drawbacks like speed, accuracy, and falls into local extremum. Therefore, the proposed identification system modifies the BA optimisation with random perturbation of trends and optimal orientation. The dataset utilised in the respective model is the Q-chat-10 dataset. This dataset contains data of four stages of age groups such as toddlers, children, adolescents, and adults. To analyse the quality of the dataset, dataset evaluation mechanism, such as the Chi-Squared Statistic and p-value, are used in the respective research. The evaluation signifies the relation of the dataset with respect to the proposed model. Further, the performance of the proposed detection system is examined with certain performance metrics to calculate its efficiency. The outcome revealed that the modified ANN classifier model attained an accuracy of 1.00, ensuring improved performance when compared with other state-of-the-art methods. Thus, the proposed model was intended to assist physicians and researchers in enhancing the diagnosis of ASD to improve the standard of life of ASD patients.

TSP-GNN: a novel neuropsychiatric disorder classification framework based on task-specific prior knowledge and graph neural network

Neuropsychiatric disorder (ND) is often accompanied by abnormal functional connectivity (FC) patterns in specific task contexts. The distinctive task-specific FC patterns can provide valuable features for ND classification models using deep learning. However, most previous studies rely solely on the whole-brain FC matrix without considering the prior knowledge of task-specific FC patterns. Insight by the decoding studies on brain-behavior relationship, we develop TSP-GNN, which extracts task-specific prior (TSP) connectome patterns and employs graph neural network (GNN) for disease classification. TSP-GNN was validated using publicly available datasets. Our results demonstrate that different ND types show distinct task-specific connectivity patterns. Compared with the whole-brain node characteristics, utilizing task-specific nodes enhances the accuracy of ND classification. TSP-GNN comprises the first attempt to incorporate prior task-specific connectome patterns and the power of deep learning. This study elucidates the association between brain dysfunction and specific cognitive processes, offering valuable insights into the cognitive mechanism of neuropsychiatric disease.

Subtype classification of attention deficit hyperactivity disorder with hierarchical binary hypothesis testing framework

Objective. The diagnosis of attention deficit hyperactivity disorder (ADHD) subtypes is important for the refined treatment of ADHD children. Although automated diagnosis methods based on machine learning are performed with structural and functional magnetic resonance imaging (sMRI and fMRI) data which have full observation of brains, they are not satisfactory with the accuracy of less than80%for the ADHD subtype diagnosis.Approach. To improve the accuracy and obtain the biomarker of ADHD subtypes, we proposed a hierarchical binary hypothesis testing (H-BHT) framework by using brain functional connectivity (FC) as input bio-signals. The framework includes a two-stage procedure with a decision tree strategy and thus becomes suitable for the subtype classification. Also, typical FC is extracted in both two stages of identifying ADHD subtypes. That means the important FC is found out for the subtype recognition.Main results. We apply the proposed H-BHT framework to resting state fMRI datasets from ADHD-200 consortium. The results are achieved with the average accuracy97.1%and an average kappa score 0.947. Discriminative FC between ADHD subtypes is found by comparing the P-values of typical FC.Significance. The proposed framework not only is an effective structure for ADHD subtype classification, but also provides useful reference for multiclass classification of mental disease subtypes.

Using micro-cognition biomarkers of neurosystem dysfunction to redefine ADHD subtypes: A scalable digital path to diagnosis based on brain function

Symptom-based diagnosis does not align with underlying neruropathology, confounding new treatment development and treatment selection for individual patients. Using high precision micro-cognition biomarkers of neurosystem dysfunction acquired during digital neurotherapy (DNT), we characterized subgroups of ADHD children with different neuropathology. K-means clustering applied to 69 children 6-9 years old with ADHD using performance variables from a Go/NoGo test normalized against 58 typically developing (TD) children identified four subgroups that were validated and further characterized by micro-cognition biomarkers extracted from thousands of responses during the DNT. The clusters differed on emblematic features of ADHD. Cluster 4 showed poor response inhibition and inconsistent attention. Cluster 3 showed only poor response inhibition and the other two showed neither. Cluster 2 showed faster and more consistent responses, higher detection of simple targets and better working memory than TD children but marked performance decrements when required to track multiple targets or ignore distractors. Cluster 1 showed much greater ability recognizing members of abstract categories rather than natural categories that children learn through physical interaction with the environment while Cluster 4 was the opposite. Fine-grained, low-cost, noninvasive, and scalable digital micro-cognition biomarkers can identify patients with the same symptom-based diagnosis but differing neuropathology.

Machine learning in attention-deficit/hyperactivity disorder: new approaches toward understanding the neural mechanisms

Attention-deficit/hyperactivity disorder (ADHD) is a highly prevalent and heterogeneous neurodevelopmental disorder in children and has a high chance of persisting in adulthood. The development of individualized, efficient, and reliable treatment strategies is limited by the lack of understanding of the underlying neural mechanisms. Diverging and inconsistent findings from existing studies suggest that ADHD may be simultaneously associated with multivariate factors across cognitive, genetic, and biological domains. Machine learning algorithms are more capable of detecting complex interactions between multiple variables than conventional statistical methods. Here we present a narrative review of the existing machine learning studies that have contributed to understanding mechanisms underlying ADHD with a focus on behavioral and neurocognitive problems, neurobiological measures including genetic data, structural magnetic resonance imaging (MRI), task-based and resting-state functional MRI (fMRI), electroencephalogram, and functional near-infrared spectroscopy, and prevention and treatment strategies. Implications of machine learning models in ADHD research are discussed. Although increasing evidence suggests that machine learning has potential in studying ADHD, extra precautions are still required when designing machine learning strategies considering the limitations of interpretability and generalization.

Exploring cognitive, behavioral and autistic trait network topology in very preterm and term-born children

Introduction

Compared to full-term (FT) born peers, children who were born very preterm (VPT; <32 weeks' gestation) are likely to display more cognitive and behavioral difficulties, including inattention, anxiety and socio-communication problems. In the published literature, such difficulties tend to be studied independently, thus failing to account for how different aspects of child development interact. The current study aimed to investigate children's cognitive and behavioral outcomes as interconnected, dynamically related facets of development that influence one another.

Methods

Participants were 93 VPT and 55 FT children (median age 8.79 years). IQ was evaluated with the Wechsler Intelligence Scale for Children-4th edition (WISC-IV), autism spectrum condition (ASC) traits with the social responsiveness scale-2nd edition (SRS-2), behavioral and emotional problems with the strengths and difficulties questionnaire (SDQ), temperament with the temperament in middle childhood questionnaire (TMCQ) and executive function with the behavior rating inventory of executive functioning (BRIEF-2). Outcome measures were studied in VPT and FT children using Network Analysis, a method that graphically represents partial correlations between variables and yields information on each variable's propensity to form a bridge between other variables.

Results

VPT and FT children exhibited marked topological differences. Bridges (i.e., the variables most connected to others) in the VPT group network were: conduct problems and difficulties with organizing and ordering their environment. In the FT group network, the most important bridges were: difficulties with initiating a task or activity and prosocial behaviors, and greater emotional problems, such as lower mood.

Discussion

These findings highlight the importance of targeting different aspects of development to support VPT and FT children in person-based interventions.

Sex differences in medication-naïve adults with attention-deficit/hyperactivity disorder: a counting Stroop functional MRI study

Emerging evidence supports deficits in executive functions in the fronto-striato-parietal network in individuals with attention-deficit/hyperactivity disorder (ADHD). However, most functional studies recruited men with ADHD only, leaving it unclear whether executive deficits are also demonstrated in women with ADHD. Thus, we used functional magnetic resonance imaging to examine the sex differences in a counting Stroop task that explored interference control. The sample consisted of 55 medication-naïve adults with ADHD (28 men, 27 women) and 52 healthy controls (HC, 26 men, 26 women). The Conners' Continuous Performance Test further evaluated the performance of focused attention (standard deviation of the reaction time, RTSD) and vigilance (the reaction time change across different inter-stimulus intervals, RTISI). First, for the main effect of diagnosis, compared to the HC group, the ADHD group showed less activation in the caudate nucleus and inferior frontal gyrus (IFG). Second, for the main effect of sex, no significant effects were found. Third, a diagnosis-by-sex interaction indicated that the magnitude of ADHD-HC difference was greater for women than men in the right IFG and precuneus, reflecting greater difficulties for ADHD women to resolve interference. Conversely, no significant brain activation showed greater ADHD-HC difference in men than women. Also, reduced right IFG and precuneus activation was negatively associated with the scores assessing focused attention and vigilance in ADHD women, indicating that the attentional abilities are disrupted in ADHD women. Abnormalities in the frontoparietal areas may represent the main difference between ADHD women and ADHD men.

Eye-movement indices of arousal predict ADHD and comorbid externalizing symptoms over a 2-year period

Attention-deficit/hyperactivity disorder (ADHD) follows a variable course across childhood. Disrupted arousal has been hypothesized to underlie core symptoms as well as comorbid internalizing and externalizing conditions. The current study examined eye-movement and pupil-dilation metrics indexing arousal as longitudinal predictors of ADHD, externalizing, and internalizing symptoms over a 2-year period. Participants aged 8-13 years (N = 54, 30% with a diagnosis of ADHD) completed a modified version of the gap-overlap task including arousal-inducing auditory warning signals. Parents rated symptoms at the time of testing and at 2 years follow-up. Phasic alerting (reaction-time reduction after alerting cues) is an index of arousal. Here, larger phasic alerting effects predicted higher ADHD-symptom levels 2 years later. Blunted pupil-dilation responses predicted externalizing symptoms at T2, controlling for ADHD and externalizing at T1. Our results support the theory that ADHD is associated with altered arousal. Blunted arousal reactivity may be a longitudinal risk factor for externalizing problems in children with ADHD symptoms.

Transdiagnostic profiles of behaviour and communication relate to academic and socioemotional functioning and neural white matter organisation

BACKGROUND

Behavioural and language difficulties co-occur in multiple neurodevelopmental conditions. Our understanding of these problems has arguably been slowed by an overreliance on study designs that compare diagnostic groups and fail to capture the overlap across different neurodevelopmental disorders and the heterogeneity within them.

METHODS

We recruited a large transdiagnostic cohort of children with complex needs (N = 805) to identify distinct subgroups of children with common profiles of behavioural and language strengths and difficulties. We then investigated whether and how these data-driven groupings could be distinguished from a comparison sample (N = 158) on measures of academic and socioemotional functioning and patterns of global and local white matter connectome organisation. Academic skills were assessed via standardised measures of reading and maths. Socioemotional functioning was captured by the parent-rated version of the Strengths and Difficulties Questionnaire.

RESULTS

We identified three distinct subgroups of children, each with different levels of difficulties in structural language, pragmatic communication, and hot and cool executive functions. All three subgroups struggled with academic and socioemotional skills relative to the comparison sample, potentially representing three alternative but related developmental pathways to difficulties in these areas. The children with the weakest language skills had the most widespread difficulties with learning, whereas those with more pronounced difficulties with hot executive skills experienced the most severe difficulties in the socioemotional domain. Each data-driven subgroup could be distinguished from the comparison sample based on both shared and subgroup-unique patterns of neural white matter organisation. Children with the most pronounced deficits in language, cool executive, or hot executive function were differentiated from the comparison sample by altered connectivity in predominantly thalamocortical, temporal-parietal-occipital, and frontostriatal circuits, respectively.

CONCLUSIONS

These findings advance our understanding of commonly co-morbid behavioural and language problems and their relationship to behavioural outcomes and neurobiological substrates.

Individual brain regulation as learned via neurofeedback is related to affective changes in adolescents with autism spectrum disorder

BACKGROUND

Emotions often play a role in neurofeedback (NF) regulation strategies. However, investigations of the relationship between the induced neuronal changes and improvements in affective domains are scarce in electroencephalography-based studies. Thus, we extended the findings of the first study on slow cortical potential (SCP) NF in autism spectrum disorder (ASD) by linking affective changes to whole-brain activity during rest and regulation.

METHODS

Forty-one male adolescents with ASD were scanned twice at rest using functional magnetic resonance imaging. Between scans, half underwent NF training, whereas the other half received treatment as usual. Furthermore, parents reported on their child's affective characteristics at each measurement. The NF group had to alternatingly produce negative and positive SCP shifts during training and was additionally scanned using functional magnetic resonance imaging while applying their developed regulation strategies.

RESULTS

No significant treatment group-by-time interactions in affective or resting-state measures were found. However, we found increases of resting activity in the anterior cingulate cortex and right inferior temporal gyrus as well as improvements in affective characteristics over both groups. Activation corresponding to SCP differentiation in these regions correlated with the affective improvements. A further correlation was found for Rolandic operculum activation corresponding to positive SCP shifts. There were no significant correlations with the respective achieved SCP regulation during NF training.

CONCLUSION

SCP NF in ASD did not lead to superior improvements in neuronal or affective functioning compared to treatment as usual. However, the affective changes might be related to the individual strategies and their corresponding activation patterns as indicated by significant correlations on the whole-brain level. Trial registration This clinical trial was registered at drks.de (DRKS00012339) on 20th April, 2017.

Pilot study to explore poor visual searching capabilities in children with ADHD: a tablet-based computerized test battery study

Aim: The frequent visual attention deficiency reported in children with attention-deficit/hyperactivity disorder (ADHD) could represent a relevant biomarker but robust estimates of such cognitive impairment in clinical populations remained challenging. To assess visual attention impairment in children ADHD using a new design tablet-based computerized test battery which allowed objective recording of visual search performances.Methods: Forty-nine children with ADHD and their IQ- and age-matched typically developmental (TD) children were enrolled in the study. Visual attention abilities were estimated by using the computerized modified barrage test developed by Metrisquare. We analyzed the time spent to achieve the whole battery and, the errors and omissions done by each child during each of the three sub-tasks.Results: We observed a significant association between the load of sustained attention requested to perform a sub-task and the numbers of errors and omissions made by the children whatever the group considered. During the most stringent sub-task in term of visual attention engagement, children with ADHD displayed more significant errors and omissions when compared to IQ- and age-matched controls. This effect was not mediated by the time spent to perform the task since we did not report any significant difference between groups.Conclusion: The different performance of the most stringent sub-task observed in children with ADHD could be due to their deficient neural activity in frontal areas responsible of visual endogenous attention needed for difficult visual searching tasks. This cognitive battery could be a useful instrument to estimate visual attention impairment in children with ADHD.HIGHLIGHTSWe assessed if a new design tablet-based computerized test battery would allow objective recording of visual search performances.We observed that children with ADHD made significantly more errors and omissions with respect to age-, sex- matched controls during the most stringent sub-task in terms of visual attention engagementThe tablet-based computerized test battery could be a promising tool to objectively estimate abnormal attention search impairment in ADHD.

Inconsistencies between Subjective Reports of Cognitive Difficulties and Performance on Cognitive Tests are Associated with Elevated Internalising and Externalising Symptoms in Children with Learning-related Problems

Children with learning difficulties are commonly assumed to have underlying cognitive deficits by health and educational professionals. However, not all children referred for psycho-educational assessment will be found to have deficits when their abilities are measured by performance on cognitive tasks. The primary aim of this study was to estimate the prevalence of this inconsistent cognitive profile (ICP) in a transdiagnostic sample of children referred by health and education service providers for problems related to attention, learning and memory (N = 715). A second aim was to explore whether elevated mental health problems were associated with ICPs. Findings suggest that approximately half of this sample could be characterised as having an ICP. Cognitive difficulties, whether identified by parent ratings or task performance, were associated with elevated internalising and externalising difficulties. Crucially, a larger discrepancy between a parent's actual ratings of a child's cognitive difficulties and the ratings that would be predicted based on the child's performance on cognitive tasks was associated greater internalising and externalising difficulties for measures of working memory, and greater externalising difficulties for measures of attention. These findings suggest that subjective cognitive difficulties occurring in the absence of any task-based performance deficits may be a functional problem arising from mental health problems.

Characterizing the ASD-ADHD phenotype: measurement structure and invariance in a clinical sample

BACKGROUND

Autism Spectrum Disorder (ASD) and Attention Deficit Hyperactivity Disorder (ADHD) have considerable overlap, supporting the need for a dimensional framework that examines neurodevelopmental domains which cross traditional diagnostic boundaries. In the following study, we use factor analysis to deconstruct the ASD-ADHD phenotype into its underlying phenotypic domains and test for measurement invariance across adaptive functioning, age, gender and ASD/ADHD clinical diagnoses.

METHODS

Participants included children and youth (aged 3-20 years) with a clinical diagnosis of ASD (n = 727) or ADHD (n = 770) for a total of 1,497 participants. Parents of these children completed the Social Communication Questionnaire (SCQ), a measure of autism symptoms, and the Strengths and Weaknesses of ADHD and Normal Behaviour (SWAN) questionnaire, a measure of ADHD symptoms. An exploratory factor analysis (EFA) was performed on combined SCQ and SWAN items. This was followed by a confirmatory factor analysis (CFA) and tests of measurement invariance.

RESULTS

EFA revealed a four-factor solution (inattention, hyperactivity/impulsivity, social-communication, and restricted, repetitive, behaviours and interests (RRBI)) and a CFA confirmed good model fit. This solution also showed good model fit across subgroups of interest.

CONCLUSIONS

Our study shows that a combined ASD-ADHD phenotype is characterized by two latent ASD domains (social communication and RRBIs) and two latent ADHD domains (inattention and hyperactivity/impulsivity). We established measurement invariance of the derived measurement model across adaptive functioning, age, gender and ASD/ADHD diagnoses.

Self-management of daily life tasks in diploma-track youth with disabilities

PURPOSE

Youth with disabilities who graduate with a regular high school diploma often continue to have difficulties in their daily functioning that ultimately impact adulthood outcomes. To better understand these functional difficulties and determine how best to address them, it is important to distinguish deficits in discrete skills from difficulty organizing skills to self-manage complex tasks associated with adult roles. The purpose of this study was to explore the extent to which challenges in social, executive function and behavior management factors relate to these two aspects of daily functioning.

METHODS

This is a secondary analysis of the National Longitudinal Transition Study 2 funded by the United States Department of Education. The direct and indirect associations between youth underlying factors and self-management of daily life tasks (SMDLT) versus discrete functional skills were modelled using structural equation modelling.

RESULTS

A model incorporating social skills, communication, and behavior regulation explained 55% of the variance in SMDLT. In contrast, the model predicting discrete functional skills had fewer significant associations and described less variance (37%) in the outcome.

CONCLUSIONS

Findings suggest that using measures of SMDLT and designing targeted interventions for SMDLT might help improve participation in independent living and productivity for diploma-track youth with disabilities.Implications for rehabilitationSuccessful transition from high school to adult roles requires the ability to self-manage the daily life tasks required for those roles, such as employment, post-secondary education, and independent living.The ability to self-manage daily tasks is distinct from mastery of discrete functional skills and should be assessed with measures that uniquely examine this domain.Social and communication skills, executive functioning, and behavioral regulation, are important contributors to the ability to self-manage life tasks for diploma-track youth with disabilities and should be incorporated into multifaceted interventions.Interventions to improve self-management of tasks should include teaching strategies and practice coordinating underlying skills in flexible ways that meet the varying demands of tasks and diverse environments.

Understanding patterns of heterogeneity in executive functioning during adolescence: Evidence from population-level data

Executive functioning (EF) is fundamental to positive development. Yet, little is known about how to best characterize constellations of EF skills that may inform disparate associations between EF and behavior during adolescence. In the current study, cross-validated latent profile analysis (LPA) was used to derive profiles of EF based on measures of inhibitory control, working memory, and cognitive flexibility using data from 11,672 youth (52.2% male, mean age = 9.91 years) in the Adolescent Brain and Cognitive Development study. Four meaningful EF profiles emerged from the data representing Average EF, High EF, Low Inhibitory Control, and Low EF. Boys, youth from low-income households, and early developing youth were more likely to be in profiles distinguished by lower EF. Profile membership also predicted differences in externalizing, internalizing, and other problem behaviors assessed one year later. Findings indicate that youth may have distinct constellations of EF skills, underscoring the need for person-centered approaches that focus on patterns of individual characteristics.

The relationship between executive function, neurodevelopmental disorder traits, and academic achievement in university students

Difficulties with executive function have often been identified in individuals with various neurodevelopmental disorders such as Autism Spectrum Disorder (ASD), Attention-Deficit Hyperactivity Disorder (ADHD), and Developmental Co-ordination Disorder (DCD). Additionally, in childhood and adolescence, executive functioning is an important predictor of academic achievement. However, less research has explored these relationships in adult students, and those with a high level of neurodevelopmental disorder traits but no clinical diagnosis. Therefore, the current study aimed to assess whether ASD, ADHD, and DCD traits can predict academic achievement in university students, and whether traits of these neurodevelopmental conditions moderate the relationship between executive function and academic achievement. Both neurotypical students and those with a clinical diagnosis of a neurodevelopmental disorder were able to participate, with the majority being neurotypical. Participants completed four self-report questionnaires and provided a measure of academic achievement based on their university assignment results. Traits of ASD, ADHD, and DCD alone did not predict achievement, however, traits of ADHD and DCD significantly moderated the relationship between executive function and academic achievement. ASD traits did not significantly moderate this relationship. Implications and suggestions for future research are also discussed.

Cognitive, perceptual, and motor profiles of school-aged children with developmental coordination disorder

Developmental coordination disorder (DCD) is a heterogeneous condition. Besides motor impairments, children with DCD often exhibit poor visual perceptual skills and executive functions. This study aimed to characterize the motor, perceptual, and cognitive profiles of children with DCD at the group level and in terms of subtypes. A total of 50 children with DCD and 31 typically developing (TD) peers (7–11 years old) underwent a comprehensive neuropsychological (15 tests) and motor (three subscales of the Movement Assessment Battery for Children-2) assessment. The percentage of children with DCD showing impairments in each measurement was first described. Hierarchical agglomerative and K-means iterative partitioning clustering analyses were then performed to distinguish the subtypes present among the complete sample of children (DCD and TD) in a data-driven way. Moderate to large percentages of children with DCD showed impaired executive functions (92%) and praxis (meaningless gestures and postures, 68%), as well as attentional (52%), visual perceptual (46%), and visuomotor (36%) skills. Clustering analyses identified five subtypes, four of them mainly consisting of children with DCD and one of TD children. These subtypes were characterized by: (i) generalized impairments (8 children with DCD), (ii) impaired manual dexterity, poor balance (static/dynamic), planning, and alertness (15 DCD and 1 TD child), (iii) impaired manual dexterity, cognitive inhibition, and poor visual perception (11 children with DCD), (iv) impaired manual dexterity and cognitive inhibition (15 DCD and 5 TD children), and (v) no impairment (25 TD and 1 child with DCD). Besides subtle differences, the motor and praxis measures did not enable to discriminate between the four subtypes of children with DCD. The subtypes were, however, characterized by distinct perceptual or cognitive impairments. These results highlight the importance of assessing exhaustively the perceptual and cognitive skills of children with DCD.

Elevated symptoms of executive dysfunction predict lower adaptive functioning in 3-year-olds with autism spectrum disorder

Executive functioning (EF) deficits co-occur frequently with autism spectrum disorder (ASD) and have a long-term detrimental impact on quality of life of children and their families. Timely identification of risk for EF vulnerabilities may hasten access to early intervention and alleviate their long-term consequences. This study examines (1) if EF deficits are elevated in toddlers with ASD compared to nonautistic siblings of children with ASD, typically developing (TYP) toddlers, and toddlers with atypical developmental presentation; and (2) if EF deficits have a detrimental effect on adaptive functioning in ASD. Participants were recruited between September 2014 and October 2019 and included 73 toddlers with ASD, 33 nonautistic siblings of children with ASD, 35 toddlers with atypical development, and 28 TYP toddlers matched on chronological age (M = 39.01 months, SD = 3.11). EF deficits were measured using the BRIEF-P; adaptive skills were measured using the VABS-II. Whenever appropriate, analyses were controlled for MSEL verbal and nonverbal developmental quotient, ADOS-2 autism severity scores, and sex. Analyses revealed that toddlers with ASD exhibited elevated BRIEF-P scores across all domains compared to each of the three comparison groups. Higher BRIEF-P scores were associated with lower adaptive social, communication, and daily living skills while controlling for symptom severity, verbal and nonverbal functioning, and sex. In conclusion, marked vulnerabilities in EF are already present in 3-year-old toddlers with ASD and are predictive of the level of adaptive functioning in ASD. EF vulnerabilities in toddlers should be targeted for intervention to improve long-term outcomes in ASD. LAY SUMMARY: Many children with autism experience vulnerabilities in executive functioning (EF), which may include challenges with inhibition, working memory, cognitive flexibility, and planning. The study shows that these vulnerabilities can already be detected at age three and that their presence is linked with lower social, communication, and daily living skills. Screening children with ASD for EF challenges and helping those who have difficulties may improve their long-term outcomes.

Revisiting the seven pillars of RDoC

BACKGROUND

In 2013, a few years after the launch of the National Institute of Mental Health's Research Domain Criteria (RDoC) initiative, Cuthbert and Insel published a paper titled "Toward the future of psychiatric diagnosis: the seven pillars of RDoC." The RDoC project is a translational research effort to encourage new ways of studying psychopathology through a focus on disruptions in normal functions (such as reward learning or attention) that are defined jointly by observable behavior and neurobiological measures. The paper outlined the principles of the RDoC research framework, including emphases on research that acquires data from multiple measurement classes to foster integrative analyses, adopts dimensional approaches, and employs novel methods for ascertaining participants and identifying valid subgroups.

DISCUSSION

To mark the first decade of the RDoC initiative, we revisit the seven pillars and highlight new research findings and updates to the framework that are related to each. This reappraisal emphasizes the flexible nature of the RDoC framework and its application in diverse areas of research, new findings related to the importance of developmental trajectories within and across neurobehavioral domains, and the value of computational approaches for clarifying complex multivariate relations among behavioral and neurobiological systems.

CONCLUSION

The seven pillars of RDoC have provided a foundation that has helped to guide a surge of new studies that have examined neurobehavioral domains related to mental disorders, in the service of informing future psychiatric nosology. Building on this footing, future areas of emphasis for the RDoC project will include studying central-peripheral interactions, developing novel approaches to phenotyping for genomic studies, and identifying new targets for clinical trial research to facilitate progress in precision psychiatry.

Impulsivity Moderates the Effect of Neurofeedback Training on the Contingent Negative Variation in Autism Spectrum Disorder

Background

The contingent negative variation (CNV) is a well-studied indicator of attention- and expectancy-related processes in the human brain. An abnormal CNV amplitude has been found in diverse neurodevelopmental psychiatric disorders. However, its role as a potential biomarker of successful clinical interventions in autism spectrum disorder (ASD) remains unclear.

Methods

In this randomized controlled trial, we investigated how the CNV changes following an intensive neurofeedback training. Therefore, twenty-one adolescents with ASD underwent 24 sessions of slow cortical potential (SCP) neurofeedback training. Twenty additional adolescents with ASD formed a control group and received treatment as usual. CNV waveforms were obtained from a continuous performance test (CPT), which all adolescents performed before and after the corresponding 3-month long training period. In order to utilize all available neural time series, trial-based area under the curve values for all four electroencephalogram (EEG) channels were analyzed with a hierarchical Bayesian model. In addition, the model included impulsivity, inattention, and hyperactivity as potential moderators of change in CNV.

Results

Our model implies that impulsivity moderates the effects of neurofeedback training on CNV depending on group. In the control group, the average CNV amplitude decreased or did not change after treatment as usual. In the experimental group, the CNV changed depending on the severity of comorbid impulsivity symptoms. The average CNV amplitude of participants with low impulsivity scores decreased markedly, whereas the average CNV amplitude of participants with high impulsivity increased.

Conclusion

The degree of impulsivity seems to play a crucial role in the changeability of the CNV following an intensive neurofeedback training. Therefore, comorbid symptomatology should be recorded and analyzed in future EEG-based brain training interventions.

Clinical Trial Registration

https://www.drks.de, identifier DRKS00012339.

Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders (MIND-SET): Protocol for a Cross-sectional Comorbidity Study From a Research Domain Criteria Perspective

BACKGROUND

It is widely acknowledged that comorbidity between psychiatric disorders is common. Shared and diverse underpinnings of psychiatric disorders cannot be systematically understood based on symptom-based categories of mental disorders, which map poorly onto pathophysiological mechanisms. In the Measuring Integrated Novel Dimensions in Neurodevelopmental and Stress-Related Mental Disorders (MIND-SET) study, we make use of current concepts of comorbidity that transcend the current diagnostic categories. We test this approach to psychiatric problems in patients with frequently occurring psychiatric disorders and their comorbidities (excluding psychosis).

OBJECTIVE

The main aim of the MIND-SET project is to determine the shared and specific mechanisms of neurodevelopmental and stress-related psychiatric disorders at different observational levels.

METHODS

This is an observational cross-sectional study. Data from different observational levels as defined in the Research Domain Criteria (genetics, physiology, neuropsychology, system-level neuroimaging, behavior, self-report, and experimental neurocognitive paradigms) are collected over four time points. Included are adult (aged ≥18 years), nonpsychotic, psychiatric patients with a clinical diagnosis of a stress-related disorder (mood disorder, anxiety disorder, or substance use disorder) or a neurodevelopmental disorder (autism spectrum disorder or attention-deficit/hyperactivity disorder). Individuals with no current or past psychiatric diagnosis are included as neurotypical controls. Data collection started in June 2016 with the aim to include a total of 650 patients and 150 neurotypical controls by 2021. The data collection procedure includes online questionnaires and three subsequent sessions with (1) standardized clinical examination, physical examination, and blood sampling; (2) psychological constructs, neuropsychological tests, and biological marker sampling; and (3) neuroimaging measures.

RESULTS

We aim to include a total of 650 patients and 150 neurotypical control participants in the time period between 2016 and 2022. In October 2021, we are at 95% of our target.

CONCLUSIONS

The MIND-SET study enables us to investigate the mechanistic underpinnings of nonpsychotic psychiatric disorders transdiagnostically. We will identify both shared and disorder-specific markers at different observational levels that can be used as targets for future diagnostic and treatment approaches.

Transdiagnostic symptom subtypes across autism spectrum disorders and attention deficit hyperactivity disorder: validated by measures of neurocognition and structural connectivity

BACKGROUNDS

Autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD) are neurodevelopmental disorders that exhibit within-disorder heterogeneity and cross-disorder phenotypic overlap, thus suggesting that the current disease categories may not fully represent the etiologic essence of the disorders, especially for highly comorbid neurodevelopmental disorders. In this study, we explored the subtypes of a combined sample of ASD and ADHD by integrating measurements of behavior, cognition and brain imaging.

METHODS

A total of 164 participants, including 65 with ASD, 47 with ADHD, and 52 controls, were recruited. Unsupervised machine learning with an agglomerative hierarchical clustering algorithm was used to identify transdiagnostic symptom clusters. Neurocognition and brain structural connectivity measurements were used to assess symptom clusters. Mediation analysis was used to explore the relationship between transdiagnostic symptoms, neurocognition and brain structural connectivity.

RESULTS

We identified three symptom clusters that did not fall within the diagnostic boundaries of DSM. External measurements from neurocognition and neuroimaging domains supported distinct profiles, including fine motor function, verbal fluency, and structural connectivity in the corpus callosum between these symptom clusters, highlighting possible biomarkers for ASD and ADHD. Additionally, fine motor function was shown to mediate the relationship between the corpus callosum and perseveration symptoms.

CONCLUSIONS

In this transdiagnostic study on ASD and ADHD, we identified three subtypes showing meaningful associations between symptoms, neurocognition and brain white matter structural connectivity. The fine motor function and structural connectivity of corpus callosum might be used as biomarkers for neurodevelopmental disorders with social skill symptoms. The results of this study highlighted the importance of precise phenotyping and further supported the effects of fine motor intervention on ASD and ADHD.

Altered voxel-mirrored homotopic connectivity in right temporal lobe epilepsy as measured using resting-state fMRI and support vector machine analyses

BACKGROUND

Prior reports revealed abnormalities in voxel-mirrored homotopic connectivity (VMHC) when analyzing neuroimaging data from patients with various psychiatric conditions, including temporal lobe epilepsy (TLE). Whether these VHMC changes can be leveraged to aid in the diagnosis of right TLE (rTLE), however, remains to be established. This study was thus developed to examine abnormal VMHC findings associated with rTLE to determine whether these changes can be used to guide rTLE diagnosis.

METHODS

The resultant imaging data of resting-state functional MRI (rs-fMRI) analyses of 59 patients with rTLE and 60 normal control individuals were analyzed using VMHC and support vector machine (SVM) approaches.

RESULTS

Relative to normal controls, patients with rTLE were found to exhibit decreased VMHC values in the bilateral superior and the middle temporal pole (STP and MTP), the bilateral middle and inferior temporal gyri (MTG and ITG), and the bilateral orbital portion of the inferior frontal gyrus (OrbIFG). These patients further exhibited increases in VMHC values in the bilateral precentral gyrus (PreCG), the postcentral gyrus (PoCG), and the supplemental motor area (SMA). The ROC curve of MTG VMHC values showed a great diagnostic efficacy in the diagnosis of rTLE with AUCs, sensitivity, specificity, and optimum cutoff values of 0.819, 0.831, 0.717, and 0.465. These findings highlight the value of the right middle temporal gyrus (rMTG) when differentiating between rTLE and control individuals, with a corresponding SVM analysis yielding respective accuracy, sensitivity, and specificity values of 70.59% (84/119), 78.33% (47/60), and 69.49% (41/59).

CONCLUSION

In summary, patients with rTLE exhibit various forms of abnormal functional connectivity, and SVM analyses support the potential value of abnormal VMHC values as a neuroimaging biomarker that can aid in the diagnosis of this condition.

Comorbidity of Attention-Deficit Hyperactivity Disorder and Autism Spectrum Disorders: Current Status and Promising Directions

High rates of co-occurring Attention-Deficit Hyperactivity Disorder (ADHD) and Autism Spectrum Disorders (ASD) suggest common causal pathways, which await elucidation. What is well-established, however, is the negative impact of comorbid ADHD and ASD on outcomes for everyday living, particularly in social interaction and communication and on broader psychopathology. Neurocognitive approaches suggest correlates of comorbidity are rooted in functional connectivity networks associated with executive control. There is support for familial origins, with molecular-genetic studies suggesting a causal role of pleiotropic genes. Further investigation is needed to elucidate fully how genetic risk for ADHD and ASD affects neurodevelopment and to identify structural and functional neural correlates and their behavioral sequelae. Identification of intermediate phenotypes is necessary to advance understanding, which requires studies that include the full spectrum of ASD and ADHD symptom severity, use longitudinal designs and multivariate methods to probe broad constructs, such as executive and social function, and consider other sources of heterogeneity, such as age, sex, and other psychopathology. Randomized efficacy trials targeting comorbid symptomatology are needed to mitigate negative developmental outcomes.

Characterizing autistic traits in treatment-seeking young adults with substance use disorders

BACKGROUND AND OBJECTIVES

Recent work highlights an increase in the overlap of autism spectrum disorder (ASD) and substance use disorder (SUD). Little is known about the presence of ASD symptoms in SUD-treatment-seeking populations.

METHODS

The informant-rated Social Responsiveness Scale-2 (SRS-2) was completed at intake to an outpatient SUD clinic for youth aged 16-26 (N = 69). Comparisons were made between those with elevated SRS-2 scores on demographic, psychiatric, and substance use variables.

RESULTS

Parents of sixty-nine patients with SUD completed the SRS-2. Fourteen (20%) (average age 18.7 ± 2.5) had elevated SRS-2 Total T-scores (≥66) and 55 (average age 18.1 ± 2.8) had non-clinical SRS-2 Total T-scores. There were few differences between groups; however, those with elevated SRS-2 Total T-scores were more likely to have a stimulant use disorder (odds ratio [OR] = 7.59, 95% confidence interval [CI] = 0.77, 101.88; p = 0.05) or an opioid use disorder (OR = 5.02, 95% CI = 0.59, 43.27; p = 0.08) than patients with normal SRS-2 Total T-scores as well as alcohol use in the week prior to intake.

DISCUSSION AND CONCLUSIONS

A significant proportion of treatment-seeking SUD outpatients suffer from clinically elevated autistic traits. These findings highlight the importance of assessing for autistic traits in SUD treatment settings yet additional research is needed to determine if these findings are specific to the presence of ASD or secondary to sequelae of specific SUD presentations.

SCIENTIFIC SIGNIFICANCE

This study is, to our knowledge, the first to have examined the prevalence, morbidity, or clinical characteristics, associated with ASD symptoms in a SUD-specific population.

Testing the Stability and Validity of an Executive Dysfunction Classification Using Task-Based Assessment in Children and Adolescents

OBJECTIVE

It is unclear if pediatric executive dysfunction assessed only with cognitive tasks predicts clinically relevant outcomes independently of psychiatric diagnoses. This study tested the stability and validity of a task-based classification of executive function.

METHOD

A total of 2,207 individuals (6-17 years old) from the Brazilian High-Risk Cohort Study participated in this study (1,930 at baseline, 1,532 at follow-up). Executive function was measured using tests of working memory and inhibitory control. Dichotomized age- and sex-standardized performances were used as input in latent class analysis and receiver operating curves to create an executive dysfunction classification (EDC). The study tested EDC's stability over time, association with symptoms, functional impairment, a polymorphism in the CADM2 gene, polygenic risk scores (PRS), and brain structure. Analyses covaried for age, sex, social class, IQ, and psychiatric diagnoses.

RESULTS

EDC at baseline predicted itself at follow-up (odds ratio [OR] = 5.11; 95% CI 3.41-7.64). Participants in the EDC reported symptoms spanning several domains of psychopathology and exhibited impairment in multiple settings, including more adverse school events (OR = 2.530; 95% CI 1.838-3.483). Children in the EDC presented higher attention-deficit/hyperactivity disorder and lower educational attainment PRS at baseline; higher schizophrenia PRS at follow-up; and lower chances of presenting a polymorphism in a gene previously linked to high performance in executive function (CADM2 gene). They also exhibited smaller intracranial volumes and smaller bilateral cortical surface areas in several brain regions.

CONCLUSION

Task-based executive dysfunction is associated with several validators, independently of psychiatric diagnoses and intelligence. Further refinement of task-based assessments might generate clinically useful tools.

A national harmonised data collection network for neurodevelopmental disorders: A transdiagnostic assessment protocol for neurodevelopment, mental health, functioning and well-being

Background

Children with neurodevelopmental disorders share common phenotypes, support needs and comorbidities. Such overlap suggests the value of transdiagnostic assessment pathways that contribute to knowledge about research and clinical needs of these children and their families. Despite this, large transdiagnostic data collection networks for neurodevelopmental disorders are not well developed. This paper describes the development of a nationally supported transdiagnostic clinical and research assessment protocol across Australia. The vision is to establish a harmonised network for data collection and collaboration that promotes transdiagnostic clinical practice and research.

Methods

Clinicians, researchers and community groups across Australia were consulted using surveys and national summits to identify assessment instruments and unmet needs. A national research committee was formed and, using a consensus approach, selected assessment instruments according to pre-determined criteria to form a harmonised transdiagnostic assessment protocol.

Results

Identified assessment instruments were clustered into domains of transdiagnostic assessment needs, which included child functioning/quality of life, child mental health, caregiver mental health, and family background information. From this, the research committee identified a core set of nine measures and an extended set of 14 measures that capture these domains with potential for further modifications as recommended by clinicians, researchers and community members.

Conclusion

The protocol proposed here was established through a strong partnership between clinicians, researchers and the community. It will enable (i) consensus driven transdiagnostic clinical assessments for children with neurodevelopmental disorders, and (ii) research studies that will inform large transdiagnostic datasets across neurodevelopmental disorders and that can be used to inform research and policy beyond narrow diagnostic groups. The long-term vision is to use this framework to facilitate collaboration across clinics to enable large-scale data collection and research. Ultimately, the transdiagnostic assessment data can be used to inform practice and improve the lives of children with neurodevelopmental disorders and their families.

Visual attention and inhibitory control in children, teenagers and adults with autism without intellectual disability: results of oculomotor tasks from a 2-year longitudinal follow-up study (InFoR)

BACKGROUND

Inhibitory control and attention processing atypicalities are implicated in various diseases, including autism spectrum disorders (ASD). These cognitive functions can be tested by using visually guided saccade-based paradigms in children, adolescents and adults to determine the time course of such disorders.

METHODS

In this study, using Gap, Step, Overlap and Antisaccade tasks, we analyzed the oculomotor behavior of 82 children, teenagers and adults with high functioning ASD and their peer typically developing (TD) controls in a two-year follow-up study under the auspices of the InFoR-Autism project. Analysis of correlations between oculomotors task measurements and diagnostic assessment of attentional (ADHD-RS and ADHD comorbidity indices) and executive functioning (BRIEF scales) were conducted in order to evaluate their relationship with the oculomotor performance of participants with ASD.

RESULTS

As indicated by the presence of a Gap and Overlap effects in all age groups, the oculomotor performances of ASD participants showed a preserved capability in overt attention switching. In contrast, the difference in performances of ASD participants in the Antisaccade task, compared to their TD peers, indicated an atypical development of inhibition and executive functions. From correlation analysis between our oculomotor data and ADHD comorbidity index, and scores of attention and executive function difficulties, our findings support the hypothesis that a specific dysfunction of inhibition skills occurs in ASD participants that is independent of the presence of ADHD comorbidity.

LIMITATIONS

These include the relatively small sample size of the ASD group over the study's two-year period, the absence of an ADHD-only control group and the evaluation of a TD control group solely at the study's inception.

CONCLUSIONS

Children and teenagers with ASD have greater difficulty in attention switching and inhibiting prepotent stimuli. Adults with ASD can overcome these difficulties, but, similar to teenagers and children with ASD, they make more erroneous and anticipatory saccades and display a greater trial-to-trial variability in all oculomotor tasks compared to their peers. Our results are indicative of a developmental delay in the maturation of executive and attentional functioning in ASD and of a specific impairment in inhibitory control.

A Unified Framework for Inattention Estimation From Resting State Phase Synchrony Using Machine Learning

Inattention is one of the most significant clinical symptoms for evaluating attention deficit hyperactivity disorder (ADHD). Previous inattention estimations were performed using clinical scales. Recently, predictive models for inattention have been established for brain-behavior estimation using neuroimaging features. However, the performance of inattention estimation could be improved for conventional brain-behavior models with additional feature selection, machine learning algorithms, and validation procedures. This paper aimed to propose a unified framework for inattention estimation from resting state fMRI to improve the classical brain-behavior models. Phase synchrony was derived as raw features, which were selected with minimum-redundancy maximum-relevancy (mRMR) method. Six machine learning algorithms were applied as regression methods. 100 runs of 10-fold cross-validations were performed on the ADHD-200 datasets. The relevance vector machines (RVMs) based on the mRMR features for the brain-behavior models significantly improve the performance of inattention estimation. The mRMR-RVM models could achieve a total accuracy of 0.53. Furthermore, predictive patterns for inattention were discovered by the mRMR technique. We found that the bilateral subcortical-cerebellum networks exhibited the most predictive phase synchrony patterns for inattention. Together, an optimized strategy named mRMR-RVM for brain-behavior models was found for inattention estimation. The predictive patterns might help better understand the phase synchrony mechanisms for inattention.

Neural correlates of schema-dependent episodic memory and association with behavioral flexibility in autism spectrum disorders and typical development

BACKGROUND

Conceptual knowledge frameworks termed schemas facilitate memory formation and are posited to support flexible behavior. In adults, the medial temporal lobe (MTL) and medial prefrontal cortex (mPFC) trade-off in supporting schema-based memory formation, such that encoding of subsequently remembered schema-congruent information relies on mPFC, whereas schema-incongruent information relies on MTL. Whether this is true in the immature brain and relates to behavioral flexibility is unknown. In this preliminary investigation, we aimed to replicate the adult findings in typically developing (TD) children and to investigate the relevance to behavioral flexibility by examining a disorder with pathognomonic behavioral rigidity, autism spectrum disorder (ASD).

METHODS

Children completed an associative subsequent memory paradigm, encoding object-scene pairs in an MRI scanner and subsequently completing a recognition test outside the scanner after a delay. Recognition performance was back sorted to construct remembered vs forgotten contrasts. One-way ANOVAS were conducted in MTL and mPFC masks for schema-congruency, followed by congruency by flexibility scores. Exploratory analyses were then conducted within the whole brain.

RESULTS

As reported in adults, episodic memory was strongest for schema-congruent object-scene pairs, followed by intermediate pairs, and lowest for schema-incongruent pairs in both TD and ASD groups. However, the trade-off between mPFC and MTL in TD children differed from adult reports such that mPFC supported memory for intermediate schema-congruency and left anterior MTL supported memory for schema-congruent pairs. In ASD, mPFC engagement interacted with flexibility such that activation supporting memory for intermediate schema-congruency varied with parent-reported flexibility and was higher in those with more flexible behavior. A similar interaction was also observed in both the left dorsolateral and rostrolateral PFC in whole-brain analysis.

CONCLUSION

Our findings provide the first preliminary evidence for the association of schema-based episodic memory formation and behavioral flexibility, an executive function impaired in multiple developmental disorders. Upon replication, this line of research holds promise for memory-based interventions addressing executive problems of behavioral rigidity.

The Effect of Comorbid Attention-Deficit/Hyperactivity Disorder Symptoms on Face Memory in Children with Autism Spectrum Disorder: Insights from Transdiagnostic Profiles

Face memory impairments are common but heterogeneous in autism spectrum disorder (ASD), which may be influenced by co-occurrence with attention-deficit/hyperactivity disorder (ADHD). Here, we aimed to investigate the phenotype change of face memory in children with ASD comorbid ADHD symptoms, and discuss the potential role of executive function (EF). Ninety-eight children were analyzed in the present study, including ASD- (ASD-only, n = 24), ADHD (n = 23), ASD+ (with ADHD symptoms, n = 23) and neurotypical controls (NTC, n = 28). All participants completed two tests: face encoding and retrieving task and Wisconsin Card Sorting Test (WCST) for measuring face memory and EF, respectively. Results revealed that: compared with the NTC group, children with ASD- exhibited lower accuracy in both face encoding and retrieving, and participants with ASD+ showed lower accuracy only in the retrieving, whereas no differences were found among participants with ADHD. Moreover, in the ASD+ group, face encoding performance was correlated with response perseverative errors (RPE) and failure to maintain sets (FMS) of WCST; significantly, there were no group differences between ASD+ and NTC in these two indices. The transdiagnostic profiles indicated that comorbid ADHD symptoms could modulate the face encoding deficiency of ASD, which may be partially compensated by EF. Shared and distinct intervention strategies to improve social cognition are recommended for children undergoing treatment for each condition.