Conduction velocity, G-ratio, and extracellular water as microstructural characteristics of autism spectrum disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a new approach to calculating axonal conduction velocity termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel formulation for calculating aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Autistic Individuals Do Not Alter Visual Processing Strategy During Encoding Versus Recognition of Faces: A Hidden Markov Modeling Approach

PURPOSE

Visual face recognition-the ability to encode, discriminate, and recognize the faces of others-is fundamentally supported by eye movements and is a common source of difficulty for autistic individuals. We aimed to evaluate how visual processing strategies (i.e., eye movement patterns) directly support encoding and recognition of faces in autistic and neurotypical (NT) individuals.

METHODS

We used a hidden Markov modeling approach to evaluate the spatiotemporal dynamics of eye movements in autistic (n = 15) and neurotypical (NT) adolescents (n = 17) during a face identity recognition task.

RESULTS

We discovered distinct eye movement patterns among all participants, which included a focused and exploratory strategy. When evaluating change in visual processing strategy across encoding and recognition phases, autistic individuals did not shift their eye movement patterns like their NT peers, who shifted to a more exploratory visual processing strategy during recognition.

CONCLUSION

These findings suggest that autistic individuals do not modulate their visual processing strategy across encoding and recognition of faces, which may be an indicator of less efficient face processing.

Conduction Velocity, G-ratio, and Extracellular Water as Microstructural Characteristics of Autism Spectrum Disorder

The neuronal differences contributing to the etiology of autism spectrum disorder (ASD) are still not well defined. Previous studies have suggested that myelin and axons are disrupted during development in ASD. By combining structural and diffusion MRI techniques, myelin and axons can be assessed using extracellular water, aggregate g-ratio, and a novel metric termed aggregate conduction velocity, which is related to the capacity of the axon to carry information. In this study, several innovative cellular microstructural methods, as measured from magnetic resonance imaging (MRI), are combined to characterize differences between ASD and typically developing adolescent participants in a large cohort. We first examine the relationship between each metric, including microstructural measurements of axonal and intracellular diffusion and the T1w/T2w ratio. We then demonstrate the sensitivity of these metrics by characterizing differences between ASD and neurotypical participants, finding widespread increases in extracellular water in the cortex and decreases in aggregate g-ratio and aggregate conduction velocity throughout the cortex, subcortex, and white matter skeleton. We finally provide evidence that these microstructural differences are associated with higher scores on the Social Communication Questionnaire (SCQ) a commonly used diagnostic tool to assess ASD. This study is the first to reveal that ASD involves MRI-measurable in vivo differences of myelin and axonal development with implications for neuronal and behavioral function. We also introduce a novel neuroimaging metric, aggregate conduction velocity, that is highly sensitive to these changes. We conclude that ASD may be characterized by otherwise intact structural connectivity but that functional connectivity may be attenuated by network properties affecting neural transmission speed. This effect may explain the putative reliance on local connectivity in contrast to more distal connectivity observed in ASD.

Social Anhedonia Accounts for Greater Variance in Internalizing Symptoms than Autism Symptoms in Autistic and Non-Autistic Youth

PURPOSE

Social anhedonia is a transdiagnostic trait that reflects reduced pleasure from social interaction. It has historically been associated with autism, however, very few studies have directly examined behavioral symptoms of social anhedonia in autistic youth. We investigated rates of social anhedonia in autistic compared to non-autistic youth and the relative contributions of autism and social anhedonia symptoms to co-occurring mental health.

METHODS

Participants were 290 youth (Mage=13.75, Nautistic=155) ranging in age from 8 to 18. Youth completed a cognitive assessment and a diagnostic interview. Their caregiver completed questionnaires regarding symptoms of autism and co-occurring psychiatric conditions.

RESULTS

Autistic youth were more likely to meet criteria for social anhedonia than non-autistic youth. There was a significant positive relationship between age and social anhedonia symptom severity, but there was no association between sex and social anhedonia. Dominance analysis revealed that social anhedonia symptom severity had the strongest association with symptoms of depression and social anxiety, while symptoms of ADHD, generalized anxiety, and separation anxiety were most strongly associated with autism symptom severity.

CONCLUSION

This was the first study to tease out the relative importance of social anhedonia and autism symptoms in understanding psychiatric symptoms in autistic youth. Findings revealed higher rates of social anhedonia in autistic youth. Our results indicate that social anhedonia is an important transdiagnostic trait that plays a unique role in understanding co-occurring depression and social anxiety in autistic youth. Future research should utilize longitudinal data to test the transactional relationships between social anhedonia and internalizing symptoms over time.

Support vector machine prediction of individual Autism Diagnostic Observation Schedule (ADOS) scores based on neural responses during live eye-to-eye contact

Social difficulties during interactions with others are central to autism spectrum disorder (ASD). Understanding the links between these social difficulties and their underlying neural processes is a primary aim focused on improved diagnosis and treatment. In keeping with this goal, we have developed a multivariate classification method based on neural data acquired by functional near infrared spectroscopy, fNIRS, during live eye-to-eye contact with adults who were either typically developed (TD) or individuals with ASD. The ASD diagnosis was based on the gold-standard Autism Diagnostic Observation Schedule (ADOS) which also provides an index of symptom severity. Using a nested cross-validation method, a support vector machine (SVM) was trained to discriminate between ASD and TD groups based on the neural responses during eye-to-eye contact. ADOS scores were not applied in the classification training. To test the hypothesis that SVM identifies neural activity patterns related to one of the neural mechanisms underlying the behavioral symptoms of ASD, we determined the correlation coefficient between the SVM scores and the individual ADOS scores. Consistent with the hypothesis, the correlation between observed and predicted ADOS scores was 0.72 (p < 0.002). Findings suggest that multivariate classification methods combined with the live interaction paradigm of eye-to-eye contact provide a promising approach to link neural processes and social difficulties in individuals with ASD.

Brief Report: Exploratory Evaluation of Clinical Features Associated with Suicidal Ideation in Youth with Autism Spectrum Disorder

There has been a heightened awareness of an increased risk of suicidality among individuals with autism spectrum disorder (ASD) due to high rates of suicidal ideation (SI) in this population (11-66%). The current study investigated the rate of parent-endorsed SI and associated clinical features in 48 youths with ASD (Age; M: 12.97 years, SD: 2.33). SI was endorsed in 18.75% of participants. Youth with SI exhibited significantly higher levels of affective problems, externalizing problems, feelings of humiliation and rejection, and symptoms related to perfectionism. Results indicate that co-occurring mental health problems are associated with suicidal ideation and provide relevant targets for psychotherapeutic intervention. This preliminary study in a modest sample suggests the value of further research in larger samples to replicate and generalize these findings.

Frontal EEG alpha asymmetry in youth with autism: Sex differences and social-emotional correlates

In youth broadly, EEG frontal alpha asymmetry (FAA) associates with affective style and vulnerability to psychopathology, with relatively stronger right activity predicting risk for internalizing and externalizing behaviors. In autistic youth, FAA has been related to ASD diagnostic features and to internalizing symptoms. Among our large, rigorously characterized, sex-balanced participant group, we attempted to replicate findings suggestive of altered FAA in youth with an ASD diagnosis, examining group differences and impact of sex assigned at birth. Second, we examined relations between FAA and behavioral variables (ASD features, internalizing, and externalizing) within autistic youth, examining effects by sex. Third, we explored whether the relation between FAA, autism features, and mental health was informed by maternal depression history. In our sample, FAA did not differ by diagnosis, age, or sex. However, youth with ASD had lower total frontal alpha power than youth without ASD. For autistic females, FAA and bilateral frontal alpha power correlated with social communication features, but not with internalizing or externalizing symptoms. For autistic males, EEG markers correlated with social communication features, and with externalizing behaviors. Exploratory analyses by sex revealed further associations between youth FAA, behavioral indices, and maternal depression history. In summary, findings suggest that individual differences in FAA may correspond to social-emotional and mental health behaviors, with different patterns of association for females and males with ASD. Longitudinal consideration of individual differences across levels of analysis (e.g., biomarkers, family factors, and environmental influences) will be essential to parsing out models of risk and resilience among autistic youth.

The Selective Social Attention task in children with autism spectrum disorder: Results from the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) feasibility study

The Selective Social Attention (SSA) task is a brief eye-tracking task involving experimental conditions varying along socio-communicative axes. Traditionally the SSA has been used to probe socially-specific attentional patterns in infants and toddlers who develop autism spectrum disorder (ASD). This current work extends these findings to preschool and school-age children. Children 4- to 12-years-old with ASD (N = 23) and a typically-developing comparison group (TD; N = 25) completed the SSA task as well as standardized clinical assessments. Linear mixed models examined group and condition effects on two outcome variables: percent of time spent looking at the scene relative to scene presentation time (%Valid), and percent of time looking at the face relative to time spent looking at the scene (%Face). Age and IQ were included as covariates. Outcome variables' relationships to clinical data were assessed via correlation analysis. The ASD group, compared to the TD group, looked less at the scene and focused less on the actress' face during the most socially-engaging experimental conditions. Additionally, within the ASD group, %Face negatively correlated with SRS total T-scores with a particularly strong negative correlation with the Autistic Mannerism subscale T-score. These results highlight the extensibility of the SSA to older children with ASD, including replication of between-group differences previously seen in infants and toddlers, as well as its ability to capture meaningful clinical variation within the autism spectrum across a wide developmental span inclusive of preschool and school-aged children. The properties suggest that the SSA may have broad potential as a biomarker for ASD.

Development of peak alpha frequency reflects a distinct trajectory of neural maturation in autistic children

Electroencephalographic peak alpha frequency (PAF) is a marker of neural maturation that increases with age throughout childhood. Distinct maturation of PAF is observed in children with autism spectrum disorder such that PAF does not increase with age and is instead positively associated with cognitive ability. The current study clarifies and extends previous findings by characterizing the effects of age and cognitive ability on PAF between diagnostic groups in a sample of children and adolescents with and without autism spectrum disorder. Resting EEG data and behavioral measures were collected from 45 autistic children and 34 neurotypical controls aged 8 to 18 years. Utilizing generalized additive models to account for nonlinear relations, we examined differences in the joint effect of age and nonverbal IQ by diagnosis as well as bivariate relations between age, nonverbal IQ, and PAF across diagnostic groups. Age was positively associated with PAF among neurotypical children but not among autistic children. In contrast, nonverbal IQ but not age was positively associated with PAF among autistic children. Models accounting for nonlinear relations revealed different developmental trajectories as a function of age and cognitive ability based on diagnostic status. Results align with prior evidence indicating that typical age-related increases in PAF are absent in autistic children and that PAF instead increases with cognitive ability in these children. Findings suggest the potential of PAF to index distinct trajectories of neural maturation in autistic children.

Investigating the Face Inversion Effect in Autism Across Behavioral and Neural Measures of Face Processing: A Systematic Review and Bayesian Meta-Analysis

Importance

Face processing is foundational to human social cognition, is central to the hallmark features of autism spectrum disorder (ASD), and shapes neural systems and social behavior. Highly efficient and specialized, the face processing system is sensitive to inversion, demonstrated by reduced accuracy in recognition and altered neural response to inverted faces. Understanding at which mechanistic level the autistic face processing system may be particularly different, as measured by the face inversion effect, will improve overall understanding of brain functioning in autism.

Objective

To synthesize data from the extant literature to determine differences of the face processing system in ASD, as measured by the face inversion effect, across multiple mechanistic levels.

Data Sources

Systematic searches were conducted in the MEDLINE, Embase, Web of Science, and PubMed databases from inception to August 11, 2022.

Study Selection

Original research that reported performance-based measures of face recognition to upright and inverted faces in ASD and neurotypical samples were included for quantitative synthesis. All studies were screened by at least 2 reviewers.

Data Extraction and Synthesis

This systematic review and meta-analysis was conducted according to the 2020 Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) reporting guideline. Multiple effect sizes were extracted from studies to maximize information gain and statistical precision and used a random-effects, multilevel modeling framework to account for statistical dependencies within study samples.

Main Outcomes and Measures

Effect sizes were calculated as a standardized mean change score between ASD and neurotypical samples (ie, Hedges g). The primary outcome measure was performance difference between upright and inverted faces during face recognition tasks. Measurement modality, psychological construct, recognition demand, sample age, sample sex distribution, and study quality assessment scores were assessed as moderators.

Results

Of 1768 screened articles, 122 effect sizes from 38 empirical articles representing data from 1764 individual participants (899 ASD individuals and 865 neurotypical individuals) were included in the meta-analysis. Overall, face recognition performance differences between upright and inverted faces were reduced in autistic individuals compared with neurotypical individuals (g = -0.41; SE = 0.11; 95% credible interval [CrI], -0.63 to -0.18). However, there was considerable heterogeneity among effect sizes, which were explored with moderator analysis. The attenuated face inversion effect in autistic individuals was more prominent in emotion compared with identity recognition (b = 0.46; SE = 0.26; 95% CrI, -0.08 to 0.95) and in behavioral compared with electrophysiological measures (b = 0.23; SE = 0.24; 95% CrI, -0.25 to 0.70).

Conclusions and Relevance

This study found that on average, face recognition in autism is less impacted by inversion. These findings suggest less specialization or expertise of the face processing system in autism, particularly in recognizing emotion from faces as measured in behavioral paradigms.

Systematic review: emotion dysregulation and challenging behavior interventions for children and adolescents on the autism spectrum with graded key evidence-based strategy recommendations

Challenging behavior, such as aggression, is highly prevalent in children and adolescents on the autism spectrum and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behavior measures, while few included emotion dysregulation measures. This review highlights the importance of teaching emotion regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

Modeling idiopathic autism in forebrain organoids reveals an imbalance of excitatory cortical neuron subtypes during early neurogenesis

Idiopathic autism spectrum disorder (ASD) is highly heterogeneous, and it remains unclear how convergent biological processes in affected individuals may give rise to symptoms. Here, using cortical organoids and single-cell transcriptomics, we modeled alterations in the forebrain development between boys with idiopathic ASD and their unaffected fathers in 13 families. Transcriptomic changes suggest that ASD pathogenesis in macrocephalic and normocephalic probands involves an opposite disruption of the balance between excitatory neurons of the dorsal cortical plate and other lineages such as early-generated neurons from the putative preplate. The imbalance stemmed from divergent expression of transcription factors driving cell fate during early cortical development. While we did not find genomic variants in probands that explained the observed transcriptomic alterations, a significant overlap between altered transcripts and reported ASD risk genes affected by rare variants suggests a degree of gene convergence between rare forms of ASD and the developmental transcriptome in idiopathic ASD.

Distinct Symptom Network Structure and Shared Central Social Communication Symptomatology in Autism and Schizophrenia: A Bayesian Network Analysis

Autism (ASD) and schizophrenia spectrum disorders (SCZ) are neurodevelopmental conditions with overlapping and interrelated symptoms. A network analysis approach that represents clinical conditions as a set of "nodes" (symptoms) connected by "edges" (relations among symptoms) was used to compare symptom organization in the two conditions. Gaussian graphical models were estimated using Bayesian methods to model separate symptom networks for adults with confirmed ASD or SCZ diagnoses. Though overall symptom organization differed by diagnostic group, both symptom networks demonstrated high centrality of social communication difficulties. Autism-relevant restricted and repetitive behaviors and schizophrenia-related cognitive-perceptual symptoms were uniquely central to the ASD and SCZ networks, respectively. Results offer recommendations to improve differential diagnosis and highlight potential treatment targets in ASD and SCZ.

Attention Allocation During Exploration of Visual Arrays in ASD: Results from the ABC-CT Feasibility Study

Visual exploration paradigms involving object arrays have been used to examine salience of social stimuli such as faces in ASD. Recent work suggests performance on these paradigms may associate with clinical features of ASD. We evaluate metrics from a visual exploration paradigm in 4-to-11-year-old children with ASD (n = 23; 18 males) and typical development (TD; n = 23; 13 males). Presented with arrays containing faces and nonsocial stimuli, children with ASD looked less at (p = 0.002) and showed fewer fixations to (p = 0.022) faces than TD children, and spent less time looking at each object on average (p = 0.004). Attention to the screen and faces correlated positively with social and cognitive skills in the ASD group (ps < .05). This work furthers our understanding of objective measures of visual exploration in ASD and its potential for quantifying features of ASD.

A Digital Mental Health App Incorporating Wearable Biosensing for Teachers of Children on the Autism Spectrum to Support Emotion Regulation: Protocol for a Pilot Randomized Controlled Trial

BACKGROUND

As much as 80% of children on the autism spectrum exhibit challenging behaviors (ie, behaviors dangerous to the self or others, behaviors that interfere with learning and development, and behaviors that interfere with socialization) that can have a devastating impact on personal and family well-being, contribute to teacher burnout, and even require hospitalization. Evidence-based practices to reduce these behaviors emphasize identifying triggers (events or antecedents that lead to challenging behaviors); however, parents and teachers often report that challenging behaviors surface with little warning. Exciting recent advances in biometric sensing and mobile computing technology allow the measurement of momentary emotion dysregulation using physiological indexes.

OBJECTIVE

We present the framework and protocol for a pilot trial that will test a mobile digital mental health app, the KeepCalm app. School-based approaches to managing challenging behaviors in children on the autism spectrum are limited by 3 key factors: children on the autism spectrum often have difficulties in communicating their emotions; it is challenging to implement evidence-based, personalized strategies for individual children in group settings; and it is difficult for teachers to track which strategies are successful for each child. KeepCalm aims to address those barriers by communicating children's stress to their teachers using physiological signaling (emotion dysregulation detection), supporting the implementation of emotion regulation strategies via smartphone pop-up notifications of top strategies for each child according to their behavior (emotion regulation strategy implementation), and easing the task of tracking outcomes by providing the child's educational team with a tool to track the most effective emotion regulation strategies for that child based on physiological stress reduction data (emotion regulation strategy evaluation).

METHODS

We will test KeepCalm with 20 educational teams of students on the autism spectrum with challenging behaviors (no exclusion based on IQ or speaking ability) in a pilot randomized waitlist-controlled field trial over a 3-month period. We will examine the usability, acceptability, feasibility, and appropriateness of KeepCalm as primary outcomes. Secondary preliminary efficacy outcomes include clinical decision support success, false positives or false negatives of stress alerts, and the reduction of challenging behaviors and emotion dysregulation. We will also examine technical outcomes, including the number of artifacts and the proportion of time children are engaged in high physical movement based on accelerometry data; test the feasibility of our recruitment strategies; and test the response rate and sensitivity to change of our measures, in preparation for a future fully powered large-scale randomized controlled trial.

RESULTS

The pilot trial will begin by September 2023.

CONCLUSIONS

Results will provide key data about important aspects of implementing KeepCalm in preschools and elementary schools and will provide preliminary data about its efficacy to reduce challenging behaviors and support emotion regulation in children on the autism spectrum.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05277194; https://www.clinicaltrials.gov/ct2/show/NCT05277194.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

PRR1-10.2196/45852.

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

Evaluation of clinical assessments of social abilities for use in autism clinical trials by the autism biomarkers consortium for clinical trials

Clinical trials in autism spectrum disorder (ASD) often rely on clinician rating scales and parent surveys to measure autism-related features and social behaviors. To aid in the selection of these assessments for future clinical trials, the Autism Biomarkers Consortium for Clinical Trials (ABC-CT) directly compared eight common instruments with respect to acquisition rates, sensitivity to group differences, equivalence across demographic sub-groups, convergent validity, and stability over a 6-week period. The sample included 280 children diagnosed with ASD (65 girls) and 119 neurotypical children (36 girls) aged from 6 to 11 years. Full scale IQ for ASD ranged from 60 to 150 and for neurotypical ranged from 86 to 150. Instruments measured clinician global assessment and autism-related behaviors, social communication abilities, adaptive function, and social withdrawal behavior. For each instrument, we examined only the scales that measured social or communication functioning. Data acquisition rates were at least 97.5% at T1 and 95.7% at T2. All scales distinguished diagnostic groups. Some scales significantly differed by participant and/or family demographic characteristics. Within the ASD group, most clinical instruments exhibited weak (≥ |0.1|) to moderate (≥ |0.4|) intercorrelations. Short-term stability was moderate (ICC: 0.5-0.75) to excellent (ICC: >0.9) within the ASD group. Variations in the degree of stability may inform viability for different contexts of use, such as identifying clinical subgroups for trials versus serving as a modifiable clinical outcome. All instruments were evaluated in terms of their advantages and potential concerns for use in clinical trials.

Concomitant medication use in children with autism spectrum disorder: Data from the Autism Biomarkers Consortium for Clinical Trials

LAY ABSTRACT

Children with autism spectrum disorder are prescribed a variety of medications that affect the central nervous system (psychotropic medications) to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity of the sample and prevent contamination of biomarkers or clinical endpoints. However, this choice may significantly diminish the clinical representativeness of the sample. In a recent multisite study designed to identify biomarkers and behavioral endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, thus providing a unique opportunity to examine characteristics of psychotropic medication use in a research cohort and to guide future decisions on medication-related inclusion criteria. The aims of the current analysis were (1) to quantify the frequency and type of psychotropic medications reported in school-age children enrolled in the ABC-CT and (2) to examine behavioral features of children with autism spectrum disorder based on medication classes. Of the 280 children with autism spectrum disorder in the cohort, 42.5% were taking psychotropic medications, with polypharmacy in half of these children. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Descriptive analysis showed that children taking antipsychotics displayed a trend toward greater overall impairment. Our findings suggest that exclusion of children taking concomitant psychotropic medications in trials could limit the clinical representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options.

Systematic Review: Emotion Dysregulation and Challenging Behavior Interventions for Children andAdolescents with Autism with Graded Key Evidence-Based Strategy Recommendations

Challenging behavior, such as aggression, is highly prevalent in children and adolescents with autism and can have a devastating impact. Previous reviews of challenging behavior interventions did not include interventions targeting emotion dysregulation, a common cause of challenging behavior. We reviewed emotion dysregulation and challenging behavior interventions for preschoolers to adolescents to determine which evidence-based strategies have the most empirical support for reducing/preventing emotion dysregulation/challenging behavior. We reviewed 95 studies, including 29 group and 66 single-case designs. We excluded non-behavioral/psychosocial interventions and those targeting internalizing symptoms only. We applied a coding system to identify discrete strategies based on autism practice guidelines with the addition of strategies common in childhood mental health disorders, and an evidence grading system. Strategies with the highest quality evidence (multiple randomized controlled trials with low bias risk) were Parent-Implemented Intervention, Emotion Regulation Training, Reinforcement, Visual Supports, Cognitive Behavioral/Instructional Strategies and Antecedent-Based Interventions. Regarding outcomes, most studies included challenging behaviors measures while few included emotion dysregulation measures. This review highlights the importance of teaching emotion-regulation skills explicitly, positively reinforcing replacement/alternative behaviors, using visuals and metacognition, addressing stressors proactively, and involving parents. It also calls for more rigorously-designed studies and for including emotion dysregulation as an outcome/mediator in future trials.

A functional model for studying common trends across trial time in eye tracking experiments

Eye tracking (ET) experiments commonly record the continuous trajectory of a subject's gaze on a two-dimensional screen throughout repeated presentations of stimuli (referred to as trials). Even though the continuous path of gaze is recorded during each trial, commonly derived outcomes for analysis collapse the data into simple summaries, such as looking times in regions of interest, latency to looking at stimuli, number of stimuli viewed, number of fixations or fixation length. In order to retain information in trial time, we utilize functional data analysis (FDA) for the first time in literature in the analysis of ET data. More specifically, novel functional outcomes for ET data, referred to as viewing profiles, are introduced that capture the common gazing trends across trial time which are lost in traditional data summaries. Mean and variation of the proposed functional outcomes across subjects are then modeled using functional principal components analysis. Applications to data from a visual exploration paradigm conducted by the Autism Biomarkers Consortium for Clinical Trials showcase the novel insights gained from the proposed FDA approach, including significant group differences between children diagnosed with autism and their typically developing peers in their consistency of looking at faces early on in trial time.

The Autism Biomarkers Consortium for Clinical Trials: Initial Evaluation of a Battery of Candidate EEG Biomarkers

OBJECTIVE

Numerous candidate EEG biomarkers have been put forward for use in clinical research on autism spectrum disorder (ASD), but biomarker development has been hindered by limited attention to the psychometric properties of derived variables, inconsistent results across small studies, and variable methodology. The authors evaluated the basic psychometric properties of a battery of EEG assays for their potential suitability as biomarkers in clinical trials.

METHODS

This was a large, multisite, naturalistic study in 6- to 11-year-old children who either had an ASD diagnosis (N=280) or were typically developing (N=119). The authors evaluated an EEG battery composed of well-studied assays of resting-state activity, face perception (faces task), biological motion perception, and visual evoked potentials (VEPs). Biomarker psychometrics were evaluated in terms of acquisition rates, construct performance, and 6-week stability. Preliminary evaluation of use was explored through group discrimination and phenotypic correlations.

RESULTS

Three assays (resting state, faces task, and VEP) show promise in terms of acquisition rates and construct performance. Six-week stability values in the ASD group were moderate (intraclass correlations ≥0.66) for the faces task latency of the P1 and N170, the VEP amplitude of N1 and P1, and resting alpha power. Group discrimination and phenotype correlations were primarily observed for the faces task P1 and N170.

CONCLUSIONS

In the context of a large-scale, rigorous evaluation of candidate EEG biomarkers for use in ASD clinical trials, neural response to faces emerged as a promising biomarker for continued evaluation. Resting-state activity and VEP yielded mixed results. The study's biological motion perception assay failed to display construct performance. The results provide information about EEG biomarker performance that is relevant for the next stage of biomarker development efforts focused on context of use.

Electrophysiological Studies of Reception of Facial Communication in Autism Spectrum Disorder and Schizophrenia

Autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SZ) are characterized by difficulty with social cognition and atypical reception of facial communication - a key area in the Research Domain Criteria framework. To identify areas of overlap and dissociation between ASD and SZ, we review studies of event-related potentials (ERP) to faces across ASD and SZ populations, focusing on ERPs implicated in social perception: P100, N170, N250, and P300. There were many inconsistent findings across studies; however, replication was strongest for delayed N170 latency in ASD and attenuated N170 amplitude in SZ. These results highlight the challenges of replicating research findings in heterogeneous clinical populations and the need for transdiagnostic research that continuously quantifies behavior and neural activity across neurodevelopmental disorders.

Linear discriminant analysis of phenotypic data for classifying autism spectrum disorder by diagnosis and sex

Autism Spectrum Disorder (ASD) is a developmental condition characterized by social and communication differences. Recent research suggests ASD affects 1-in-44 children in the United States. ASD is diagnosed more commonly in males, though it is unclear whether this diagnostic disparity is a result of a biological predisposition or limitations in diagnostic tools, or both. One hypothesis centers on the ‘female protective effect,’ which is the theory that females are biologically more resistant to the autism phenotype than males. In this examination, phenotypic data were acquired and combined from four leading research institutions and subjected to multivariate linear discriminant analysis. A linear discriminant model was trained on the training set and then deployed on the test set to predict group membership. Multivariate analyses of variance were performed to confirm the significance of the overall analysis, and individual analyses of variance were performed to confirm the significance of each of the resulting linear discriminant axes. Two discriminant dimensions were identified between the groups: a dimension separating groups by the diagnosis of ASD (LD1: 87% of variance explained); and a dimension reflective of a diagnosis-by-sex interaction (LD2: 11% of variance explained). The strongest discriminant coefficients for the first discriminant axis divided the sample in domains with known differences between ASD and comparison groups, such as social difficulties and restricted repetitive behavior. The discriminant coefficients for the second discriminant axis reveal a more nuanced disparity between boys with ASD and girls with ASD, including executive functioning and high-order behavioral domains as the dominant discriminators. These results indicate that phenotypic differences between males and females with and without ASD are identifiable using parent report measures, which could be utilized to provide additional specificity to the diagnosis of ASD in female patients, potentially leading to more targeted clinical strategies and therapeutic interventions. The study helps to isolate a phenotypic basis for future empirical work on the female protective effect using neuroimaging, EEG, and genomic methodologies.

Neural correlates of eye contact and social function in autism spectrum disorder

Reluctance to make eye contact during natural interactions is a central diagnostic criterion for autism spectrum disorder (ASD). However, the underlying neural correlates for eye contacts in ASD are unknown, and diagnostic biomarkers are active areas of investigation. Here, neuroimaging, eye-tracking, and pupillometry data were acquired simultaneously using two-person functional near-infrared spectroscopy (fNIRS) during live "in-person" eye-to-eye contact and eye-gaze at a video face for typically-developed (TD) and participants with ASD to identify the neural correlates of live eye-to-eye contact in both groups. Comparisons between ASD and TD showed decreased right dorsal-parietal activity and increased right ventral temporal-parietal activity for ASD during live eye-to-eye contact (p≤0.05, FDR-corrected) and reduced cross-brain coherence consistent with atypical neural systems for live eye contact. Hypoactivity of right dorsal-parietal regions during eye contact in ASD was further associated with gold standard measures of social performance by the correlation of neural responses and individual measures of: ADOS-2, Autism Diagnostic Observation Schedule, 2nd Edition (r = -0.76, -0.92 and -0.77); and SRS-2, Social Responsiveness Scale, Second Edition (r = -0.58). The findings indicate that as categorized social ability decreases, neural responses to real eye-contact in the right dorsal parietal region also decrease consistent with a neural correlate for social characteristics in ASD.

Predictability modulates neural response to eye contact in ASD

BACKGROUND

Deficits in establishing and maintaining eye-contact are early and persistent vulnerabilities of autism spectrum disorder (ASD), and the neural bases of these deficits remain elusive. A promising hypothesis is that social features of autism may reflect difficulties in making predictions about the social world under conditions of uncertainty. However, no research in ASD has examined how predictability impacts the neural processing of eye-contact in naturalistic interpersonal interactions.

METHOD

We used eye tracking to facilitate an interactive social simulation wherein onscreen faces would establish eye-contact when the participant looked at them. In Experiment One, receipt of eye-contact was unpredictable; in Experiment Two, receipt of eye-contact was predictable. Neural response to eye-contact was measured via the N170 and P300 event-related potentials (ERPs). Experiment One included 23 ASD and 46 typically developing (TD) adult participants. Experiment Two included 25 ASD and 43 TD adult participants.

RESULTS

When receipt of eye-contact was unpredictable, individuals with ASD showed increased N170 and increased, but non-specific, P300 responses. The magnitude of the N170 responses correlated with measures of sensory and anxiety symptomology, such that increased response to eye-contact was associated with increased symptomology. However, when receipt of eye-contact was predictable, individuals with ASD, relative to controls, exhibited slower N170s and no differences in the amplitude of N170 or P300.

LIMITATIONS

Our ASD sample was composed of adults with IQ > 70 and included only four autistic women. Thus, further research is needed to evaluate how these results generalize across the spectrum of age, sex, and cognitive ability. Additionally, as analyses were exploratory, some findings failed to survive false-discovery rate adjustment.

CONCLUSIONS

Neural response to eye-contact in ASD ranged from attenuated to hypersensitive depending on the predictability of the social context. These findings suggest that the vulnerabilities in eye-contact during social interactions in ASD may arise from differences in anticipation and expectation of eye-contact in addition to the perception of gaze alone.

Functional Connectome-Based Predictive Modeling in Autism

Autism is a heterogeneous neurodevelopmental condition, and functional magnetic resonance imaging-based studies have helped advance our understanding of its effects on brain network activity. We review how predictive modeling, using measures of functional connectivity and symptoms, has helped reveal key insights into this condition. We discuss how different prediction frameworks can further our understanding of the brain-based features that underlie complex autism symptomatology and consider how predictive models may be used in clinical settings. Throughout, we highlight aspects of study interpretation, such as data decay and sampling biases, that require consideration within the context of this condition. We close by suggesting exciting future directions for predictive modeling in autism.

Multilevel hybrid principal components analysis for region-referenced functional electroencephalography data

Electroencephalography experiments produce region-referenced functional data representing brain signals in the time or the frequency domain collected across the scalp. The data typically also have a multilevel structure with high-dimensional observations collected across multiple experimental conditions or visits. Common analysis approaches reduce the data complexity by collapsing the functional and regional dimensions, where event-related potential (ERP) features or band power are targeted in a pre-specified scalp region. This practice can fail to portray more comprehensive differences in the entire ERP signal or the power spectral density (PSD) across the scalp. Building on the weak separability of the high-dimensional covariance process, the proposed multilevel hybrid principal components analysis (M-HPCA) utilizes dimension reduction tools from both vector and functional principal components analysis to decompose the total variation into between- and within-subject variance. The resulting model components are estimated in a mixed effects modeling framework via a computationally efficient minorization-maximization algorithm coupled with bootstrap. The diverse array of applications of M-HPCA is showcased with two studies of individuals with autism. While ERP responses to match vs mismatch conditions are compared in an audio odd-ball paradigm in the first study, short-term reliability of the PSD across visits is compared in the second. Finite sample properties of the proposed methodology are studied in extensive simulations.

Combinatorial approaches for treating neuropsychiatric social impairment

Social behaviour is an essential component of human life and deficits in social function are seen across multiple psychiatric conditions with high morbidity. However, there are currently no FDA-approved treatments for social dysfunction. Since social cognition and behaviour rely on multiple signalling processes acting in concert across various neural networks, treatments aimed at social function may inherently require a combinatorial approach. Here, we describe the social neurobiology of the oxytocin and endocannabinoid signalling systems as well as translational evidence for their use in treating symptoms in the social domain. We leverage this systems neurobiology to propose a network-based framework that involves pharmacology, psychotherapy, non-invasive brain stimulation and social skills training to combinatorially target trans-diagnostic social impairment. Lastly, we discuss the combined use of oxytocin and endocannabinoids within our proposed framework as an illustrative strategy to treat specific aspects of social function. Using this framework provides a roadmap for actionable treatment strategies for neuropsychiatric social impairment. This article is part of the theme issue 'Interplays between oxytocin and other neuromodulators in shaping complex social behaviours'.

Brief Report: A Specialized Fitness Program for Individuals with Autism Spectrum Disorder Benefits Physical, Behavioral, and Emotional Outcomes

Individuals with autism spectrum disorder (ASD) engage in less physical activity than typically-developing peers. This can result in serious negative consequences for individual well-being and may contribute to the physical, behavioral, and emotional challenges associated with ASD. This study explored the potential benefits of trainer-led, individualized, physical fitness sessions specialized for ASD. Eleven individuals (ages 7-24 years) with ASD were assessed at baseline and following 15 fitness sessions. Participants demonstrated improvements in core and lower-body strength and reductions in restricted and repetitive patterns of behavior, along with non-significant but marked reductions in issues with daytime sleepiness. Results suggest the merit of specialized fitness programs and emphasize the need for larger and more rigorous research studies on this topic.

Patterns of Intervention Utilization Among School-Aged Children with Autism Spectrum Disorder: Findings from a Multi-Site Research Consortium

When designing and interpreting results from clinical trials evaluating treatments for children on the autism spectrum, a complicating factor is that most children receive a range of concurrent treatments. Thus, it is important to better understand the types and hours of interventions that participants typically receive as part of standard of care, as well as to understand the child, family, and geographic factors that are associated with different patterns of service utilization. In this multi-site study, we interviewed 280 caregivers of 6-to-11-year-old school-aged children on the autism spectrum about the types and amounts of interventions their children received in the prior 6 weeks. Reported interventions were coded as "evidence-based practice" or "other interventions," reflecting the level of empirical support. Results indicated that children received a variety of interventions with varying levels of empirical evidence and a wide range of hours (0 to 79.3 hours/week). Children with higher autism symptom levels, living in particular states, and who identified as non-Hispanic received more evidence-based intervention hours. Higher parental education level related to more hours of other interventions. Children who were younger, had lower cognitive ability, and with higher autism symptom levels received a greater variety of interventions overall. Thus, based on our findings, it would seem prudent when designing clinical trials to take into consideration a variety of factors including autism symptom levels, age, cognitive ability, ethnicity, parent education and geographic location. Future research should continue to investigate the ethnic, racial, and socioeconomic influences on school-aged intervention services.

Associations between sleep problems and domains relevant to daytime functioning and clinical symptomatology in autism: A meta-analysis

Autistic individuals experience significantly higher rates of sleep problems compared to the general population, which negatively impacts various aspects of daytime functioning. The strength of associations across domains of functioning has not yet been summarized across studies. The present meta-analysis examined the strength of associations between sleep problems and various domains of daytime functioning in autistic individuals. Searches were conducted in EMBASE, PubMed, Web of Science, and Google Scholar through May 2020. Inclusion criteria were: an index of sleep disturbance in individuals diagnosed with autism spectrum disorder (ASD); data collected prior to any sleep-related intervention; statistical data indicating relations between sleep problems and outcomes relevant to behavior, cognition, and physical or mental health. Exclusion criteria were: statistics characterizing the relationship between sleep disturbance and outcome variables that partialled out covariates; studies examining correlations between different measures of sleep disturbance. Participants totaled 15,074 from 49 published articles and 51 samples, yielding 209 effect sizes. Sleep problems were significantly associated with more clinical symptomatology and worse daytime functioning. Subgroup analyses demonstrated that sleep problems were most strongly associated with internalizing and externalizing symptoms and executive functioning, followed by core autism symptoms, family factors, and adaptive functioning. Findings highlight the far-reaching consequences of sleep problems on daytime functioning for autistic individuals and support the continued prioritization of sleep as a target for intervention through integrated care models to improve wellbeing. LAY SUMMARY: Autistic individuals experience higher rates of sleep problems, such as difficulty falling asleep and staying asleep, compared to the general population. We quantitatively summarized the literature about how sleep problems are related to different aspects of daytime functioning to identify areas that may be most affected by sleep. Sleep problems were related to all areas assessed, with the strongest associations for mood and anxiety symptoms. We recommend prioritizing sleep health in autistic individuals to improve wellbeing and quality of life.

The autism biomarkers consortium for clinical trials: evaluation of a battery of candidate eye-tracking biomarkers for use in autism clinical trials

BACKGROUND

Eye tracking (ET) is a powerful methodology for studying attentional processes through quantification of eye movements. The precision, usability, and cost-effectiveness of ET render it a promising platform for developing biomarkers for use in clinical trials for autism spectrum disorder (ASD).

METHODS

The autism biomarkers consortium for clinical trials conducted a multisite, observational study of 6-11-year-old children with ASD (n = 280) and typical development (TD, n = 119). The ET battery included: Activity Monitoring, Social Interactive, Static Social Scenes, Biological Motion Preference, and Pupillary Light Reflex tasks. A priori, gaze to faces in Activity Monitoring, Social Interactive, and Static Social Scenes tasks were aggregated into an Oculomotor Index of Gaze to Human Faces (OMI) as the primary outcome measure. This work reports on fundamental biomarker properties (data acquisition rates, construct validity, six-week stability, group discrimination, and clinical relationships) derived from these assays that serve as a base for subsequent development of clinical trial biomarker applications.

RESULTS

All tasks exhibited excellent acquisition rates, met expectations for construct validity, had moderate or high six-week stabilities, and highlighted subsets of the ASD group with distinct biomarker performance. Within ASD, higher OMI was associated with increased memory for faces, decreased autism symptom severity, and higher verbal IQ and pragmatic communication skills.

LIMITATIONS

No specific interventions were administered in this study, limiting information about how ET biomarkers track or predict outcomes in response to treatment. This study did not consider co-occurrence of psychiatric conditions nor specificity in comparison with non-ASD special populations, therefore limiting our understanding of the applicability of outcomes to specific clinical contexts-of-use. Research-grade protocols and equipment were used; further studies are needed to explore deployment in less standardized contexts.

CONCLUSIONS

All ET tasks met expectations regarding biomarker properties, with strongest performance for tasks associated with attention to human faces and weakest performance associated with biological motion preference. Based on these data, the OMI has been accepted to the FDA's Biomarker Qualification program, providing a path for advancing efforts to develop biomarkers for use in clinical trials.

Identifying Age Based Maturation in the ERP Response to Faces in Children With Autism: Implications for Developing Biomarkers for Use in Clinical Trials

Recent proposals have suggested the potential for neural biomarkers to improve clinical trial processes in neurodevelopmental conditions; however, few efforts have identified whether chronological age-based adjustments will be necessary (as used in standardized behavioral assessments). Event-related potentials (ERPs) demonstrate early differences in the processing of faces vs. objects in the visual processing system by 4 years of age and age-based improvement (decreases in latency) through adolescence. Additionally, face processing has been proposed to be related to social skills as well as autistic social-communication traits. While previous reports suggest delayed latency in individuals with autism spectrum disorder (ASD), extensive individual and age based heterogeneity exists. In this report, we utilize a sample of 252 children with ASD and 118 children with typical development (TD), to assess the N170 and P100 ERP component latencies (N170L and P100L, respectively), to upright faces, the face specificity effect (difference between face and object processing), and the inversion effect (difference between face upright and inverted processing) in relation to age. First, linear mixed models (LMMs) were fitted with fixed effect of age at testing and random effect of participant, using all available data points to characterize general age-based development in the TD and ASD groups. Second, LMM models using only the TD group were used to calculate age-based residuals in both groups. The purpose of residualization was to assess how much variation in ASD participants could be accounted for by chronological age-related changes. Our data demonstrate that the N170L and P100L responses to upright faces appeared to follow a roughly linear relationship with age. In the ASD group, the distribution of the age-adjusted residual values suggest that ASD participants were more likely to demonstrate slower latencies than would be expected for a TD child of the same age, similar to what has been identified using unadjusted values. Lastly, using age-adjusted values for stratification, we found that children who demonstrated slowed age-adjusted N170L had lower verbal and non-verbal IQ and worse face memory. These data suggest that age must be considered in assessing the N170L and P100L response to upright faces as well, and these adjusted values may be used to stratify children within the autism spectrum.

Language and Aggressive Behaviors in Male and Female Youth with Autism Spectrum Disorder

Aggressive behaviors are common among youth with autism spectrum disorder (ASD) and correlate with pervasive social-emotional difficulties. Communication skill is an important correlate of disruptive behavior in typical development, and clarification of links between communication and aggression in ASD may inform intervention methods. We investigate child/family factors and communication in relation to aggression among 145 individuals with ASD (65 female; ages 8-17 years). Overall, more severe aggression was associated with younger age, lower family income, and difficulties with communication skills. However, this pattern of results was driven by males, and aggression was unrelated to child or family characteristics for females. Future work should incorporate these predictors in conjunction with broader contextual factors to understand aggressive behavior in females with ASD.

Looking Back at the Next 40 Years of ASD Neuroscience Research

During the last 40 years, neuroscience has become one of the most central and most productive approaches to investigating autism. In this commentary, we assemble a group of established investigators and trainees to review key advances and anticipated developments in neuroscience research across five modalities most commonly employed in autism research: magnetic resonance imaging, functional near infrared spectroscopy, positron emission tomography, electroencephalography, and transcranial magnetic stimulation. Broadly, neuroscience research has provided important insights into brain systems involved in autism but not yet mechanistic understanding. Methodological advancements are expected to proffer deeper understanding of neural circuitry associated with function and dysfunction during the next 40 years.

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

BACKGROUND

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

METHODS

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

RESULTS

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

CONCLUSIONS

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

Contrast Is in the Eye of the Beholder: Infelicitous Beat Gesture Increases Cognitive Load During Online Spoken Discourse Comprehension

We investigated how two cues to contrast-beat gesture and contrastive pitch accenting-affect comprehenders' cognitive load during processing of spoken referring expressions. In two visual-world experiments, we orthogonally manipulated the presence of these cues and their felicity, or fit, with the local (sentence-level) referential context in critical referring expressions while comprehenders' task-evoked pupillary responses (TEPRs) were examined. In Experiment 1, beat gesture and contrastive accenting always matched the referential context of filler referring expressions and were therefore relatively felicitous on the global (experiment) level, whereas in Experiment 2, beat gesture and contrastive accenting never fit the referential context of filler referring expressions and were therefore infelicitous on the global level. The results revealed that both beat gesture and contrastive accenting increased comprehenders' cognitive load. For beat gesture, this increase in cognitive load was driven by both local and global infelicity. For contrastive accenting, this increase in cognitive load was unaffected when cues were globally felicitous but exacerbated when cues were globally infelicitous. Together, these results suggest that comprehenders' cognitive resources are taxed by processing infelicitous use of beat gesture and contrastive accenting to convey contrast on both the local and global levels.

Modeling temporal dynamics of face processing in youth and adults

A hierarchical model of temporal dynamics was examined in adults (n = 34) and youth (n = 46) across the stages of face processing during the perception of static and dynamic faces. Three ERP components (P100, N170, N250) and spectral power in the mu range were extracted, corresponding to cognitive stages of face processing: low-level vision processing, structural encoding, higher-order processing, and action understanding. Youth and adults exhibited similar yet distinct patterns of hierarchical temporal dynamics such that earlier cognitive stages predicted later stages, directly and indirectly. However, latent factors indicated unique profiles related to behavioral performance for adults and youth and age as a continuous factor. The application of path analysis to electrophysiological data can yield novel insights into the cortical dynamics of social information processing.

Brief Report: Preliminary Evidence of the N170 as a Biomarker of Response to Treatment in Autism Spectrum Disorder

Background: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder characterized by primary difficulties in social function. Individuals with ASD display slowed neural processing of faces, as indexed by the latency of the N170, a face-sensitive event-related potential. Currently, there are no objective biomarkers of ASD useful in clinical care or research. Efficacy of behavioral treatment is currently evaluated through subjective clinical impressions. To explore whether the N170 might have utility as an objective index of treatment response, we examined N170 before and after receipt of an empirically validated behavioral treatment in children with ASD. Method: Electroencephalography (EEG) data were obtained on a preliminary cohort of preschool-aged children with ASD before and after a 16-week course of PRT and in a subset of participants in waitlist control (16-weeks before the start of PRT) and follow-up (16-weeks after the end of PRT). EEG was recorded while participants viewed computer-generated faces with neutral and fearful affect. Results: Significant reductions in N170 latency to faces were observed following 16 weeks of PRT intervention. Change in N170 latency was not observed in the waitlist-control condition. Conclusions: This exploratory study offers suggestive evidence that N170 latency may index response to behavioral treatment. Future, more rigorous, studies in larger samples are indicated to evaluate whether the N170 may be useful as a biomarker of treatment response.

Impact of autism genetic risk on brain connectivity: a mechanism for the female protective effect

The biological mechanisms underlying the greater prevalence of autism spectrum disorder in males than females remain poorly understood. One hypothesis posits that this female protective effect arises from genetic load for autism spectrum disorder differentially impacting male and female brains. To test this hypothesis, we investigated the impact of cumulative genetic risk for autism spectrum disorder on functional brain connectivity in a balanced sample of boys and girls with autism spectrum disorder and typically developing boys and girls (127 youth, ages 8-17). Brain connectivity analyses focused on the salience network, a core intrinsic functional connectivity network which has previously been implicated in autism spectrum disorder. The effects of polygenic risk on salience network functional connectivity were significantly modulated by participant sex, with genetic load for autism spectrum disorder influencing functional connectivity in boys with and without autism spectrum disorder but not girls. These findings support the hypothesis that autism spectrum disorder risk genes interact with sex differential processes, thereby contributing to the male bias in autism prevalence and proposing an underlying neurobiological mechanism for the female protective effect.

Face perception predicts affective theory of mind in autism spectrum disorder but not schizophrenia or typical development

Autism spectrum disorder (ASD) and schizophrenia spectrum disorder (SCZ) have overlapping symptomatology related to difficulties with social cognition. Yet, few studies have directly compared social cognition in ASD, SCZ, and typical development (TD). The current study examined individual differences in face recognition and its relation to affective theory of mind (ToM) in each diagnostic group. Adults with ASD (n = 31), SCZ (n = 43), and TD (n = 47) between the ages of 18 and 48 years-old with full scale IQ above 80 participated in this study. The Reading the Mind in the Eyes Test (RMET) measured affective ToM, and the Benton Facial Recognition Test (BFRT) measured face perception. Adults with ASD and SCZ did not differ in their affective ToM abilities, and both groups showed affective ToM difficulties compared with TD. However, better face recognition ability uniquely predicted better affective ToM ability in ASD. Results suggest that affective ToM difficulties may relate to face processing in ASD but not SCZ. By clarifying the complex nature of individual differences in affective ToM and face recognition difficulties in these disorders, the present study suggests there may be divergent mechanisms underlying pathways to social dysfunction in ASD compared with SCZ. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

A neurogenetic analysis of female autism

Females versus males are less frequently diagnosed with autism spectrum disorder (ASD), and while understanding sex differences is critical to delineating the systems biology of the condition, female ASD is understudied. We integrated functional MRI and genetic data in a sex-balanced sample of ASD and typically developing youth (8–17 years old) to characterize female-specific pathways of ASD risk. Our primary objectives were to: (i) characterize female ASD (n = 45) brain response to human motion, relative to matched typically developing female youth (n = 45); and (ii) evaluate whether genetic data could provide further insight into the potential relevance of these brain functional differences. For our first objective we found that ASD females showed markedly reduced response versus typically developing females, particularly in sensorimotor, striatal, and frontal regions. This difference between ASD and typically developing females does not resemble differences between ASD (n = 47) and typically developing males (n = 47), even though neural response did not significantly differ between female and male ASD. For our second objective, we found that ASD females (n = 61), versus males (n = 66), showed larger median size of rare copy number variants containing gene(s) expressed in early life (10 postconceptual weeks to 2 years) in regions implicated by the typically developing female > female functional MRI contrast. Post hoc analyses suggested this difference was primarily driven by copy number variants containing gene(s) expressed in striatum. This striatal finding was reproducible among n = 2075 probands (291 female) from an independent cohort. Together, our findings suggest that striatal impacts may contribute to pathways of risk in female ASD and advocate caution in drawing conclusions regarding female ASD based on male-predominant cohorts.

The N170 event-related potential reflects delayed neural response to faces when visual attention is directed to the eyes in youths with ASD

Atypical neural response to faces is thought to contribute to social deficits in autism spectrum disorder (ASD). Compared to typically developing (TD) controls, individuals with ASD exhibit delayed brain responses to upright faces at a face-sensitive event-related potential (ERP), the N170. Given observed differences in patterns of visual attention to faces, it is not known whether slowed neural processing may simply reflect atypical looking to faces. The present study manipulated visual attention to facial features to examine whether directed attention to the eyes normalizes N170 latency in ASD. ERPs were recorded in 30 children and adolescents with ASD as well as 26 TD children and adolescents. Results replicated prior findings of shorter N170 latency to the eye region of the face in TD individuals. In contrast, those with ASD did not demonstrate modulation of N170 latency by point of regard to the face. Group differences in latency were most pronounced when attention was directed to the eyes. Results suggest that well-replicated findings of N170 delays in ASD do not simply reflect atypical patterns of visual engagement with experimental stimuli. These findings add to a body of evidence indicating that N170 delays are a promising marker of atypical neural response to social information in ASD. LAY SUMMARY: This study looks at how children's and adolescents' brains respond when looking at different parts of a face. Typically developing children and adolescents processed eyes faster than other parts of the face, whereas this pattern was not seen in ASD. Children and adolescents with ASD processed eyes more slowly than typically developing children. These findings suggest that observed inefficiencies in face processing in ASD are not simply reflective of failure to attend to the eyes.

The gap between IQ and adaptive functioning in autism spectrum disorder: Disentangling diagnostic and sex differences

LAY ABSTRACT

Adaptive functioning refers to skills that are vital to success in day-to-day life, including daily living (e.g. grocery shopping, food preparation, transportation use), communication (e.g. verbal expression of needs), and socialization skills (e.g. interpersonal skills, including expressing and recognizing emotions, and understanding turn-taking in conversation). Among autistic individuals without intellectual disability, adaptive functioning is not commensurate with intellectual ability (IQ), and instead a gap exists between these individuals' intellectual ability and their adaptive skills. Further, these autistic individuals show a widening of this gap with increasing age. Existing studies of the gap between IQ and adaptive functioning have studied predominantly male samples. Thus, we do not know if the gap also exists in autistic females. We therefore looked at adaptive functioning and the gap between IQ and adaptive functioning in a large sample of autistic girls and boys without intellectual disability. To disentangle effects of group (autistic vs typically developing) from effects of sex (girls vs boys), we compared autistic girls and boys to one another as well as to their same-sex typically developing peers. Analyses took into consideration differences in IQ between autistic and typically developing youth. We found autistic girls, like autistic boys, show lower adaptive functioning than their same-sex typically developing peers. Results underscore the need to evaluate adaptive functioning in autistic individuals without intellectual disability and to provide necessary supports. The large gap between intellectual ability and socialization skills, in particular, may be of critical importance in improving our understanding of outcomes and mental health difficulties among autistic females.

Eye see what you're saying: Contrastive use of beat gesture and pitch accent affects online interpretation of spoken discourse

Cues to prominence such as beat gesture and contrastive pitch accent play an important role in constraining what is remembered. However, it is currently unclear how beat gesture affects online discourse processing alone and in combination with contrastive accenting. Using an adaptation of the visual world eye-tracking paradigm, we orthogonally manipulated the presence of these cues and their felicity (match) with contrast within local (sentence-level) and global (experiment-level) referential contexts. In Experiment 1, in which beat gesture and contrastive accenting were always globally felicitous with the context of filler referring expressions, beat gesture increased anticipation of both target and competitor referents of locally infelicitous critical referring expressions differing in color and shape, whereas contrastive accenting hindered resolution of these expressions. In Experiment 2, in which beat gesture and contrastive accenting were always globally infelicitous with the context of filler referring expressions, beat gesture increased anticipation of both target and competitor referents of locally felicitous critical referring expressions contrasting in color, whereas contrastive accenting did not affect their interpretation. Taken together, these findings indicate that local and global felicity of cues to prominence with contrast affects their interpretation during online spoken discourse processing. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

First-Hand Accounts of Interoceptive Difficulties in Autistic Adults

Interoceptive awareness refers to one's ability to detect, discriminate, and regulate internal bodily and mental processes. Interoceptive challenges in ASD remain under researched and poorly understood. In this study, we analyzed texts of adults who self-identify as autistic describing their interoceptive challenges. Many individuals described limited awareness of hunger, satiation, or thirst, which contributed to eating disordered behavior in some instances. Others described limited awareness or difficulty understanding affective arousal, pain or illness, and difficulty differentiating benign body signals from signals that represent medical concerns. Findings from this study call for increased research attention on this topic, and a need for valid and objective measures for assessing interoception in ASD.

Do Biological Sex and Early Developmental Milestones Predict the Age of First Concerns and Eventual Diagnosis in Autism Spectrum Disorder?

Despite advances in early detection, the average age of autism spectrum disorder (ASD) diagnosis exceeds 4 years and is often later in females. In typical development, biological sex predicts inter-individual variation across multiple developmental milestones, with females often exhibiting earlier progression. The goal of this study was to examine sex differences in caregiver-reported developmental milestones (first word, phrase, walking) and their contribution to timing of initial concerns expressed by caregivers and eventual age of diagnosis. 195 (105 males) children and adolescents aged 8 to 17 years with a clinical diagnosis of ASD were recruited to the study (mean IQ = 99.76). While developmental milestones did not predict timing of diagnosis or age parents first expressed concerns, females had earlier first words and phrases than males. There was a marginal difference in the age of diagnosis, with females receiving their diagnosis 1 year later than males. Despite sex differences in developmental milestones and diagnostic variables, IQ was the most significant predictor in the timing of initial concerns and eventual diagnosis, suggesting children with lower IQ, regardless of sex, are identified and diagnosed earlier. Overall, biological sex and developmental milestones did not account for a large proportion of variance for the eventual age of ASD diagnosis, suggesting other factors (such as IQ and the timing of initial concerns) are potentially more influential. LAY SUMMARY: In this study, a later age of diagnosis in females having ASD was confirmed; however, biological sex was not the stronger predictor of age of diagnosis. Parents reported that females learned language more quickly than males, and parents noted their first concerns when females were older than males. In this sample, the strongest predictor of age of diagnosis was the age of first concerns.

Low-motion fMRI data can be obtained in pediatric participants undergoing a 60-minute scan protocol

Performing functional magnetic resonance imaging (fMRI) scans of children can be a difficult task, as participants tend to move while being scanned. Head motion represents a significant confound in fMRI connectivity analyses. One approach to limit motion has been to use shorter MRI protocols, though this reduces the reliability of results. Hence, there is a need to implement methods to achieve high-quality, low-motion data while not sacrificing data quantity. Here we show that by using a mock scan protocol prior to a scan, in conjunction with other in-scan steps (weighted blanket and incentive system), it is possible to achieve low-motion fMRI data in pediatric participants (age range: 7-17 years old) undergoing a 60 min MRI session. We also observe that motion is low during the MRI protocol in a separate replication group of participants, including some with autism spectrum disorder. Collectively, the results indicate it is possible to conduct long scan protocols in difficult-to-scan populations and still achieve high-quality data, thus potentially allowing more reliable fMRI findings.