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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.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.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.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.

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.

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.

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.

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.

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. Conclusions: 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.

BACKGROUND As many as 80% of children on the autism spectrum exhibit challenging behaviors (i.e., behaviors dangerous to the self or others, behaviors that interfere with learning and development, and/or 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), yet parents and teachers often report that challenging behaviors surface with little warning. Exciting recent advances in biometric sensing and mobile computing technology allow measurement of momentary emotion dysregulation using physiological indices. OBJECTIVE We present the framework and protocol for a pilot trial that will test a mobile digital mental health application, the KeepCalm app. School-based approaches to managing challenging behaviors in children on the autism spectrum are limited by three key factors: 1) children on the autism spectrum often have difficulties communicating their emotions; 2) it is challenging to implement evidence-based, personalized strategies for individual children in group settings; and 3) it is difficult for teachers to track which strategies are successful for each child. KeepCalm aims to address those barriers by 1) communicating children’s stress to their teachers using physiological signaling (emotion dysregulation detection); 2) supporting implementation of emotion regulation strategies via smartphone pop-up notifications of top strategies for each child per behavior (emotion regulation strategy implementation); and 3) easing the burden 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/negatives of stress alerts, and 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 on important aspects of implementing KeepCalm in preschools and elementary schools and will provide preliminary data on its efficacy to reduce challenging behaviors and support emotion regulation in children on the autism spectrum. CLINICALTRIAL ClinicalTrials.gov ID: NCT05277194 (https://www.clinicaltrials.gov/ct2/show/NCT05277194)

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).

Children with autism spectrum disorder are prescribed various medications to address behavior and mood. In clinical trials, individuals taking concomitant psychotropic medications often are excluded to maintain homogeneity and prevent contamination of clinical endpoints. However, this choice may compromise the representativeness of the sample. In a recent study designed to identify biomarkers and endpoints for clinical trials (the Autism Biomarkers Consortium for Clinical Trials), school-age children with autism spectrum disorder were enrolled without excluding for medications, providing the opportunity to examine characteristics of psychotropic medication use and 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 study 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. The most commonly reported psychotropic medications included melatonin, stimulants, selective serotonin reuptake inhibitors, alpha agonists, and antipsychotics. Our findings suggest that exclusion of children taking concomitant psychotropic medications could limit the representativeness of the study population, perhaps even excluding children who may most benefit from new treatment options. 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.

Autism spectrum disorder (ASD) and schizophrenia spectrum disorders (SZ) are both characterized by difficulty with social cognition. Likewise, social brain activity is atypical in both disorders and indicates atypical reception of facial communication – a key area in the Research Domain Criteria framework for identifying common biological underpinnings of psychiatric disorders. To identify areas of overlap and dissociation between ASD and SZ, this paper reviews studies of electrophysiological (EEG) response to facial stimuli across ASD and SZ populations. We focus on findings regarding amplitude and latency of four brain responses implicated in social perception: P100, N170, N250, and P300. There were many inconsistent findings in both the ASD and SZ literatures; however, replication across studies was strongest for delayed N170 latency in ASD and attenuated N170 amplitude in SZ. EEG responses corresponded with clinical symptoms in multiple samples. These results highlight the challenges associated with replicating research findings in heterogeneous clinical populations, as well as the need for transdiagnostic research and for designing studies to examine relationships among continuous quantifications of behavior and neural activity across neurodevelopmental disorders.

Impairments in theory of mind (ToM)—long considered common among individuals with autism spectrum disorder (ASD)—are in fact highly heterogeneous across this population. Although such heterogeneity should be reflected in differential recruitment of neural mechanisms during ToM reasoning, no research has yet uncovered a mechanism that explains these individual differences. In this study, 78 (48 with ASD) adolescents viewed ToM vignettes and made mental-state inferences about characters’ behavior while participant electrophysiology was concurrently recorded. Two candidate event-related-potentials (ERPs)—the late positive complex (LPC) and the late slow wave (LSW)—were successfully elicited. LPC scores correlated positively with ToM accuracy and negatively with ASD symptom severity. Note that the LPC partially mediated the relationship between ASD symptoms and ToM accuracy, which suggests that this ERP component, thought to represent cognitive metarepresentation, may help explain differences in ToM performance in some individuals with ASD.

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., Females are less frequently diagnosed with autism than males. Using functional brain imaging and genetic analyses, Jack et al. show that differences in the striatum, a part of the brain involved in attaching motivational value to stimuli in the environment, may contribute to autism risk in girls.

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.

Adaptive functioning, or the suite of skills essential for real-world, day-to-day functioning, includes daily living, communication, and socialization abilities. Even in the absence of co-occurring intellectual disability (IQ 70) ASD (females = 75, males = 102), and 178 typically developing (TD) (females = 87, males = 91) youth, aged 8–17 years. We examined whether each group evidenced a gap between full-scale IQ and adaptive skills and its associations with age. ASD youth evinced significantly lower adaptive skills and a significantly greater IQ-adaptive functioning gap than their same-sex TD peers. In this cross-sectional sample, the increase in the IQ-adaptive functioning gap with age was of similar magnitude for ASD males and females, but only reached statistical significance in males. We discuss unique implications the profound IQ-socialization skills gap in particular may have for ASD females. 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.

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’.

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.

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.

There is growing interest in "interoception" (i.e., detection and interpretation of internal body signals) as a relevant mechanism contributing to certain symptoms and features of autism spectrum disorder (ASD) and alexithymia. However, inconsistent measurement and operationalization of interoception has led to confusion and inconsistent findings in the literature. In this commentary, we present alternative interpretations of findings from existing studies to demonstrate that ASD and alexithymia are conditions associated with reduced adaptive forms of interoceptive attention (i.e., attention toward bodily signals) but heightened maladaptive forms of interoceptive attention related to anxiety-induced somatization. Differentiating adaptive and maladaptive forms of interoceptive attention reveals a clearer pattern of findings in the research literature for further investigation of interoceptive processes that are involved in the neurobiology of ASD. However, interoception is a complex and multi-faceted construct that requires continual refinement in conceptualization and operationalization. Interoception research may benefit from self-report measures that clearly differentiate adaptive and maladaptive forms of bodily awareness. LAY SUMMARY: Some research suggests that autistic people have difficulty understanding bodily feelings such as hunger, illness, or emotions, whereas some studies have reported the opposite pattern of findings. We argue that this latter subset of studies reached false conclusions from using measures of bodily awareness that largely measure physical symptoms of anxiety. While attention to unpleasant bodily signals is an important ability necessary for maintaining healthy bodily functioning, excessive attention, and worry toward bodily signals can increase anxiety and be harmful.

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.

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.

Objective: Despite the frequent occurrence of depressive symptoms in children and adolescents with autism spectrum disorder (ASD), few studies have investigated the relationship between depressive ...

Light-adapted (LA) electroretinograms (ERGs) from 90 individuals with autism spectrum disorder (ASD), mean age (13.0 ± 4.2), were compared to 87 control subjects, mean age (13.8 ± 4.8). LA-ERGs were produced by a random series of nine different Troland based, full-field flash strengths and the ISCEV standard flash at 2/s on a 30 cd m−2 white background. A random effects mixed model analysis showed the ASD group had smaller b- and a-wave amplitudes at high flash strengths (p