Sleep and Activity Patterns in Autism Spectrum Disorder.

Background: Autism spectrum disorder (ASD) is a highly heritable and heterogeneous neurodevelopmental disorder characterized by impaired social interactions, repetitive behaviors, and a wide range of comorbidities. Between 44-83% of autistic individuals report sleep disturbances, which may share an underlying neurodevelopmental basis with ASD. Methods: We recruited 382 ASD individuals and 223 of their family members to obtain quantitative ASD-related traits and wearable device-based accelerometer data spanning three consecutive weeks. An unbiased approach identifying traits associated with ASD was achieved by applying the elastic net machine learning algorithm with five-fold cross-validation on 6,878 days of data. The relationship between sleep and physical activity traits was examined through linear mixed-effects regressions using each night of data. Results: This analysis yielded 59 out of 242 actimetry measures associated with ASD status in the training set, which were validated in a test set (AUC: 0.777). For several of these traits (e.g. total light physical activity), the day-to-day variability, in addition to the mean, was associated with ASD. Individuals with ASD were found to have a stronger correlation between physical activity and sleep, where less physical activity decreased their sleep more significantly than that of their non-ASD relatives. Conclusions: The average duration of sleep/physical activity and the variation in the average duration of sleep/physical activity strongly predict ASD status. Physical activity measures were correlated with sleep quality, traits, and regularity, with ASD individuals having stronger correlations. Interventional studies are warranted to investigate whether improvements in both sleep and increased physical activity may improve the core symptoms of ASD.

A quasi-experimental study in sibling dyads: differential provocation-aggression patterns in the interactive taylor aggression paradigm.

Introduction: The Taylor Aggression Paradigm (TAP) is a well-established tool for assessing provocation-induced reactive aggression. We introduce an interactive version, the iTAP, with real-time opponents across 60 trials, including five simulated provocation trials in the middle. In this quasi-experimental study, we evaluate the effectiveness of the paradigm to investigate reactive aggression in interacting participants. The design allows us to employ the TAP in settings of high familiarity dyads, addressing an existing gap. Method: Twenty-eight healthy same-sex adult sibling pairs (N = 56) competed against each other in the iTAP, exemplifying high familiarity through their social and emotional co-development, and mutual knowledge. Additionally, we explore naturally arising aggression types in terms of sibling pairs' reciprocal aggression trajectories across trials. Lastly, we investigate situational and personal variables influencing reactive aggression on the iTAP within high familiarity dyads. Results: In line with non-interactive TAP versions, siblings employed a global "tit-for-tat" strategy in response to heightened provocation: Aggression increased during manipulated trials of increasing provocation, persisted during real interaction and declined in the final block, suggesting sibling co-regulation which was underscored by the convergence in within-pair aggression level. We found no gender differences in these dynamics but a trend for higher initial aggression levels within brother pairs and higher responsiveness to increased provocation in sister pairs. Overall aggression levels were related to situational variables including trial outcome (lost, won, and tie), Further, siblings' state anger correlated positively with aggression scores on the iTAP. Aggression was not reliably related to personal variables predicting aggression. We identified subgroups of sibling pairs with distinct provocation-aggression patterns related to differences in reported behavioral motivations and emotional states. The results highlight situational over personal variables in determining aggressive behavior on the task in this sample of healthy adults. While no direct link between sibling relationship quality and aggression was found, the overall behavior was likely influenced by the familiarity between siblings and the specific context of their relationship. Conclusion: The iTAP demonstrates promise as a tool for studying reciprocal aggressive behavior. The emergence of different interaction patterns underscores the ecological validity introduced by the interactive context, which complements the standard versions of the TAP.

Psychotropic Medication Use in Children and Youth with Autism Enrolled in Medicaid.

Children with autism frequently present with complex mental health diagnoses and psychotropic medications are often a component of comprehensive biopsychosocial treatment plans for these conditions. The purpose of this study is to provide rates and patterns of psychotropic medication use, and predictors thereof, in children and youth with autism enrolled in Medicaid across the US. This study examined national Medicaid claims from 2008 to 2016 of all children and youth with autism ages 0-21 years enrolled in Medicaid. Psychotropic medication use was examined across several child and youth characteristics, including age, co-occurring mental health conditions, sex, and race and ethnicity. About half of children and youth with autism enrolled in Medicaid had at least one psychotropic prescription in a year, a number that decreased slightly across the study period due to decreases in the prescription of antipsychotics. As new medications for autism or co-occurring conditions are developed and deployed, and as the understanding of the characteristics of the population of children with autism evolves, studying rates of medication usage helps to understand utilization patterns and differences in access to quality care.

HD-tDCS induced changes in resting-state functional connectivity: Insights from EF modeling.

BACKGROUND: High-definition transcranial direct current stimulation (HD-tDCS) holds promise for therapeutic use in psychiatric disorders. One obstacle for the implementation into clinical practice is response variability. One way to tackle this obstacle is the use of Individualized head models. OBJECTIVE: This study investigated the variability of HD-tDCS induced electric fields (EFs) and its impact on resting-state functional connectivity (rsFC) during different time windows. METHODS: In this randomized, double-blind, and sham controlled study, seventy healthy males underwent 20 min of 1.5 mA HD-tDCS on the right inferior frontal gyrus (rIFG) while undergoing resting-state functional magnetic resonance imaging (rs-fMRI). Individual head models and EF simulations were created from anatomical images. The effects of HD-tDCS on rsFC were assessed using a seed-to-voxel analysis. A subgroup analysis explored the relationship between EF magnitude and rsFC during different stimulation time windows. RESULTS: Results highlighted significant variability in HD-tDCS-induced EFs. Compared to the sham group, the active group showed increased rsFC between the rIFG and the left prefrontal cortex, during and after stimulation. During active stimulation, EF magnitude correlated positively with rsFC between the rIFG and the left hippocampus initially, and negatively during the subsequent period. CONCLUSION: This study indicated an HD-tDCS induced increase of rsFC between left and right prefrontal areas. Furthermore, an interaction between the magnitude and the duration of HD-tDCS on rsFC was observed. Due to the high EF variability that was apparent, these findings highlight the need for individualized HD-tDCS protocols and the creation of head models to optimize effects and reduce response heterogeneity.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population.

Importance: Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment. Objective: To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations. Design, Setting, and Participants: This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022. Main Outcomes and Measures: The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations. Results: Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] ß, 0.83 [0.02]; P = 4.22 × 10-6). Conclusions and Relevance: This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Allelic contribution of Nrxn1α to autism-relevant behavioral phenotypes in mice.

Copy number variations (CNVs) in the Neurexin 1 (NRXN1) gene, which encodes a presynaptic protein involved in neurotransmitter release, are some of the most frequently observed single-gene variants associated with autism spectrum disorder (ASD). To address the functional contribution of NRXN1 CNVs to behavioral phenotypes relevant to ASD, we carried out systematic behavioral phenotyping of an allelic series of Nrxn1 mouse models: one carrying promoter and exon 1 deletion abolishing Nrxn1α transcription, one carrying exon 9 deletion disrupting Nrxn1α protein translation, and one carrying an intronic deletion with no observable effect on Nrxn1α expression. We found that homozygous loss of Nrxn1α resulted in enhanced aggression in males, reduced affiliative social behaviors in females, and significantly altered circadian activities in both sexes. Heterozygous or homozygous loss of Nrxn1α affected the preference for social novelty in male mice, and notably, enhanced repetitive motor skills and motor coordination in both sexes. In contrast, mice bearing an intronic deletion of Nrxn1 did not display alterations in any of the behaviors assessed. These findings demonstrate the importance of Nrxn1α gene dosage in regulating social, circadian, and motor functions, and the variables of sex and genomic positioning of CNVs in the expression of autism-related phenotypes. Importantly, mice with heterozygous loss of Nrxn1, as found in numerous autistic individuals, show an elevated propensity to manifest autism-related phenotypes, supporting the use of models with this genomic architecture to study ASD etiology and assess additional genetic variants associated with autism.

Contrasting Views of Autism Spectrum Traits in Adults, Especially in Self-Reports vs. Informant-Reports for Women High in Autism Spectrum Traits.

There is uncertainty among researchers and clinicians about how to best measure autism spectrum dimensional traits in adults. In a sample of adults with high levels of autism spectrum traits and without intellectual disability (probands, n = 103) and their family members (n = 96), we sought to compare self vs. informant reports of autism spectrum-related traits and possible effects of sex on discrepancies. Using correlational analysis, we found poor agreement between self- and informant-report measures for probands, yet moderate agreement for family members. We found reporting discrepancy was greatest for female probands, often self-reporting more autism-related behaviors. Our findings suggest that autism spectrum traits are often underrecognized by informants, making self-report data important to collect in clinical and research settings.

High-definition transcranial direct current stimulation (HD-tDCS) for the enhancement of working memory - A systematic review and meta-analysis of healthy adults.

BACKGROUND: High-definition transcranial direct current stimulation (HD-tDCS) administers weak electric current through multiple electrodes, enabling focal brain stimulation. An increasing number of studies investigate the effects of anodal HD-tDCS on the enhancement of working memory (WM). The effectiveness of the technique is, however, still unclear. OBJECTIVE/HYPOTHESIS: This systematic review analyzed the current literature on anodal HD-tDCS for WM enhancement, investigating its effectiveness and the influence of different moderators to allow for comparison with conventional tDCS. METHODS: Following the Preferred Reporting Items for Systematic Reviews (PRISMA) guidelines, a comprehensive literature review was conducted using PubMed, Web of Science, and Scopus. Sixteen single- or double-blind, sham-controlled studies were included in the review. Eleven studies were included in the meta-analysis, focusing solely on stimulation of the left prefrontal cortex (PFC). RESULTS: No significant effect of anodal HD-tDCS on the left PFC for WM accuracy (g = 0.23, p = 0.08), and reaction time (g = 0.03, p = 0.75 after trim-and-fill) was found. Further analysis revealed heterogeneity in the accuracy results. Here, moderator analysis indicated a significant difference between studies that repeatedly used HD-tDCS enhanced WM training and studies with one-time use of HD-tDCS (p < 0.001), the latter having a smaller effect size. Another moderator was the research design, with differences between within-subjects-, and between-subjects designs (p < 0.05). Within-subject studies showed lower effect sizes and substantially lower heterogeneity. Qualitative analysis reinforced this finding and indicated that the motivation of the participant to engage in the task also moderates the effectiveness of HD-tDCS. CONCLUSION: This review highlights the importance of inter-individual differences and the setup for the effectiveness of anodal, HD-tDCS augmented WM training. Limited evidence for increased sensitivity of HD-tDCS to these factors as compared to conventional tDCS is provided.

Two mechanisms facilitate regional independence between brain regions based on an examination of alpha-band activity in healthy control adult males.

BACKGROUND: At rest, 8 to 12 Hz alpha rhythms are the dominant rhythm in the brain, with a common peak alpha frequency (PAF = the frequency at which alpha generators show maximum power) observed across brain regions. Although a common PAF across brain regions should result in high between-region connectivity, especially connectivity measures assessing the phase-similarity between alpha generators, high inter-regional alpha connectivity has not been observed. The present study was conducted as an initial step toward identifying mechanisms that allow brain regions to maintain functional independence in the presence of a common PAF. METHODS: MEG data were obtained from 16 healthy control male adults (mean age = 24 years; range 21 to 30 years). A task requiring participants to alternate between a 10 s eyes-closed condition and a 5 s eyes-open condition was used to drive parietal-occipital alpha generators, with the 10 s eyes-closed condition eliciting large-amplitude alpha activity and thus providing alpha measures with good signal-to-noise ratio for source localization. Alpha source-space measures were obtained using Vector-based Spatial-Temporal Analysis using L1-minimum-norm. In each participant, the four strongest parietal-occipital alpha generators were identified. Connectivity between sources was assessed via a measure of phase-based connectivity called inter-site phase clustering (ISPC). RESULTS: Intra-class correlations (ICC) showed very high similarity in the average PAF (=computed using all eyes-closed data) between the four alpha sources (ICC single measure = 0.88, p < 0.001). Despite a common average PAF, across participants, significant ISPC was often observed no more than that expected by chance. Examination of the alpha time course data indicated that low ISPC was often due to instantaneous changes in alpha phase (phase slips). ISPC analyses removing data with phase slips indicated that low ISPC was also due to slight continuous changes in the alpha frequency, with frequency drift more likely in non-significant than significant ISPC trials. CONCLUSIONS: The present exploratory effort suggested two processes underlying the lack of observed inter-regional alpha phase coherence that may help maintain regional functional independence even in the presence of a common PAF. In particular, although the alpha generators were observed to oscillate at the same rate on average, across time each alpha generator oscillated a little slower or faster, and about every one and a half seconds an alpha generator abruptly lost the beat. Because of this, functional independence among alpha generators (and thus brain regions) was the rule rather than the exception. Studies replicating these processes that allow brain regions to maintain functional independence, using different source localization methods and in different conditions (e.g., a true resting state), are warranted. IMPACT STATEMENT: Using source localization to measure parietal-occipital alpha generator activity, two properties that limit between-region alpha functional connectivity are proposed. In particular, a model of alpha generator activity is offered where via transient phase slips occurring approximately every 1.5 s, as well as slight non-stationarity in the alpha frequency, brain regions retain a common alpha frequency while also maintaining regional identity and presumably functionality. Findings also suggest novel markers for use in studies examining changes in alpha activity across maturation as well as in studies examining alpha activity in patient populations where alpha abnormalities have been reported.

Calculating genetic risk for dysfunction in pleiotropic biological processes using whole exome sequencing data.

BACKGROUND: Numerous genes are implicated in autism spectrum disorder (ASD). ASD encompasses a wide-range and severity of symptoms and co-occurring conditions; however, the details of how genetic variation contributes to phenotypic differences are unclear. This creates a challenge for translating genetic evidence into clinically useful knowledge. Sleep disturbances are particularly prevalent co-occurring conditions in ASD, and genetics may inform treatment. Identifying convergent mechanisms with evidence for dysfunction that connect ASD and sleep biology could help identify better treatments for sleep disturbances in these individuals. METHODS: To identify mechanisms that influence risk for ASD and co-occurring sleep disturbances, we analyzed whole exome sequence data from individuals in the Simons Simplex Collection (n = 2380). We predicted protein damaging variants (PDVs) in genes currently implicated in either ASD or sleep duration in typically developing children. We predicted a network of ASD-related proteins with direct evidence for interaction with sleep duration-related proteins encoded by genes with PDVs. Overrepresentation analyses of Gene Ontology-defined biological processes were conducted on the resulting gene set. We calculated the likelihood of dysfunction in the top overrepresented biological process. We then tested if scores reflecting genetic dysfunction in the process were associated with parent-reported sleep duration. RESULTS: There were 29 genes with PDVs in the ASD dataset where variation was reported in the literature to be associated with both ASD and sleep duration. A network of 108 proteins encoded by ASD and sleep duration candidate genes with PDVs was identified. The mechanism overrepresented in PDV-containing genes that encode proteins in the interaction network with the most evidence for dysfunction was cerebral cortex development (GO:0,021,987). Scores reflecting dysfunction in this process were associated with sleep durations; the largest effects were observed in adolescents (p = 4.65 × 10-3). CONCLUSIONS: Our bioinformatic-driven approach detected a biological process enriched for genes encoding a protein-protein interaction network linking ASD gene products with sleep duration gene products where accumulation of potentially damaging variants in individuals with ASD was associated with sleep duration as reported by the parents. Specifically, genetic dysfunction impacting development of the cerebral cortex may affect sleep by disrupting sleep homeostasis which is evidenced to be regulated by this brain region. Future functional assessments and objective measurements of sleep in adolescents with ASD could provide the basis for more informed treatment of sleep problems in these individuals.

Reconsidering animal models used to study autism spectrum disorder: Current state and optimizing future.

Neurodevelopmental disorders (NDDs), including autism spectrum disorder (ASD) and intellectual disability (ID), are pervasive, often lifelong disorders, lacking evidence-based interventions for core symptoms. With no established biological markers, diagnoses are defined by behavioral criteria. Thus, preclinical in vivo animal models of NDDs must be optimally utilized. For this reason, experts in the field of behavioral neuroscience convened a workshop with the goals of reviewing current behavioral studies, reports, and assessments in rodent models. Goals included: (a) identifying the maximal utility and limitations of behavior in animal models with construct validity; (b) providing recommendations for phenotyping animal models; and (c) guidelines on how in vivo models should be used and reported reliably and rigorously while acknowledging their limitations. We concluded by recommending minimal criteria for reporting in manuscripts going forward. The workshop elucidated a consensus of potential solutions to several problems, including revisiting claims made about animal model links to ASD (and related conditions). Specific conclusions included: mice (or other rodent or preclinical models) are models of the neurodevelopmental insult, not specifically any disorder (e.g., ASD); a model that perfectly recapitulates a disorder such as ASD is untenable; and greater attention needs be given to validation of behavioral testing methods, data analysis, and critical interpretation.

Synaptic dysfunction connects autism spectrum disorder and sleep disturbances: A perspective from studies in model organisms.

Sleep disturbances (SD) accompany many neurodevelopmental disorders, suggesting SD is a transdiagnostic process that can account for behavioral deficits and influence underlying neuropathogenesis. Autism Spectrum Disorder (ASD) comprises a complex set of neurodevelopmental conditions characterized by challenges in social interaction, communication, and restricted, repetitive behaviors. Diagnosis of ASD is based primarily on behavioral criteria, and there are no drugs that target core symptoms. Among the co-occurring conditions associated with ASD, SD are one of the most prevalent. SD often arises before the onset of other ASD symptoms. Sleep interventions improve not only sleep but also daytime behaviors in children with ASD. Here, we examine sleep phenotypes in multiple model systems relevant to ASD, e.g., mice, zebrafish, fruit flies and worms. Given the functions of sleep in promoting brain connectivity, neural plasticity, emotional regulation and social behavior, all of which are of critical importance in ASD pathogenesis, we propose that synaptic dysfunction is a major mechanism that connects ASD and SD. Common molecular targets in this interplay that are involved in synaptic function might be a novel avenue for therapy of individuals with ASD experiencing SD. Such therapy would be expected to improve not only sleep but also other ASD symptoms.

Investigating the relationships between resilience, autism-related quantitative traits, and mental health outcomes among adults during the COVID-19 pandemic.

Resilience is a dynamic process through which people adjust to adversity and buffer anxiety and depression. The COVID-19 global pandemic has introduced a shared source of adversity for people across the world, with detrimental implications for mental health. Despite the pronounced vulnerability of autistic adults to anxiety and depression during the COVID-19 pandemic, relationships among autism-related quantitative traits, resilience, and mental health outcomes have not been examined. As such, we aimed to describe the relationships between these traits in a sample enriched in autism spectrum-related quantitative traits during the COVID-19 pandemic. We also aimed to investigate the impact of demographic and social factors on these relationships. Across three independent samples of adults, we assessed resilience factors, autism-related quantitative traits, anxiety symptoms, and depression symptoms during the COVID-19 pandemic. One sample (recruited via the Autism Spectrum Program of Excellence, n = 201) was enriched for autism traits while the other two (recruited via Amazon Mechanical Turk, n = 624 and Facebook, n = 929) drew from the general population. We found resilience factors and quantitative autism-related traits to be inversely related, regardless of the resilience measure used. Additionally, we found that resilience factors moderate the relationship between autism-related quantitative traits and depression symptoms such that resilience appears to be protective. Across the neurodiversity spectrum, resilience factors may be targets to improve mental health outcomes. This approach may be especially important during the ongoing COVID-19 pandemic and in its aftermath.

Sufficient sleep duration in autistic children and the role of physical activity.

LAY ABSTRACT: Higher levels of physical activity may be associated with improved sleep in children, but this relationship is still being determined, especially in autistic children. In this study, we used existing data from the 2018 National Survey of Children's Health. Caregivers of children 6-17 years old, including caregivers of autistic children, completed a questionnaire that included questions about physical activity (days active in the past week) and sleep duration. We then determined if children were obtaining the recommended hours of sleep for their age (i.e. sufficient sleep). We found that higher physical activity levels were associated with sufficient sleep duration, but this finding was weaker in autistic children. In particular, this association was not observed in autistic children with more severe autism spectrum disorder, female autistic children, and autistic children 6-12 years old. In conclusion, physical activity is a promising approach to help children obtain sufficient sleep duration. However, more personalized approaches to improving sleep may be needed for certain groups of autistic children.

The relationship between autism spectrum and sleep-wake traits.

Autistic children and adults often have sleep disturbances, which may affect their and their family's quality of life. Yet, the relationship between sleep-wake patterns and autism spectrum traits is understudied. Identifying such relationships could lead to future research elucidating common mechanistic underpinnings. Thus, we aimed to determine whether sleep-wake patterns, specifically related to sleep, physical activity, and the daily sleep-wake rhythm (i.e., circadian rhythm), are associated with autism spectrum-related traits. Accelerometer-derived sleep-wake parameters were estimated in individuals with autistic spectrum traits and their family members (N = 267). We evaluated autism spectrum traits using the Social Responsiveness Scale (SRS) to assess the presence and severity of social impairment and the Behavior Rating Inventory of Executive Function (BRIEF) to assess executive function. The linear multivariate regression analysis (using SOLAR-Eclipse) showed that in adults, increased core autism spectrum traits and executive dysfunction were associated with disruption of several sleep-wake parameters, particularly related to the daily sleep-wake rhythm, and that executive dysfunction was associated with disrupted sleep quality and level of physical activity. We highlight the interplay between daytime function and disrupted sleep-wake patterns, specifically related to the daily sleep-wake rhythm, that could guide future research into common mechanisms. LAY SUMMARY: Autistic children and adults often report sleep disturbances. To dissect the relationship between a range of autism spectrum traits and sleep-wake patterns, we assessed social interaction and executive function in participants who also wore actimetry watches on their wrists to assess their sleep-wake patterns. We found that increased impairments in social and executive function occurred with increased sleep-wake disturbances, particularly those related to the circadian rhythm, suggesting that these perturbations/disruptions in the sleep-wake cycle could be connected to autism spectrum traits.

Using Adaptive Computer-based Instruction to Teach Staff to Implement a Social Skills Intervention.

This study evaluated the effectiveness of an adaptive, computer-based staff training software program called Train-to-Code (TTC) to teach the administration of a social skills intervention. The software program actively trained participants to identify whether video models illustrated each step of the procedure effectively or ineffectively. Multiple exemplars of each step of the social skills task analysis were represented. Most-to-least prompting as well as feedback and error correction were embedded into the software program and prompts were faded through seven levels as the participant reached criterion accuracy. A multiple-probe across participants design was used to evaluate the effectiveness of this program by comparing pre- and post-training in vivo probes conducted with a confederate learner. All participant scores increased from pre-training to post-training, indicating that Train-to-Code was effective at teaching administration of the social skills intervention. These results have implications for training staff in applied community settings. Due to Train-to-Code's ability to be internet-based and to measure actual viewing performance, it has the potential for "distance training" deliveries.

Heritability of quantitative autism spectrum traits in adults: A family-based study.

Autism spectrum disorder (ASD) comprises a multi-dimensional set of quantitative behavioral traits expressed along a continuum in autistic and neurotypical individuals. ASD diagnosis-a dichotomous trait-is known to be highly heritable and has been used as the phenotype for most ASD genetic studies. But less is known about the heritability of autism spectrum quantitative traits, especially in adults, an important prerequisite for gene discovery. We sought to measure the heritability of many autism-relevant quantitative traits in adults high in autism spectrum traits and their extended family members. Among adults high in autism spectrum traits (n = 158) and their extended family members (n = 245), we calculated univariate and bivariate heritability estimates for 19 autism spectrum traits across several behavioral domains. We found nearly all tested autism spectrum quantitative traits to be significantly heritable (h2  = 0.24-0.79), including overall ASD traits, restricted repetitive behaviors, broader autism phenotype traits, social anxiety, and executive functioning. The degree of shared heritability varied based on method and specificity of the assessment measure. We found high shared heritability for the self-report measures and for most of the informant-report measures, with little shared heritability among performance-based cognition tasks. These findings suggest that many autism spectrum quantitative traits would be good, feasible candidates for future genetics studies, allowing for an increase in the power of autism gene discovery. Our findings suggest that the degree of shared heritability between traits depends on the assessment method (self-report vs. informant-report vs. performance-based tasks), as well as trait-specificity. LAY SUMMARY: We found that the scores from questionnaires and tasks measuring different types of behaviors and abilities related to autism spectrum disorder (ASD) were heritable (strongly influenced by gene variants passed down through a family) among autistic adults and their family members. These findings mean that these scores can be used in future studies interested in identifying specific genes and gene variants that are associated with different behaviors and abilities related with ASD.

The early postpartum period - Differences between women with and without a history of depression.

Depression is a highly recurrent disorder. When in remission, it affords an important opportunity to understand the state-independent neurobiological alterations, as well as the socio-demographic characteristics, that likely contribute to the recurrence of major depressive disorder (MDD). The present study examined 110 euthymic women in their early postpartum period. A comparison was made between participants with (n = 20) and without (n = 90) a history of MDD by means of a multimodal approach including an fMRI experiment, assessment of hair cortisol concentration (HCC) and a clinical anamnestic interview. Women with a personal history of MDD were found to have decreased resting-state functional connectivity (RSFC) between the lateral parietal cortex (LPC) and the posterior cingulate cortex (PCC), and their Edinburgh Postnatal Depression Scale (EPDS) scores were significantly higher shortly after childbirth. More often than not, these women also had a family history of MDD. While women with no history of depression showed a negative association between hair cortisol concentration (HCC) and gray matter volume (GMV) in the medial orbitofrontal cortex (mOFC), the opposite trend was seen in women with a history of depression. This implies that women with remitted depression show distinctive neural phenotypes with subclinical residual symptoms, which likely predispose them to later depressive episodes.

Dynamic Eye Tracking as a Predictor and Outcome Measure of Social Skills Intervention in Adolescents and Adults with Autism Spectrum Disorder.

To evaluate an eye tracking task as a predictor and outcome measure of treatment response for autism spectrum disorder (ASD) social skills interventions, adolescents and young adults with ASD completed the eye tracking task before, immediately after, and two months after completing Social Cognition and Interaction Training for Autism (SCIT-A). The study compared SCIT-A participants (n = 20) to participants with ASD who received treatment as usual (TAU; n = 21). Overall, increased visual attention to faces and background objects and decreased attention to hands playing with toys at baseline were associated with improved social functioning immediately following intervention, suggesting this eye tracking task may reliably predict ASD social intervention outcomes.

Age- and sex-specific fear conditioning deficits in mice lacking Pcdh10, an Autism Associated Gene.

PCDH10 is a gene associated with Autism Spectrum Disorder. It is involved in the growth of thalamocortical projections and dendritic spine elimination. Previously, we characterized Pcdh10 haploinsufficient mice (Pcdh10+/- mice) and found male-specific social deficits and dark phase hypoactivity. Pcdh10+/- males exhibit increased dendritic spine density of immature morphology, decreased NMDAR expression, and decreased gamma synchronization in the basolateral amygdala (BLA). Here, we further characterize Pcdh10+/- mice by testing for fear memory, which relies on BLA function. We used both male and female Pcdh10+/- mice and their wild-type littermates at two ages, juvenile and adult, and in two learning paradigms, cued and contextual fear conditioning. We found that males at both ages and in both assays exhibited fear conditioning deficits, but females were only impaired as adults in the cued condition. These data are further evidence for male-specific alterations in BLA-related behaviors in Pcdh10+/- mice and suggest that these mice may be a useful model for dissecting male specific brain and behavioral phenotypes relevant to social and emotional behaviors.