Neural correlates of shared sensory symptoms in autism and attention-deficit/hyperactivity disorder

Machine learning model for reproducing subjective sensations and alleviating sound-induced stress in individuals with developmental disorders

Introduction

An everyday challenge frequently encountered by individuals with developmental disorders is auditory hypersensitivity, which causes distress in response to certain sounds and the overall sound environment. This study developed deep neural network (DNN) models to address this issue. One model predicts changes in subjective sound perception to quantify auditory hypersensitivity characteristics, while the other determines the modifications needed to sound stimuli to alleviate stress. These models are expected to serve as a foundation for personalized support systems for individuals with developmental disorders experiencing auditory hypersensitivity.

Methods

Experiments were conducted with participants diagnosed with autism spectrum disorder or attention deficit hyperactivity disorder who exhibited auditory hypersensitivity (the developmental disorders group, DD) and a control group without developmental disorders (the typically developing group, TD). Participants were asked to indicate either "how they perceived the sound in similar past situations" (Recollection task) or "how the sound should be modified to reduce stress" (Easing task) by applying various auditory filters to the input auditory stimulus. For both tasks, the DNN models were trained to predict the filter settings and subjective stress ratings based on the input stimulus, and the performance and accuracy of these predictions were evaluated.

Results

Three main findings were obtained. (a) Significant reductions in stress ratings were observed in the Easing task compared to the Recollection task. (b) The prediction models successfully estimated stress ratings, achieving a correlation coefficient of approximately 0.4 to 0.7 with the actual values. (c) Differences were observed in the performance of parameter predictions depending on whether data from the entire participant pool were used or whether data were analyzed separately for the DD and TD groups.

Discussion

These findings suggest that the prediction model for the Easing task can potentially be developed into a system that automatically reduces sound-induced stress through auditory filtering. Similarly, the model for the Recollection task could be used as a tool for assessing auditory stress. To establish a robust support system, further data collection, particularly from individuals with DD, is necessary.

Sensory seeking and its influence on sustained attention performance in adult males with Autism Spectrum Condition

Atypical sensory responses and seeking behaviors constitute the core symptoms of autism spectrum condition (ASC). There are possible links between atypical sensory profiles and attentional challenges in ASC. Due to the paucity of studies in adults, the nature of attentional challenges and their associations with sensory profiles in autistic adults remain elusive. Here, we investigated sustained attention performance and its associations with sensory profiles in 28 autistic adult males and 23 typically developing controls (TDCs). A gradual-onset continuous performance task and the Adolescent/Adult Sensory Profile were employed to assess sustained attention performance and sensory profiles, respectively. Our results revealed that the two groups exhibited comparable sustained attention performance quantified by d-prime. A statistically significant negative correlation between d-prime and sensory seeking was observed only in the ASC group. Moreover, an interaction effect of group-by-sensory seeking was observed in d-prime, suggesting a unique interplay between sensory profiles and attention in autistic individuals. In the ASC group, omission error rate and post-error slowing were statistically significantly associated with difficulties in social communication and interactions. These results contribute to understanding attentional processes in ASC and highlight the potential influence of sensory profiles on cognitive functions in this population.

Perceptual alterations in the relationship between sensory reactivity, intolerance of uncertainty, and anxiety in autistic children with and without ADHD

Sensory differences and anxiety disorders are highly prevalent in autistic individuals with and without ADHD. Studies have shown that sensory differences and anxiety are associated and that intolerance of uncertainty (IU) plays an important role in this relationship. However, it is unclear as to how different levels of the sensory processing pathway (i.e., perceptual, affective, or behavioral) contribute. Here, we used psychophysics to assess how alterations in tactile perception contribute to questionnaire measures of sensory reactivity, IU, and anxiety. Thirty-eight autistic children (aged 8-12 years; 27 with co-occurring ADHD) were included. Consistent with previous findings, mediation analyses showed that child-reported IU fully mediated an association between parent-reported sensory reactivity and parent-reported anxiety and that anxiety partially mediated an association between sensory reactivity and IU. Of the vibrotactile thresholds, only simultaneous frequency discrimination (SFD) thresholds correlated with sensory reactivity. Interestingly, we found that sensory reactivity fully mediated an association between SFD threshold and anxiety, and between SFD threshold and IU. Taken together, those findings suggest a mechanistic pathway whereby tactile perceptual alterations contribute to sensory reactivity at the affective level, leading in turn to increased IU and anxiety. This stepwise association can inform potential interventions for IU and anxiety in autism.

What is the best brain state to predict autistic traits?

Autism is a heterogeneous condition, and functional magnetic resonance imaging-based studies have advanced understanding of neurobiological correlates of autistic features. Nevertheless, little work has focused on the optimal brain states to reveal brain-phenotype relationships. In addition, there is a need to better understand the relevance of attentional abilities in mediating autistic features. Using connectome-based predictive modelling, we interrogate three datasets to determine scanning conditions that can boost prediction of clinically relevant phenotypes and assess generalizability. In dataset one, a sample of youth with autism and neurotypical participants, we find that a sustained attention task (the gradual onset continuous performance task) results in high prediction performance of autistic traits compared to a free-viewing social attention task and a resting-state condition. In dataset two, we observe the predictive network model of autistic traits generated from the sustained attention task generalizes to predict measures of attention in neurotypical adults. In dataset three, we show the same predictive network model of autistic traits from dataset one further generalizes to predict measures of social responsiveness in data from the Autism Brain Imaging Data Exchange. In sum, our data suggest that an in-scanner sustained attention challenge can help delineate robust markers of autistic traits and support the continued investigation of the optimal brain states under which to predict phenotypes in psychiatric conditions.

Probing Autism and ADHD subtypes using cortical signatures of the T1w/T2w-ratio and morphometry

Autism spectrum disorder (ASD) and attention-deficit/hyperactivity disorder (ADHD) are neurodevelopmental conditions that share genetic etiology and frequently co-occur. Given this comorbidity and well-established clinical heterogeneity, identifying individuals with similar brain signatures may be valuable for predicting clinical outcomes and tailoring treatment strategies. Cortical myelination is a prominent developmental process, and its disruption is a candidate mechanism for both disorders. Yet, no studies have attempted to identify subtypes using T1w/T2w-ratio, a magnetic resonance imaging (MRI) based proxy for intracortical myelin. Moreover, cortical variability arises from numerous biological pathways, and multimodal approaches can integrate cortical metrics into a single network. We analyzed data from 310 individuals aged 2.6-23.6 years, obtained from the Province of Ontario Neurodevelopmental (POND) Network consisting of individuals diagnosed with ASD (n = 136), ADHD (n = 100), and typically developing (TD) individuals (n = 74). We first tested for differences in T1w/T2w-ratio between diagnostic categories and controls. We then performed unimodal (T1w/T2w-ratio) and multimodal (T1w/T2w-ratio, cortical thickness, and surface area) spectral clustering to identify diagnostic-blind subgroups. Linear models revealed no statistically significant case-control differences in T1w/T2w-ratio. Unimodal clustering mostly isolated single individual- or minority clusters, driven by image quality and intensity outliers. Multimodal clustering suggested three distinct subgroups, which transcended diagnostic boundaries, showing separate cortical patterns but similar clinical and cognitive profiles. T1w/T2w-ratio features were the most relevant for demarcation, followed by surface area. While our analysis revealed no significant case-control differences, multimodal clustering incorporating the T1w/T2w-ratio among cortical features holds promise for identifying biologically similar subsets of individuals with neurodevelopmental conditions.

Connectome-based symptom mapping and in silico related gene expression in children with autism and/or attention-deficit/hyperactivity disorder

Clinical, neuroimaging and genomics evidence have increasingly underscored a degree of overlap between autism and attention-deficit/hyperactivity disorder (ADHD). This study explores the specific contribution of their core symptoms to shared biology in a sample of N=166 verbal children (6-12 years) with rigorously-established primary diagnoses of either autism or ADHD (without autism). We investigated the associations between inter-individual differences in clinician-based dimensional measures of autism and ADHD symptoms and whole-brain low motion intrinsic functional connectivity (iFC). Additionally, we explored their linked gene expression patterns in silico. Whole-brain multivariate distance matrix regression revealed a transdiagnostic association between autism severity and iFC of two nodes: the middle frontal gyrus of the frontoparietal network and posterior cingulate cortex of the default mode network. Across children, the greater the iFC between these nodes, the more severe the autism symptoms, even after controlling for ADHD symptoms. Results from segregation analyses were consistent with primary findings, underscoring the significance of internetwork iFC interactions for autism symptom severity across diagnoses. No statistically significant brain-behavior relationships were observed for ADHD symptoms. Genetic enrichment analyses of the iFC maps associated with autism symptoms implicated genes known to: (i) have greater rate of variance in autism and ADHD, and (ii) be involved in neuron projection, suggesting shared genetic mechanisms for this specific brain-clinical phenotype. Overall, these findings underscore the relevance of transdiagnostic dimensional approaches in linking clinically-defined phenomena to shared presentations at the macroscale circuit- and genomic-levels among children with diagnoses of autism and ADHD.

Comparing the stability and reproducibility of brain-behavior relationships found using canonical correlation analysis and partial least squares within the ABCD sample

Canonical correlation analysis (CCA) and partial least squares correlation (PLS) detect linear associations between two data matrices by computing latent variables (LVs) having maximal correlation (CCA) or covariance (PLS). This study compared the similarity and generalizability of CCA- and PLS-derived brain-behavior relationships. Data were accessed from the baseline Adolescent Brain Cognitive Development (ABCD) dataset (N > 9,000, 9-11 years). The brain matrix consisted of cortical thickness estimates from the Desikan-Killiany atlas. Two phenotypic scales were examined separately as the behavioral matrix; the Child Behavioral Checklist (CBCL) subscale scores and NIH Toolbox performance scores. Resampling methods were used to assess significance and generalizability of LVs. LV1 for the CBCL brain relationships was found to be significant, yet not consistently stable or reproducible, across CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 for the NIH brain relationships showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001). The current study suggests that stability and reproducibility of brain-behavior relationships identified by CCA and PLS are influenced by the statistical characteristics of the phenotypic measure used when applied to a large population-based pediatric sample.

A Shared Multivariate Brain-Behavior Relationship in a Transdiagnostic Sample of Adolescents

BACKGROUND

Internalizing and externalizing psychopathology typically present in early childhood and can have negative implications on general functioning and quality of life. Prior work has linked increased psychopathology symptoms with altered brain structure. Multivariate analysis such as partial least squares correlation can help identify patterns of covariation between brain regions and psychopathology symptoms. This study examined the relationship between gray matter volume (GMV) and psychopathology symptoms in adolescents with various psychiatric diagnoses.

METHODS

Structural magnetic resonance imaging data were collected from 490 participants with various internalizing and externalizing diagnoses (197 female/293 male; age = 14.68 ± 2.35 years; IQ = 104.05 ± 13.11). Cortical and subcortical volumes were parcellated using the Desikan-Killiany atlas. Partial least squares correlation was used to identify multivariate linear relationships between GMV and the Strength and Difficulties Questionnaire difficulties domains (emotional, peer, conduct, and hyperactivity issues). Resampling approaches were used to determine significance (permutation test), stability (bootstrap resampling), and reproducibility (split-half resampling) of identified relationships.

RESULTS

We found a significant, stable, and largely reproducible dimension that linked lower Strength and Difficulties Questionnaire scores (less impairment) across all difficulties domains with greater widespread GMV (singular value = 1.17, accounts for 87.1% of the covariance; p < .001). This dimension emphasized the relationship between lower conduct problems and greater GMV in frontotemporal regions.

CONCLUSIONS

Our results indicate that the most significant and stable brain-behavior relationship in a transdiagnostic sample is a domain-general relationship, linking lower psychopathology symptom scores to greater global GMV. This finding suggests that a shared brain-behavior relationship may be present across adolescents with and without clinically significant psychopathology symptoms.

Sensory Processing in Children and Adolescents with Neurofibromatosis Type 1

Despite the evidence of elevated autistic behaviors and co-occurring neurodevelopmental difficulties in many children with neurofibromatosis type 1 (NF1), we have a limited understanding of the sensory processing challenges that may occur with the condition. This study examined the sensory profile of children and adolescents with NF1 and investigated the relationships between the sensory profiles and patient characteristics and neuropsychological functioning. The parent/caregivers of 152 children with NF1 and 96 typically developing children completed the Sensory Profile 2 (SP2), along with standardized questionnaires assessing autistic behaviors, ADHD symptoms, internalizing symptoms, adaptive functioning, and social skills. Intellectual functioning was also assessed. The SP2 data indicated elevated sensory processing problems in children with NF1 compared to typically developing children. Over 40% of children with NF1 displayed differences in sensory registration (missing sensory input) and were unusually sensitive to and unusually avoidant of sensory stimuli. Sixty percent of children with NF1 displayed difficulties in one or more sensory modalities. Elevated autistic behaviors and ADHD symptoms were associated with more severe sensory processing difficulties. This first detailed assessment of sensory processing, alongside other clinical features, in a relatively large cohort of children and adolescents with NF1 demonstrates the relationships between sensory processing differences and adaptive skills and behavior, as well as psychological well-being. Our characterization of the sensory profile within a genetic syndrome may help facilitate more targeted interventions to support overall functioning.

Qualitative and quantitative analysis of self-care regarding sensory issues among people with neurodevelopmental disorders

Introduction

Issues in sensory processing (hereafter, sensory issues) associated with neurodevelopmental disorders are known to be particularly prominent from 6 to 9 years of age and are a critical issue in school life. These issues affect each individual's quality of life. Some of the issues are known to be relieved by self-care while some are not.

Methods

To clarify the sensory issues that cannot be managed by self-care, this study examined self-care for sensory issues among people with neurodevelopmental disorders using a web survey. The survey encompassed questions about neurodevelopmental disorders, the sensory issues individuals experience, and the kind of self-care they perform. In the qualitative analysis, each was categorized by the type of sensory modality; we further scrutinized the descriptions of self-care, which were collected simultaneously, and examined how each problem was addressed.

Results

Self-care was categorized as "physically blocking," "leaving from," "relaxing," "devising," "help from others," "taking medication," "coping with body," "others," or "could not cope." Based on these findings, we quantitatively compared the frequency of sensory issues that could and could not be managed by self-care. Consequently, significantly higher percentages of the participants stated that they experienced difficulties in managing problems about "body representations," "contact with humans," "selective listening," and "force control." In contrast, significantly more participants stated that they could manage problems related to "loud sound" and "dazzling".

Conclusion

In this study, qualitative analysis allowed us to categorize methods of self-care for sensory issues, and quantitative research allowed us to identify issues that were difficult to manage. While it was possible to manage strong light and sound using sunglasses, earplugs, and so on, problems related to the senses of proprioception, selective attention, and so on were clearly difficult to manage.

Comparing the stability and reproducibility of brain-behaviour relationships found using Canonical Correlation Analysis and Partial Least Squares within the ABCD Sample

Introduction

Canonical Correlation Analysis (CCA) and Partial Least Squares Correlation (PLS) detect associations between two data matrices based on computing a linear combination between the two matrices (called latent variables; LVs). These LVs maximize correlation (CCA) and covariance (PLS). These different maximization criteria may render one approach more stable and reproducible than the other when working with brain and behavioural data at the population-level. This study compared the LVs which emerged from CCA and PLS analyses of brain-behaviour relationships from the Adolescent Brain Cognitive Development (ABCD) dataset and examined their stability and reproducibility.

Methods

Structural T1-weighted imaging and behavioural data were accessed from the baseline Adolescent Brain Cognitive Development dataset (N > 9000, ages = 9-11 years). The brain matrix consisted of cortical thickness estimates in different cortical regions. The behavioural matrix consisted of 11 subscale scores from the parent-reported Child Behavioral Checklist (CBCL) or 7 cognitive performance measures from the NIH Toolbox. CCA and PLS models were separately applied to the brain-CBCL analysis and brain-cognition analysis. A permutation test was used to assess whether identified LVs were statistically significant. A series of resampling statistical methods were used to assess stability and reproducibility of the LVs.

Results

When examining the relationship between cortical thickness and CBCL scores, the first LV was found to be significant across both CCA and PLS models (singular value: CCA = .13, PLS = .39, p < .001). LV1 from the CCA model found that covariation of CBCL scores was linked to covariation of cortical thickness. LV1 from the PLS model identified decreased cortical thickness linked to lower CBCL scores. There was limited evidence of stability or reproducibility of LV1 for both CCA and PLS. When examining the relationship between cortical thickness and cognitive performance, there were 6 significant LVs for both CCA and PLS (p < .01). The first LV showed similar relationships between CCA and PLS and was found to be stable and reproducible (singular value: CCA = .21, PLS = .43, p < .001).

Conclusion

CCA and PLS identify different brain-behaviour relationships with limited stability and reproducibility when examining the relationship between cortical thickness and parent-reported behavioural measures. However, both methods identified relatively similar brain-behaviour relationships that were stable and reproducible when examining the relationship between cortical thickness and cognitive performance. The results of the current study suggest that stability and reproducibility of brain-behaviour relationships identified by CCA and PLS are influenced by characteristics of the analyzed sample and the included behavioural measurements when applied to a large pediatric dataset.

Identifying Replicable Subgroups in Neurodevelopmental Conditions Using Resting-State Functional Magnetic Resonance Imaging Data

Importance

Neurodevelopmental conditions, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and obsessive-compulsive disorder (OCD), have highly heterogeneous and overlapping phenotypes and neurobiology. Data-driven approaches are beginning to identify homogeneous transdiagnostic subgroups of children; however, findings have yet to be replicated in independently collected data sets, a necessity for translation into clinical settings.

Objective

To identify subgroups of children with and without neurodevelopmental conditions with shared functional brain characteristics using data from 2 large, independent data sets.

Design, Setting, and Participants

This case-control study used data from the Province of Ontario Neurodevelopmental (POND) network (study recruitment began June 2012 and is ongoing; data were extracted April 2021) and the Healthy Brain Network (HBN; study recruitment began May 2015 and is ongoing; data were extracted November 2020). POND and HBN data are collected from institutions across Ontario and New York, respectively. Participants who had diagnoses of ASD, ADHD, and OCD or were typically developing (TD); were aged between 5 and 19 years; and successfully completed the resting-state and anatomical neuroimaging protocol were included in the current study.

Main Outcomes and Measures

The analyses consisted of a data-driven clustering procedure on measures derived from each participant's resting-state functional connectome, performed independently on each data set. Differences between each pair of leaves in the resulting clustering decision trees in the demographic and clinical characteristics were tested.

Results

Overall, 551 children and adolescents were included from each data set. POND included 164 participants with ADHD; 217 with ASD; 60 with OCD; and 110 with TD (median [IQR] age, 11.87 [9.51-14.76] years; 393 [71.2%] male participants; 20 [3.6%] Black, 28 [5.1%] Latino, and 299 [54.2%] White participants) and HBN included 374 participants with ADHD; 66 with ASD; 11 with OCD; and 100 with TD (median [IQR] age, 11.50 [9.22-14.20] years; 390 [70.8%] male participants; 82 [14.9%] Black, 57 [10.3%] Hispanic, and 257 [46.6%] White participants). In both data sets, subgroups with similar biology that differed significantly in intelligence as well as hyperactivity and impulsivity problems were identified, yet these groups showed no consistent alignment with current diagnostic categories. For example, there was a significant difference in Strengths and Weaknesses ADHD Symptoms and Normal Behavior Hyperactivity/Impulsivity subscale (SWAN-HI) between 2 subgroups in the POND data (C and D), with subgroup D having increased hyperactivity and impulsivity traits compared with subgroup C (median [IQR], 2.50 [0.00-7.00] vs 1.00 [0.00-5.00]; U = 1.19 × 104; P = .01; η2 = 0.02). A significant difference in SWAN-HI scores between subgroups g and d in the HBN data was also observed (median [IQR], 1.00 [0.00-4.00] vs 0.00 [0.00-2.00]; corrected P = .02). There were no differences in the proportion of each diagnosis between the subgroups in either data set.

Conclusions and Relevance

The findings of this study suggest that homogeneity in the neurobiology of neurodevelopmental conditions transcends diagnostic boundaries and is instead associated with behavioral characteristics. This work takes an important step toward translating neurobiological subgroups into clinical settings by being the first to replicate our findings in independently collected data sets.

Qualitative and quantitative analysis of self-reported sensory issues in individuals with neurodevelopmental disorders

INTRODUCTION

Individuals with neurodevelopmental disorders, such as autism spectrum disorder (ASD), attention-deficit/hyperactivity disorder (ADHD), and specific learning disorders (SLD) have various types of sensory characteristics.

METHODS

This study investigated sensory issues in individuals with neurodevelopmental disorders using a web-based questionnaire for qualitative and quantitative analysis, categorized the contents of their three most distressful sensory issues, and evaluated their order of priority.

RESULTS

Auditory problems were reported as the most distressing sensory issue among the participants. In addition to auditory problems, individuals with ASD frequently reported more tactile problems, and individuals with SLD reported more visual problems. Among the individual sensory issues, in addition to aversion to sudden, strong, or specific stimuli, some participants reported confusions regarding multiple stimuli presenting concurrently. Additionally, the sensory issues related to foods (i.e., taste) was relatively more common in the minor group.

CONCLUSION

These results suggest that the diversity of sensory issues experienced should be carefully considered when aiding persons with neurodevelopmental disorders.

Emotional and sensory dysregulation as a possible missing link in attention deficit hyperactivity disorder: A review

Attention Deficit Hyperactivity Disorder (ADHD) is a common developmental disorder affecting 5-7% of adults and children. We surveyed the literature to examine ADHD through three pillars: developmental characteristics, symptomatology, and treatment strategies. Firstly, in terms of developmental characterstics, early life stress may increase the risk of developing ADHD symptoms according to animal models' research. Secondly, the current core symptoms of ADHD are comprised of inattention, hyperactivity, and impulsivity. However, the up-to-date literature indicates individuals with ADHD experience emotional and sensory dysregulation as well, which early-life stress may also increase the risk of. Finally, we discuss the therapeutic benefits of methylphenidate on both the current core ADHD symptoms and the sensory and emotional dysregulation found in those with ADHD. In summation, we surveyed the recent literature to analyze (i) the potential role of early-life stress in ADHD development, (ii) the involvement of emotional and sensory dysregulation in ADHD symptomatology and finally, (iii) the therapeutic intervention with methylphenidate, aiming to reduce the potential effect of early life stress in ADHD, and mainly emotional and sensory dysregulation. The apparent but currently less recognized additional symptoms of emotional and sensory dysregulation in ADHD call for further investigation of these possible causes and thus increasing treatments efficacy in individuals with ADHD.

Autistic children and adolescents with frequent restricted interest and repetitive behavior showed more difficulty in social cognition during mask-wearing during the COVID-19 pandemic: a multisite survey

BACKGROUND

The public health measures enacted in order to control the coronavirus disease (COVID-19) pandemic have caused considerable changes to daily life. For autistic children and adolescents, adapting to the "new normal," including mask-wearing, may be difficult because of their restricted interest and repetitive behavior (RRB) characteristics. We aimed to examine the relationships between RRB characteristics and the impact of mask-wearing on their social communications during the pandemic.

METHODS

We recruited participants with a clinical diagnosis of autism spectrum disorder based on DSM-5 diagnostic criteria from two outpatient clinics in Tokyo, Japan, between November 2020 and April 2021 using a convenience sampling methodology. As a result, the participants consisted of 102 children and adolescents (mean (SD) age = 11.6 (5.3)). We collected data on RRB characteristics frequency before and during the pandemic using the CoRonavIruS Health Impact Survey (CRISIS) - Adapted for Autism and Related Neurodevelopmental conditions (AFAR). We then conducted factor analyses to compute the RRB severity composite scores, which are divided into lower- (e.g., sensory seeking), and higher-order (e.g., restricted interest). We also investigated mask-wearing culture using a bespoke questionnaire, and using Spearman's rank correlation analyses, we examined the relationships between before pandemic RRB characteristics, and the impact of mask-wearing on social communications during the pandemic.

RESULTS

We found that children and adolescents who exhibited lower-order RRB before the pandemic had difficulties in going-out with mask-wearing (rho = -0.25, q = .031), more challenges with mask-wearing (rho =  - 0.34, q = .0018), and difficulty in referring to others' emotions while wearing masks (rho =  - 0.36, q = .0016). We also found an association between higher-order RRB before the pandemic and an uncomfortable sensation (rho =  - 0.42, q = .0002) and difficulties in referring to other's emotions while wearing masks (rho =  - 0.25, q = .031).

CONCLUSIONS

We revealed that various behaviors, such as sensory seeking, repetitive motor mannerisms and movements, and rituals and routines, undertaken before the pandemic could be important predictors of difficulties with mask-wearing and social communication for autistic children and adolescents during the pandemic. Caregivers and teachers wearing masks may need to provide extra support for social communication to autistic children and adolescents showing RRB characteristics frequently.

Ultrasonic bone age fractionates cognitive abilities in adolescence

Adolescent development is not only shaped by the mere passing of time and accumulating experience, but it also depends on pubertal timing and the cascade of maturational processes orchestrated by gonadal hormones. Although individual variability in puberty onset confounds adolescent studies, it has not been efficiently controlled for. Here we introduce ultrasonic bone age assessment to estimate biological maturity and disentangle the independent effects of chronological and biological age on adolescent cognitive abilities. Comparing cognitive performance of female participants with different skeletal maturity we uncover the impact of biological age on both IQ and specific abilities. We find that biological age has a selective effect on abilities: more mature individuals within the same age group have higher working memory capacity and processing speed, while those with higher chronological age have better verbal abilities, independently of their maturity. Based on our findings, bone age is a promising biomarker of adolescent maturity.

Intergroup bias in punishing behaviors of adults with autism spectrum disorder

Groups are essential elements of society, and humans, by nature, commonly manifest intergroup bias (i.e., behave more positively toward an ingroup member than toward an outgroup member). Despite the growing evidence of various types of altered decision-making in individuals with autism spectrum disorder (ASD), their behavior under the situation involving group membership remains largely unexplored. By modifying a third-party punishment paradigm, we investigated intergroup bias in individuals with ASD and typical development (TD). In our experiment, participants who were considered as the third party observed a dictator game wherein proposers could decide how to distribute a provided amount of money while receivers could only accept unconditionally. Participants were confronted with two different group situations: the proposer was an ingroup member and the recipient was an outgroup member (IN/OUT condition) or the proposer was an outgroup member and the recipient was an ingroup member (OUT/IN condition). Participants with TD punished proposers more severely when violating social norms in the OUT/IN condition than in IN/OUT condition, indicating that their decisions were influenced by the intergroup context. This intergroup bias was attenuated in individuals with ASD. Our findings deepen the understanding of altered decision-making and socioeconomic behaviors in individuals with ASD.

Atypical Integration of Sensory-to-Transmodal Functional Systems Mediates Symptom Severity in Autism

A notable characteristic of autism spectrum disorder (ASD) is co-occurring deficits in low-level sensory processing and high-order social interaction. While there is evidence indicating detrimental cascading effects of sensory anomalies on the high-order cognitive functions in ASD, the exact pathological mechanism underlying their atypical functional interaction across the cortical hierarchy has not been systematically investigated. To address this gap, here we assessed the functional organisation of sensory and motor areas in ASD, and their relationship with subcortical and high-order trandmodal systems. In a resting-state fMRI data of 107 ASD and 113 neurotypical individuals, we applied advanced connectopic mapping to probe functional organization of primary sensory/motor areas, together with targeted seed-based intrinsic functional connectivity (iFC) analyses. In ASD, the connectopic mapping revealed topological anomalies (i.e., excessively more segregated iFC) in the motor and visual areas, the former of which patterns showed association with the symptom severity of restricted and repetitive behaviors. Moreover, the seed-based analysis found diverging patterns of ASD-related connectopathies: decreased iFCs within the sensory/motor areas but increased iFCs between sensory and subcortical structures. While decreased iFCs were also found within the higher-order functional systems, the overall proportion of this anomaly tends to increase along the level of cortical hierarchy, suggesting more dysconnectivity in the higher-order functional networks. Finally, we demonstrated that the association between low-level sensory/motor iFCs and clinical symptoms in ASD was mediated by the high-order transmodal systems, suggesting pathogenic functional interactions along the cortical hierarchy. Findings were largely replicated in the independent dataset. These results highlight that atypical integration of sensory-to-high-order systems contributes to the complex ASD symptomatology.