Molecular Autism

Sensory processing differences are a core feature of autism, affecting 60-95% of individuals, yet the associated neural mechanisms remain unclear. An excitation-inhibition (E/I) imbalance in brain circuits has been proposed, but in vivo evidence linking genetic variation in E/I pathways, regional neurochemistry, neural circuit function, and sensory behaviour has been lacking. Here we performed a multimodal investigation in 206 individuals (130 autistic), integrating gene-set polygenic scores for excitatory glutamatergic and inhibitory gamma-aminobutyric acid (GABA)-ergic pathways, magnetic resonance spectroscopy (MRS) measures of regional GABA and Glx (glutamate + glutamine) levels, vibrotactile psychophysical measures of tactile perception, and questionnaire measures of behavioural sensory reactivity. We found that glutamatergic polygenic scores predicted thalamic glutamate levels in neurotypical but not autistic individuals, suggesting altered genotype-neurochemistry coupling in autism. Thalamic Glx:GABA levels associated with tactile perception in both groups, but with opposing directions of effect, indicating that autistic and neurotypical individuals achieve similar perceptual outcomes with potentially differing thalamocortical circuit mechanisms. Within autistic individuals, tactile perceptual differences further related to behavioural sensory reactivity. Together, these findings suggest that autistic sensory processing potentially relies on distinct circuit mechanisms linking genetic variation, neurochemistry and perception. This work thus has important implications for how sensory differences are conceptualised, studied, and interpreted, and ultimately for how interventions and support are developed.

Phelan-McDermid syndrome (PMS) is a genetic neurodevelopmental disorder caused by a microdeletion within chromosome 22q13.3 1-6, and accounts for [~]1-3% of cases of autism spectrum disorders (ASD). Individuals with PMS typically present with neonatal hypotonia, severe speech delay, intellectual disability, motor impairments, and autism-related features, although additional manifestations such as epilepsy, sleep disturbances, and developmental regression are common. As in ASD, there is considerable heterogeneity in cognitive and behavioral impairments in PMS, making it difficult to determine which features arise directly from SHANK3/Shank3 deficiency and how deficits manifest across development. In the present study, we transferred the targeted Shank3 mutation, previously characterized on the Sprague Dawley background, onto the Long-Evans strain and performed a longitudinal behavioral assessment of Shank3-deficient rats from infancy to adulthood. The rats were evaluated for delays in early sensory and motor development, and ultrasonic vocalizations as neonates, social behavior, short term memory and gait as juveniles, and cognitive-executive dysfunction using a touchscreen-based visual discrimination and reversal learning task as adults. Despite profound reductions and/or complete loss of Shank3 protein expression, heterozygous and homozygous male and female rats showed normal physical and neurological reflexes across development, yet female Shank3 knockout pups showed a selective reduction in distress-associated ultrasonic vocalizations. As juveniles, subtle abnormalities emerged in short-term memory and limb coordination, while social preference for novelty and recognition was normal. Prominent behavioral abnormalities were observed in adults characterized by rapid and error-prone responding to visual stimuli during discrimination learning and reversal. These data suggest that rats with complete or partial Shank3 deficiency produce a selective behavioral profile in which high-order cognitive dysfunction is more pronounced than deficits in basic sensorimotor or select social behaviors. More broadly, these findings highlight executive dysfunction as a key consequence of the loss of Shank3. For the first time, we report the loss of Shank3 expression on a Long-Evans background strain as a valuable translational tool for investigating cognitive dysfunction and therapeutic windows in Shank3-associated disorders.

Background: Previous large-scale structural MRI analyses of the brain in autism have identified gray matter (GM) differences when using region-of-interest analyses based on gross anatomical regions. However, such analyses have limited spatial specificity for localizing neuroanatomical alterations and may obscure subtle, spatially focal differences. Whole brain voxel-based morphometry (VBM) analyses enable greater spatial precision for localizing GM and white matter (WM) alterations in autism. Purpose: To rigorously identify voxel-wise GM and WM volume differences in autism in the largest VBM mega-analysis to date. Materials and Methods: This retrospective mega-analysis included structural 3D volumetric T1-weighted MRI brain scans from 3,051 participants (1,519 autism; 1,532 neurotypicals) collected across 51 sites/scanners. Voxel-wise GM and WM volumes were quantified using the ENIGMA CAT12 VBM pipeline. Linear mixed-effects regression was performed at each voxel to evaluate the association between diagnostic group and voxel-wise volume while adjusting for standard nuisance covariates Results: A total of 3,051 participants (15.0 {+/-} 8.2 yrs; 2,342 male) were included in the study. Autism was associated with widespread lower GM volume involving cortical, subcortical, and cerebellar regions. The most extensive alterations in autism were detected in the orbitofrontal cortex, amygdala, thalamus, and posterior lobes of the cerebellum. WM volume was lower in autism across major projection, commissural, association, and cerebellar/brainstem tracts, including the corona radiata, internal capsule, corpus callosum, and cerebellar peduncles. These findings remained consistent in sensitivity analyses, including the application of increasingly strict motion exclusion criteria. Conclusion: Autism is associated with smaller voxel-wise GM and WM volume involving widespread cortical, subcortical, and cerebellar regions. Our findings remained robust across supplementary analyses and provide high-resolution localization of structural brain differences in autism. These findings support the involvement of distributed neural systems underlying reward processing, sensory integration, and motor functioning in autism.

Communication deficits are a defining feature of autism spectrum disorder (ASD) and among the earliest detectable markers of atypical neurodevelopment. Yet how specific genetic ASD risk factors shape the developmental trajectory of vocal communication remains poorly understood. Fragile X syndrome (FXS) is the most common inherited cause of ASD, resulting from the transcriptional silencing of the FMR1 gene, and a majority of FXS individuals exhibit impaired language development and atypical vocal communication. Rodent ultrasonic vocalizations (USVs) produced during maternal isolation provide a tractable model for studying the developmental trajectory of early vocal communication in FXS. Here, we characterized isolation- induced USVs in Fmr1 knockout (KO) and littermate wildtype (WT) rats from postnatal days 3- 21 to determine whether Fmr1 mutation disrupts the acoustic structure, temporal organization, or sequential syntax of USVs across postnatal development. We found that Fmr1 KO rat pups exhibited reduced call number during the peak developmental window for isolation-induced calling (p6-p10), while acoustic structure and temporal organization were largely preserved. Network analysis of call transitions revealed that WT pups exhibited a progressive increase in syntactic complexity from p3-p10. However, this developmental trajectory was significantly altered and delayed in Fmr1 KO pups. Together, these findings demonstrate that Fmr1 mutation not only disrupts vocal production but the developmental expansion of syntactic flexibility in rats, highlighting USV syntax as a sensitive marker of atypical communicative development in FXS models.

Background The global prevalence of autism spectrum disorder (ASD) has significantly increased over the past two decades. Despite substantial research advances, critical aspects, including etiology, diagnostic biomarkers, and pharmacological interventions, remain incompletely elucidated. This persistent knowledge gap warrants systematic mapping of the field's evolution to inform future research priorities. Methods A bibliometric analysis of ASD-related publications indexed in Web of Science was conducted from January 2020 to May 2025. Following a systematic deduplication process, original articles, reviews, case reports, and clinical trials were included in the analysis. The analytical framework comprised co-authorship networks, institutional collaboration patterns, national research contributions, and keyword co-occurrence structures, all of which were examined using CiteSpace (version 5.8.R3) and VOSviewer. Results After deduplication, 8,162 publications (January 2020-May 2025) were analyzed. The annual output grew steadily, confirming ASD as a sustained priority in neuroscience. Research remains academia-driven, led by the United States, with China as the second-largest contributor. Chinese institutions place greater emphasis on mechanistic and developmental phenotyping, which aligns with national priorities. These studies maintain strong methodological rigor, and their growing volume underscores the central role of ASD in translational neuroscience. Conclusion Future research on ASD should focus on strengthening case identification, refining clinical phenotyping, and expanding large-scale cohort studies to advance our understanding of its etiology and identify reliable diagnostic biomarkers. It is equally important to develop and evaluate targeted interventions for core symptoms and integrate telemedicine into service delivery models. A critical yet understudied priority is improving the quality of life for autistic individuals and their families, an area in which research globally, including in China, requires greater depth and consistency. With China's growing investment in autism research, it is well-positioned to contribute to these pressing international challenges.

Importance There is increasing interest in the potential of psilocybin to treat mental health and neurodevelopmental conditions. At high doses, the therapeutic benefit of psilocybin is linked to greater functional connectivity or integration between large-scale brain networks which underpin mood, emotion and cognition. However, it is unknown how the brain responds to psilocybin in autism - a condition characterised by both altered functional connectivity and differential response to drugs. Thus, a first step before clinical trials of psilocybin involving autistic people, is to evaluate the response of the autistic brain to psilocybin, initially at low dose. Objective Low doses of psilocybin were used to test the hypothesis that the functional connectivity of large-scale resting-state brain networks respond differently in autistic and non-autistic adults. Design The PSILAUT study had a pseudo-randomised, cross-over, double-blind, case-control design. There was no evaluation of clinical efficacy. PSILAUT was not a Clinical Trial according to UK regulations. Data collection was conducted from January 2023 to August 2024. Setting Single-centre, study conducted at the Institute of Psychiatry, Psychology & Neuroscience, Kings College London, London, United Kingdom. Participants Adult (> 18 years) participants with and without an autism spectrum disorder (ASD) diagnosis were recruited and matched for age, sex and IQ. Autistic participants were included if they had an existing diagnosis (DSM-IV, DSM-5 or ICD-10 criteria). Exposures A single oral dose of 2 or 5 mg psilocybin or (inactive) placebo administered on separate visits at least one week apart. Main Outcomes and Measures Resting-state fMRI was acquired to investigate the change in functional connectivity within and between brain networks, as measures of network integrity and integration, respectively. Results A total of 67 participants were recruited (18-58 years at first visit; 30 non-autistic participants, mean [SD] age, 30.0 [8.3] years, 15 males [50%] and 37 autistic participants, mean [SD] age, 28.6 [9.2] years, 19 males [51%]). We report for the first time that the autistic brain responds differently to low doses of psilocybin, despite no group differences in network connectivity in the baseline placebo condition. 5 mg psilocybin elicited the greatest shifts in functional connectivity in both groups, but in different directions. In non-autistic participants only, on average, after 5 mg psilocybin within-network connectivity of the frontoparietal ({beta} = -0.053, T = -2.73, FDR-corrected P value = 0.027, Cohen d = -0.71) and limbic networks ({beta} = -0.087, T = -2.59, FDR-corrected P value = 0.021, Cohen d = -0.61) decreased. In contrast, in autistic participants, 5 mg psilocybin increased between-network connectivity (i.e. integration) of higher-order and attentional networks, but decreased connectivity between the same networks in non-autistic participants (default mode and frontoparietal networks, dose x group interaction: {beta} = 0.053, T = 2.91, FDR-corrected P value = 0.042; dorsal and ventral attention networks, dose x group interaction: {beta} = 0.059, T = 2.31, FDR-corrected P value = 0.015). Across the whole sample, the extent to which psilocybin elicited an increase in connectivity between higher-order ({beta} = 0.33, T = 2.16, FDR-corrected P value = 0.036) and attentional ({beta} = 0.36, T = 2.43, FDR-corrected P value = 0.036) networks was positively correlated with core autistic traits quantified using the Autism Quotient. Conclusions and Relevance Functional brain networks that support mood, emotion and cognition are more responsive to low dose psilocybin in autistic adults compared to non-autistic adults. Given that increased network integration is associated with clinical utility, future applications of psilocybin in autistic people should include the evaluation of low doses.

Background: Autism spectrum disorder is a prevalent neurodevelopmental condition featuring marked social difficulties. Oxytocin supplementation shows promising therapeutic efficacy in alleviating autism-like traits in rodent models, but clinical effects in humans remain inconsistent. The rodent-derived social salience network (SSN) comprises several oxytocin-modulated brain regions implicated in social behavior, but its conservation has not been established in humans. Here we assess, for the first time, functional connectivity (FC) within a homologous human SSN in autistic men to examine its relationship with behavioral traits and modulation by oxytocin. Methods: The human SSN atlas was collated from open-access cortical and subcortical parcellations, and used to retrospectively analyze a resting-state fMRI dataset of adult men with autism from a previously published, randomized, placebo-controlled oxytocin trial. SSN-wide and sub-network ROI-to-ROI FC correlations with social trait expression and salivary oxytocin concentrations were performed at baseline and post-administration. Treatment specific outcomes on FC were calculated using ANCOVA. Results: We observed SSN sub-network FC correlations with social and repetitive behavioral scores and identified strong oxytocin sensitivity of nucleus accumbens-somatosensory and paraventricular nucleus-somatosensory circuits at baseline. Following nasal spray administration, a strengthening of amygdala-somatosensory circuit was detected as the largest oxytocin-induced FC shift. Notably, baseline connectivity within this circuit strongly predicted treatment response, with individuals having lower baseline FC showing greater post-treatment FC. Conclusions: These findings provide first evidence for clinical relevance of the SSN in humans with autism and highlight circuits that may represent promising biomarkers for predicting oxytocin responsiveness.

Autism spectrum disorder (ASD) is one of the most common neurodevelopmental disorders. The absence of a clear aetiology strengthens the need to identify quantitative biomarkers capable of diagnosing the condition and assessing the severity of symptoms. We implemented a normative modelling framework based on EEG effective connectivity (EC), leveraging recordings collected in three centers, in typical development (TD) and ASD participants with age spanning from 5 to 19 years. Deviations from the normative evolution were tested as ASD biomarkers, compared with standard EC metrics. Normative EC metrics supported accurate classification of ASD vs TD participants (0.82 AUC), reaching 0.95 AUC when combined with behavioral subscales, significantly outperforming a classification based on behavioral data alone. In ASD participants, selected metrics in the Temporo-Parietal-Frontal network predicted social responsiveness scale (SRS) values with high significance (SRS Total R^2=0.42, p=0.0005). These results suggest that normative EC values constitute robust and generalizable ASD biomarkers.

Introduction: Autism spectrum disorder, or autism, is a common neurodevelopmental condition characterized by socio-communicative problems together with restrictive and repetitive behaviors. Typically, the latter is manifested as deficits in behavioral flexibility, i.e. changing routine behaviors to adapt to environmental changes. Despite noticeable difficulties with flexible behavior in autism, there is to date not adequate knowledge about the intricacies of such challenges and neurobiological processes that may subserve them. This study aims to investigate both cognitive and motor flexibility in autistic compared with neurotypical adults using a novel combination of detailed methods for brain imaging and behavioral investigations in relation to probabilistic reversal learning (PRL) paradigms. In addition, the experiences of autistic adults on flexible behavior in education and everyday activities will be explored. Methods and analysis: Differences in cognitive flexibility between autistic (n[≥]20) and neurotypical (n[≥]20) adults (18-35 years) will be investigated in terms of brain activations, measured by functional magnetic resonance imaging (fMRI), during two-choice PRL performance (cognitive task). In addition, group differences in microcirculation as measured by arterial spin labelling (ASL) will be evaluated. Group differences in motor flexibility will be investigated as expressed in movement planning and execution (spatio-temporal parameters), measured by a robotic manipulandum platform (KinArm End-Point Robot), during two-choice PRL performance (motor task). Semi-structured interviews will be conducted individually with autistic participants (n=15). Questions concern own experiences of cognitive and motor behavior, and strategies used to support flexibility in these behaviors. Data from this qualitative approach will be analyzed by thematic analysis. Ethics and dissemination: Ethical approval has been obtained from the Swedish Ethical Review Authority (ref:2025-07939-01) and the study will be conducted in accordance with the Declaration of Helsinki, the European Union General Data Protection Regulation (GDPR) and national guidelines for the storing of personal data. The different investigations included are well-established, non-invasive and safe. Study outcomes will be published in peer-reviewed international scientific journals (open access), presented at national and international conferences, and to any interested audience/stakeholders.

Although language acquisition delays are frequently observed in children with autism spectrum disorder (autism), our current understanding of the neurobiological mechanisms underlying language development in autism is sparse. Previous studies have found resting-state electroencephalography (EEG) power to be associated with language abilities in autistic children. However, longitudinal studies examining resting-state EEG phase coherence in relation to language development in preschool-aged children with autism are limited. This study aimed to characterize age- and group-related changes in whole-brain coherence in neurotypical children and in autistic children with and without language delay. Resting-state EEG and language data were collected at 2, 3, and 4 years of age. Peak phase coherence within the alpha band (6-11 Hz) was calculated at each timepoint and differences in the developmental trajectory of peak alpha coherence (PAC) were analyzed. In neurotypical children, PAC increased between 2 and 4 years of age. In contrast, PAC did not significantly change with age in children with autism. However, when examining autistic children based on language delay status, PAC increased with age in autistic children without language delay, but not in children with language delay. Exploratory analysis revealed evidence for an interaction between PAC and age, suggesting that the direction of the association between PAC and VDQ varied across age. Overall, these results support previous findings of altered oscillatory connectivity in autism and suggest that differences become apparent early in development. Importantly, phase coherence may not only differentiate diagnostic groups but also capture meaningful variability within the autism group. Future research should further investigate the use of EEG coherence as a biomarker of language development in autism.

Background: Sleep disruption is prevalent in people with neurodevelopmental disorders such as autism but is not clear whether it occurs as an endophenotype or secondary to other behaviours. The ABCD Study is a population-based longitudinal study that monitors the health, demography and lifestyle of over 11,000 children in the US. In this study we leverage these data to investigate whether traits consistent with autism (social responsiveness) are associated with sleep disruption independent of lifestyle and other behavioural measures. Methods: Autistic traits were assessed using the Social Responsiveness Scale at age 11, and sleep disruption and behavioural outcomes were assessed at ages 11 and 13 years using the Sleep Disturbance Scale, and the Child Behaviour Check List, respectively. Demographic, health and lifestyle-related variables were assessed by caregiver questionnaires. Regression models were applied to investigate associations between autistic traits and sleep outcomes. Results: There was a significant cross-sectional association between sleep disturbance and SRS at age 11 years old that was independent of sex, ethnicity, socioeconomic position, physical activity, sedentary behaviour and anxiety/depression ({beta} = 0.12, 95% CI (0.07, 0.17); p < 0.001), that persisted at age 13, and that was modulated by chronotype, with evening types showing a stronger association. Discussion: Social responsiveness assessed in early adolescence (age 11) were associated with sleep disruption independent of multiple confounding factors and were prospectively associated with sleep disruption at age 13 years. These findings contribute to the evidence that disruption of sleep and circadian timing may have a primary role in the neurobiological mechanisms that mediate autistic traits.

Background: Infant muscle tone reflects early central nervous system integrity and has been associated with later motor and cognitive development, including autism traits. The cerebellum regulates both motor control and higher-order socio-cognitive functions and has been repeatedly implicated in autism, but its role in linking infant muscle tone to adolescent autistic traits has not previously been studied in a large, prospective population cohort. Methods: We used data from the prospective Generation R Study. Infant muscle tone (hypotonia and hypertonia) was assessed via Prechtl examination, and third-trimester fetal transcerebellar diameter was measured using ultrasound n=6,842). Cerebellar morphology at ages 6, 10, and 14 years (n=4,861) was measured using structural MRI. Linear mixed-effects models tested associations between infant muscle tone and 35 anatomical and 10 functional cerebellar regions. Causal mediation models tested whether cerebellar volume mediated associations between infant muscle tone and adolescent autistic traits at age 14 (Social Responsiveness Scale). Results: Hypotonia predicted larger vermis IX volumes across childhood (beta=0.037, pFDR =0.043). Hypertonia showed an age-dependent association with left lateral lobule IX (beta=-0.0027, pFDR =0.041), with differences diminishing with age. Third-trimester transcerebellar diameter did not predict postnatal muscle tone. Given its significant main effect, vermis IX volume was tested as a mediator, but did not mediate the pathway to adolescent autistic traits. However, infant hypotonia showed a small direct association with elevated autistic traits at age 14, specific to girls (beta=0.0255, p=0.020). Conclusions: Infant muscle tone is associated with localized differences in cerebellar volumes. These associations are specific to vermal and left hemispheric lobule IX, a region commonly implicated in spinocerebellar postural control, axial stability, and higher-order sensorimotor integration. Furthermore, infant muscle tone was not predicted by prenatal cerebellar diameter, and cerebellar volumes did not mediate the association between infant hypotonia and adolescent autistic traits in our study. Future research should further investigate these findings in clinical populations, integrating longitudinal whole-brain, multi-modal imaging to clarify the association between infant muscle tone, the cerebellar functioning, and autistic traits.

BackgroundThe 40Hz auditory steady-state response (ASSR) is a measure of gamma-band neural synchrony sensitive to excitation-inhibition (E/I) balance. Disruptions to E/I balance have been implicated in autism spectrum disorder (ASD), making ASSR an efficient tool for investigating neural synchrony development in this population. Whether age-related differences in 40Hz ASSR are detectable across development in ASD remains understudied. Phelan-McDermid syndrome (PMS), a rare genetic disorder with a phenotype overlapping with autism, caused by SHANK3 disruption, provides a genetically defined model for further investigating E/I-related neural synchrony disruptions. MethodsWe examined 40Hz inter-trial phase coherence (ITPC) as an index of neural synchrony across a wide age range (2-37 years) in 127 participants from four groups: TD (n=43), ASD without intellectual disability (w/o ID; n=37), ASD with intellectual disability (w/ID; n=24), and PMS (n=23). Given the distinct age and cognitive profiles of ASD subgroups in this sample, analyses were conducted in separate models: TD vs. ASD w/o ID across all ages, and TD vs. ASD w/ID vs. PMS restricted to participants under 18. ResultsFor the first time in a cross-sectional sample spanning a large age range, we show that 40Hz ITPC increases significantly with age in TD individuals, while this developmental trajectory is absent in ASD without intellectual disability. Among children and adolescents under 18, 40Hz ITPC did not differ across TD, ASD w/ID, and PMS, and IQ did not predict ITPC in clinical groups. A post-hoc analysis revealed higher ITPC in TD males than females, with no sex differences in ASD or PMS. ConclusionsWe demonstrate that gamma-band ITPC trajectories diverge between TD and ASD, specifically in adulthood, with no such difference detectable in childhood. No significant group differences were found among TD, ASD w/ID, and PMS individuals under 18. These findings highlight the importance of age as a critical variable when measuring ASSR, and underscore the need for lifespan studies, particularly in genetically defined conditions such as PMS, to determine whether similar divergence emerges in adulthood.

Background: Autism polygenic scores (PGS) reliably predict case-control status yet explain little variance in autism-related traits. Landscape accounts of neurodevelopmental diversity propose that genetic liability broadens the range of viable neural configurations rather than shifting brain organisation toward dysfunction. We tested whether autism polygenic load is associated with increased variability in functional network organisation among non-autistic adults. Methods: We analysed resting-state functional connectivity from 910 non-autistic adults (aged 22-35) in the Human Connectome Project. Polygenic scores were derived from the iPSYCH autism GWAS at a pre-specified threshold (p = 0.1). Modularity (segregation) and global efficiency (integration) were computed at a pre-selected parcellation size and density (100-node, 20%), and residualised for age, intracranial volume, and head motion. Variance effects were assessed by variance regression including a PGS-by-sex interaction, decile-stratified dispersion trends, and PGS-balanced bootstrap resampling. Edge-wise analyses used false discovery rate correction. Results: Modularity variability broadened with polygenic load in a sex-dependent manner (sex-by-PGS beta = 1.92e-4, p = 0.031). Decile trends (male minus female difference = 0.82, p = 0.034) and balanced-bootstrap trends (difference = 1.19, p = 0.032) both differed by sex: variance increased across polygenic bins in males (r = 0.57, one-tailed p = 0.021) but not females. No comparable effect emerged for global efficiency (all p >= 0.54). Polygenic scores showed no association with social-cognitive difficulty (beta = 0.11, p = 0.209), mean network organisation, or connectivity after correction. Limitations: All participants were non-autistic adults and the analysis was cross-sectional. The identified effects are small and the sample size not sufficient to resolve very small effects often reported in genetics studies. Characterisation of genetic effects in women may be influenced by biases in the data used to calculate polygenic scores. Conclusions: Autism polygenic load broadened modular network configurations in males without shifting mean organisation or its behavioural correlates, offering partial support for landscape accounts.

Children with Down syndrome (DS) experience delays in cognitive, physical, and motor development. Overexpression of Dual-specificity tyrosine phosphorylation-regulated kinase-1A (DYRK1A), a gene on human chromosome 21 (Hsa21) and triplicated in individuals with Trisomy 21, contributes to neurodevelopmental delays associated with DS, and is a candidate for therapies to improve neurodevelopmental phenotypes. Male and female Ts65Dn DS model pups are trisomic for [~]100 Hsa21 orthologs including Dyrk1a, and both sexes show significant DYRK1A overexpression on postnatal day 6 (P6) in the hippocampus, cerebral cortex, and cerebellum. This study tested the hypothesis that normalization of Dyrk1a copy number in Ts65Dn pups prior to P6 would diminish physical and behavioral developmental outcomes in Ts65Dn mice, thus providing a standard of comparison for success of interventions targeting Dyrk1a. At P3-P21, Ts65Dn compared to euploid pups showed sex-specific deficits in physical, motor, and behavioral development. Male Ts,Dyrk1a+/+/Dox-Cre mice showed improved emergence to running on P19, and both sexes of Ts,Dyrk1a+/+/Dox-Cre mice exhibited reduced isolation-induced ultrasonic vocalizations during the second postnatal week. Dyrk1a normalization in Ts65Dn pups did not improve all abnormal phenotypes, perhaps because of developmental dysregulation between Dyrk1a RNA and DYRK1A protein levels, involvement of other trisomic genes, or improvements in only adult mice.

Autism spectrum disorder (ASD) is characterized by differences in social communication, interaction, and restricted and repetitive behaviors. The hypothesis that ASD involves altered cortical excitation-inhibition (EI) balance has been extensively investigated, yet evidence remains mixed, partly because EI balance changes substantially during typical maturation. We used resting-state magnetoencephalography (MEG) to examine developmental trajectories of cortical EI alterations with regional specificity in a large cross-sectional cohort (N = 172; 92 typically developing, 80 ASD; ages 6-32). Functional EI (fEI), derived from critical brain dynamics, was estimated across 500 cortical parcellations. Group-averaged fEI maps revealed broadly similar large-scale topographic patterns across groups. Age-stratified analyses revealed increased global fEI in childhood and decreased fEI in adolescence in ASD, with no evidence of a group difference in adulthood. Parcel-wise regressions identified a significant main effect of diagnosis in right dorsolateral prefrontal cortex, where typically developing individuals showed higher fEI across all ages. A significant group-by-age interaction in left inferior parietal cortex indicated diverging developmental trajectories. Finally, fEI in paracentral and precuneus regions was associated with the magnitude of ASD symptoms. These findings indicate that EI imbalance in ASD is neither globally distributed nor static, but expressed through regionally and developmentally specific differences, with relevance for ASD heterogeneity.

Generalization is a key cognitive process that allows humans to flexibly apply prior knowledge to guide new behaviors. Difficulties with generalization and flexibility are observed across neurodevelopmental disorders, especially autism, limiting adaptive function and quality of life. Cognitive-behavioral treatment benefits some but not all autistic individuals. As treatment requires application of learned skills to everyday life, variability in generalization ability may limit intervention success in autism. While cognitive substrates of learning and generalization are well established, their potential for explaining clinical outcomes is not known. Here, we combined a category learning task with computational modelling to distinguish two learning strategies underlying generalization -- prototype abstraction vs. exemplar memorization -- and tested whether individual differences in these learning strategies predicted real-world intervention outcomes in autistic youth. Fifty-four participants completed the category learning task at two pre-intervention timepoints, and then completed Unstuck and On Target:14-22 intervention targeting flexible problem solving, goal setting, and planning. We found that participants who consistently relied on prototype abstraction (N=26) were subsequently more likely to benefit from the intervention, showing improvement in parent- and self-reported flexibility. These findings identify prototype abstraction as a clinically relevant cognitive capacity that may help explain individual differences in intervention response and support the tailoring of interventions. More broadly, they demonstrate the value of linking basic cognitive mechanisms to clinical outcomes and may inform strategies to enhance the effectiveness of cognitive-behavioral interventions for youth with developmental disabilities.

The Autism Spectrum Quotient (AQ-50) is widely used to assess autistic traits, yet its Hungarian version has not been psychometrically evaluated. We assessed the reliability, factor structure, temporal stability, convergent validity, and clinical utility of the Hungarian AQ-50 and a revised translation (AQ-50-HU-R) in two samples (N1 = 1967; N2 = 423), including autistic and non-autistic participants. The AQ-50-HU-R showed high internal consistency and test-retest reliability. A bifactor model provided the best fit ({chi}2[1125] = 1650.433, p < 0.001; CFI = 0.991; TLI = 0.990; RMSEA = 0.033 [90% CI = 0.030-0.037]; SRMR = 0.083), with 71% of common variance attributable to a general autistic traits factor. The total score distinguished clinically verified autistic participants from participants reporting no ASD diagnosis (AUC = 0.906), with a cutoff of 25. Associations with ADOS scores were weak or nonsignificant. The AQ-50-HU-R is best interpreted as a reliable total-score screening measure, supporting referral for comprehensive autism assessment.

Autism Spectrum Disorder (ASD) is a heterogeneous neurodevelopmental condition defined by differences in social communication and restricted, repetitive behaviours. As diagnostic criteria have broadened, ASD is now recognised across a wider range of individuals, raising key questions about its structure: does ASD have discrete sub-types, or is it better conceptualised as a continuous, possibly multidimensional, condition? We aim to explore whether a multidimensional continuum model more accurately captures the variability within ASD. We analysed a large SPARK phenotypic dataset of medical history and diagnostic surveys (background history, SCQ, RBS-R; n=36,710 individuals). We apply and compare two traditional statistical approaches, Factor Analysis and Gaussian Mixture Models, with a modern machine learning technique, the Variational Autoencoder (VAE). VAEs reconstructed unseen test data with ~4-fold better accuracy than Factor Analysis, and ~8-fold better accuracy than Gaussian Mixture Models. We identified four stable latent factors across 100 independently trained VAEs. These four dimensions provide an individual behavioural profile that can be visualized using radar-plots, offering a compact way to compare profiles at the person level. Through further analysis, we found evidence for 3 overlapping clusters or subtypes of ASD identified within the 4D latent space. This work aims to inform new ways of modelling ASD using a VAE that will be able to discern between a continuum or a clustered output and that go beyond binary diagnosis, instead reflecting the complex range of trait profiles, with implications for personalised diagnosis and intervention.

In many high-income countries, autistic children attend preschools ranging from exclusive special education (SE) to inclusive mainstream education (ME). These settings differ in staff expertise, capacity to implement structured autism interventions, exposure to typically developing peers, and cost. In this prospective longitudinal study, we compared 119 autistic children across three preschool settings in southern Israel: SE with TABAM services, an extended intervention program; SE without TABAM; and ME. Children completed behavioral assessments at the beginning and end of their first preschool year, yielding measures of cognition, autism symptom severity, joint attention, verbal abilities, adaptive behaviors, and aberrant behaviors. Developmental trajectories varied across children, with some demonstrating marked gains and others showing limited progress. On average, developmental changes were modest across most domains and were not explained by educational setting. The only exception was verbal ability, where children in SE with TABAM showed greater gains than children in SE without TABAM. These findings suggest that autistic children in ME and SE demonstrated broadly similar developmental trajectories during their first preschool year. Further large-scale research is needed to identify which children may benefit more from specific educational environments and intervention approaches, and to inform ongoing efforts to optimize preschool services for autistic children.