Molecular Autism

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.

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.

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.

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.

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.

Objectives To evaluate the positive and adverse effects of parent-mediated interventions (PMIs) versus care as usual for children with autism. Setting Systematic review and meta-analysis and Trial Sequential Analyses (TSA), following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Methods We searched for randomised clinical trials of PMIs for children with autism in the databases CENTRAL, EMBASE, LILACS, PsycINFO, MEDLINE, and SCI-EXPANDED (up to 13 August, 2025), complemented with manual searches. 12,359 articles were screened. Data were synthesised using meta-analyses and Trial Sequential Analyses (TSA), and risks of bias and certainty of the evidence were evaluated. Primary and secondary outcome measures The primary outcome was autism characteristics. Secondary outcomes were adverse effects, child adaptive functioning, child language, child and parent quality of life, and parental stress. Ten exploratory outcomes were included. Results 32 trials (N=1,625) comparing PMIs to usual care, waiting list, or no intervention were included. All trials had a high risk of bias. The multiplicity-adjusted threshold for statistical significance was p = 0.013 due to the number of outcomes. Meta-analyses and TSAs showed it could be rejected that PMIs reduced autism characteristics (MD = -0.88; 95% confidence interval -2.92 to 1.15; p = 0.05, 4 trials, N=353, low certainty), child adaptive functioning (7 trials, N=408), child language (4 trials, N=308), or parental stress (7 trials, N=385). Due to insufficient data, the remaining secondary meta-analyses could not be conducted. Meta-analyses of exploratory outcomes showed beneficial effects concerning child behaviour problems and parent sensitivity/synchronicity. Conclusions This meta-analysis found no benefits of PMIs on child autism characteristics, child adaptive functioning, child language, or parental stress. Benefits were found in reduction of child behaviour problems and improved parent sensitivity/synchronicity. The evidence remains uncertain, and more trials including outcomes of adverse effects and quality of life are needed.

Background: Sleep problems are common in autism, emerge early in life and reduce quality of life, yet the mechanistic link between autism and poor sleep remains unclear. Human and rodent data indicate that difficulty falling asleep is a core feature of autistic insomnia, pointing to impaired responses to sleepiness as the underlying cause. We previously showed that adult mice carrying a mutation in the high-confidence autism gene Shank3 (Shank3{Delta}C) recapitulate this insomnia phenotype and struggle to respond to sleepiness after acute sleep deprivation. Here, we used Shank3{Delta}C mice to examine the molecular basis of sleepiness and how this autism-associated mutation alters it to inform understanding of sleep problems in autistic individuals. Methods: This study used RNA-sequencing and bioinformatics to identify molecular targets underlying the effect of the Shank3{Delta}C mutation on the molecular basis of sleepiness across development in male mice. We first compared cortical genome-wide gene expression following acute sleep deprivation and recovery sleep in adult wild-type (WT) and mutant mice. We then used polysomnography and RNA-sequencing to assess the response to increased sleepiness in WT and mutant mice at postnatal days 24 and 30. Results: The neurotypical response to acute sleep deprivation shifted from upregulating neuronal growth and development pathways at P24/P30 to upregulating DNA damage repair and neuronal activity-dependent transcription in adulthood. The Shank3{Delta}C mutation largely blocked recruitment of these pathways at P24 and in adulthood while paradoxically increasing the magnitude of the mutant response at P30. In addition, mutants consistently upregulated oxidative stress pathways linked to neurodegeneration and protein synthesis regardless of age, whereas WT animals downregulated these functions. Limitations: This study examined gene expression only in male mice, used a single autism rodent model, and averaged signals across mixed cortical cell types. Future work should include females, additional autism models, and single-cell approaches in additional brain regions to further characterize the cellular effects of sleep deprivation and autism-associated mutations. Conclusions: The Shank3{Delta}C mutation impairs the molecular accumulation of and response to sleepiness, both by elevating oxidative stress responses and by blocking the age-typical upregulation of pathways that differ between juveniles and adults.

Fragile X syndrome (FXS) is the leading monogenetic cause of intellectual disability and autism, yet how basic hippocampal circuit properties evolve across development for this condition remains unclear. Here, we studied CA1 pyramidal neurons in male Fmr1 knockout rats at postnatal day (P)12 - 15 and 6 - 10 weeks using ex vivo electrophysiology pharmacology, imaging and biochemistry. P12 - 15 knockout neurons showed impaired sustained firing, progressive action potential broadening and enhanced activity-dependent synaptic vesicle replenishment. These defects recovered by 6 -10 weeks. These phenotypes were linked to Kv7 channel dysfunction, as Kv7 activation altered action potential dynamics and neurotransmission in WT but not Fmr1 KO neurons. Rather than directly altering Kv7 channel function, Fmr1 knockout altered axon initial segment (AIS) development such that Kv7 became functionally inert. These findings suggest that this drives early, transient Kv7-dependent CA1 dysfunction in FXS and highlight how alterations in AIS development can have profound functional impacts.

Background: Autistic Chronic Energy Depletion Syndrome, commonly referred to as Autistic Burnout, is a debilitating condition characterized by exhaustion, loss of function, and reduced tolerance to stimuli. While several instruments attempt to measure it, validation studies have only used cross-sectional designs and/or convenience samples with low support needs, limiting understanding of their performance across heterogeneous, autistic populations and over time. Methods: Using a community-based participatory research (CBPR) approach, we revised the 27-item AASPIRE Autistic Burnout Measure (AABM) into a 14-item AASPIRE Autistic Burnout Measure-Revised (AABM-R) and tested it in a longitudinal study of 835 autistic adults recruited from healthcare systems, disability services, and the community. Participants completed surveys directly (with or without support) or via a caregiver. We assessed structural validity and measurement invariance using exploratory and confirmatory factor analysis, tested construct validity through a priori hypothesis testing, examined discriminant validity from depression using longitudinal factor analysis and cross-lagged panel models, and assessed criterion validity using ROC analysis. Results: The AABM-R demonstrated a clear single-factor structure among direct reporters, with and without support, and measurement invariance across these groups; findings were less conclusive for the smaller caregiver-report subsample. Autistic burnout correlated as hypothesized with stressors (e.g., discrimination, masking, adverse childhood experiences), supports (e.g., social support, receiving needed help with daily living activities), and broader outcomes (e.g., quality of life, depression, anxiety). Longitudinal modeling supported autistic burnout as empirically distinct from, though related to, depression. ROC analysis (AUC = 0.89) supported cut-offs distinguishing probable (33-56, LR 7.38), unsure, and unlikely (0-22, LR 0.15) burnout. Conclusions: The AABM-R is a brief, accessible, psychometrically sound measure of autistic burnout suitable for heterogeneous autistic populations, with preliminary clinical cut-offs to guide screening. Further research is needed on the caregiver-report version and on longitudinal predictors and outcomes of burnout.

Metastability is a fundamental dynamical property of large-scale brain networks and reflects the capacity of the brain to flexibly reorganize transient coordination patterns. In this study, we investigated whether metastable properties of resting-state electroencephalographic (EEG) phase synchronization networks are associated with individual differences in autistic traits. Resting-state EEG data from 88 neurotypical adults were analyzed using two complementary metrics: synchrony coalition entropy (SCE), which quantifies the diversity of transient phase synchronization patterns, and the metastability index (MSI), which quantifies temporal variance in global phase synchronization. SCE showed frequency-specific associations with the Autism-Spectrum Quotient (AQ) attention-switching subscore at 18-24 Hz and the communication subscore at 4-8 Hz, suggesting that frequency- and network-specific patterns of metastable synchronization are associated with distinct aspects of autistic traits. In contrast, MSI showed a modest association with the social-skill subscore in the lower-beta range, but this effect did not survive a cluster-based permutation test. This exploratory observation suggests that global synchronization variability may capture a weaker, complementary aspect of trait-related metastable dynamics. These findings suggest that, within a neurotypical population, individual differences in autistic traits may be more sensitively captured by the repertoire of transient phase synchronization patterns, as indexed by SCE, than by global phase synchronization variability, as indexed by MSI. Moreover, the associations of distinct AQ subscores with SCE in different frequency ranges suggest that different dimensions of autistic traits may be related to metastable network dynamics operating at different temporal scales. Author SummaryThe brain constantly coordinates activity across many regions, and this coordination changes over time rather than remaining constant. Understanding these dynamic patterns is important for explaining individual differences in cognition and behavior. In this study, we focused on a dynamical property called "metastability," which describes how brain activity flexibly shifts between different patterns of coordination. Instead of remaining in a stable state, the brain repeatedly forms and dissolves coordinated activity across regions. We analyzed brain signals recorded with resting-state electroencephalography (EEG) and examined whether these dynamic patterns were related to individual differences in autistic traits. We found that different aspects of time-varying coordination were linked to different dimensions of autistic traits in a neurotypical population. These findings suggest that examining how brain activity changes over time, rather than relying only on time-averaged measures, can reveal neural features associated with individual differences in autistic traits. Our study highlights metastability as a useful concept for understanding the flexible and dynamic nature of human brain function.

Empirical evidence from traditional inhibitory control tasks regarding inhibitory deficits in high autistic traits has been mixed, indicating that this issue remains controversial. Although sex differences are widely documented in autistic cognitive profiles, their role in inhibitory gating mechanisms remains underexplored. Given that the expression of inhibitory gating deficits may be modulated by the social versus non-social nature of stimuli, and no prior study has investigated this topic by integrating both sex differences and stimulus domain, we addressed these two questions with the attribute amnesia paradigm. We manipulated stimulus type (non-social vs. social). In Experiment 1, participants performed a location task with animal drawings as targets and were unexpectedly asked to report animal identity on a surprise trial. High autistic trait females showed significantly higher accuracy on the surprise trial than all other groups, reflecting a failure to actively filter out task-irrelevant non-social information, that is, a reduced inhibitory gating efficiency. In Experiment 2, using face stimuli and a self-vs. other-face design, this gating deficit was no longer expressed: all groups performed at chance levels on the identity judgment, regardless of autistic trait level, sex, or face type. This dissociation aligns with a dual-mechanism framework: the inhibitory gating deficit in high autistic trait females is specific to non-social stimuli and masked by camouflaging for social ones. This study demonstrates that the inhibitory gating deficit in high autistic trait females is not a global impairment but rather a stimulus-dependent one, highlighting the need to consider sex and stimulus type.

Background: Altered gamma-aminobutyric acid (GABA) neurotransmission is a proposed mechanism underlying autism spectrum disorder (ASD), prompting evaluation of several GABA-modulating pharmacotherapies. However, it remains unclear whether these interventions improve ASD broadly or preferentially affect specific symptom domains. Methods: We conducted a systematic review and random-effects meta-analysis of randomized controlled trials evaluating GABA-modulating pharmacotherapies in individuals with ASD. PubMed/MEDLINE, Embase, Scopus, and CENTRAL were searched from inception to April 1, 2026. Outcomes were prespecified as global autism severity, social communication, functional communication, restricted and repetitive behaviours (RRBs), adaptive behaviour, and irritability. Risk of bias was assessed using the Cochrane Risk of Bias 2 tool, and certainty of evidence was evaluated using GRADE. Results: Thirteen randomized controlled trials evaluating three GABA-modulating interventions (bumetanide, arbaclofen, and valproate) were included. GABA-modulating therapies were associated with statistically significant improvements in global autism severity (Hedges' g = -0.25, 95% CI -0.46 to -0.03; p = 0.028) and adaptive behaviour (Hedges' g = -0.09, 95% CI -0.15 to -0.02; p = 0.023). No significant pooled effects were observed for social communication (Hedges' g = -0.26, p = 0.077), functional communication (Hedges' g = -0.01, p = 0.869), RRBs (Hedges' g = -0.21, p = 0.126), or irritability (Hedges' g = -0.07, p = 0.543). After Holm-Bonferroni step down procedure, neither global autism severity nor adaptive behaviour remained statistically significant (Holm-adjusted p = .140 and .138, respectively). Adverse events were predominantly gastrointestinal, neurological, metabolic, and appetite-related. Overall risk of bias was variable, and the certainty of evidence ranged from very low to moderate. Conclusions: GABA-modulating pharmacotherapies did not demonstrate a robust, multiplicity-corrected benefit in any of the six prespecified ASD symptom domains. Nominal, unadjusted improvements in global autism severity and adaptive behaviour did not withstand correction for multiple comparisons and should be regarded as hypothesis-generating rather than confirmatory. Larger, adequately powered randomized trials using standardized domain-specific outcome measures are needed to determine whether individual GABA-modulating agents provide clinically meaningful benefit.

Predictive coding frameworks propose that perception emerges from a continuous comparison of incoming sensory signals with internally generated predictions, with mismatches between the two computed as prediction errors. Disruptions to the balance between these top-down predictions and bottom-up sensory signals are theorized to contribute to sensory abnormalities in neuropsychiatric conditions like autism spectrum disorders. However, disambiguating bottom-up from top-down contributions to sensory perception remains a difficult challenge, particularly in animal models. Here we develop a probabilistic oddball detection task in which rats must track local statistics within a trial to detect a deviant stimulus, as well as global statistics across trials to anticipate when a deviant will occur. This design enables formation of experimentally specified internal models of deviant expectation that can be quantitatively derived from behavior and manipulated independently of local stimulus statistics. We used this task to characterize sensory predictive behavior in a Fmr1 KO rat model of Fragile X Syndrome, the most common monogenic cause of autism. Male Fmr1 KO rats detected deviant stimuli at wildtype levels but exhibited reduced anticipation of deviant occurrence based on cross-trial statistics and failed to adapt their behavior when these statistics changed. Computational modeling revealed that these behavioral deficits reflected imprecise and unstable internal predictive models skewed towards sensory immediacy. These findings provide evidence for disrupted predictive processing in Fragile X Syndrome, consistent with active inference accounts of autism, and highlight the utility of this probabilistic oddball task design for interrogating predictive coding and perceptual impairments in neuropsychiatric conditions.

Background The global increase in autism spectrum disorder (ASD) diagnoses is expected to substantially increase demand for long-term rehabilitation services. However, little is known about how this increase affects rehabilitation service utilization and capacity in low- and middle-income countries. Methods We conducted a retrospective longitudinal study of children receiving developmental care at a tertiary rehabilitation center in Salvador, Brazil (2017-2026). Patients were classified into Childhood Autism, Other ASD, and non-ASD diagnostic groups according to ICD-10 diagnoses. Temporal trends in admissions and patients under follow-up were analyzed using generalized additive models and segmented Poisson regression. Factors associated with follow-up duration were evaluated using multivariable Cox proportional hazards models. Results Among 2,123 eligible children, 833 (39.2%) had Childhood Autism, 462 (21.8%) had Other ASD, and 828 (39.0%) had non-ASD diagnoses. Compared with children with non-ASD diagnoses, those with Childhood Autism entered care at younger ages, were predominantly male (77.9% vs. 57.2%), attended more visits, and remained under follow-up longer (all P<0.001). Admissions of children with Childhood Autism increased by 30.2% annually before 2023 but declined thereafter (-19.6% annually; P<0.001). Despite this decline, the number of children with Childhood Autism receiving ongoing rehabilitation continued to increase, reflecting prolonged follow-up. In adjusted analyses, Childhood Autism was associated with a substantially lower hazard of reaching the last recorded follow-up visit than non-ASD diagnoses (adjusted hazard ratio, 0.35; 95% CI, 0.30-0.40; P<0.001). Conclusions The rapid increase in ASD admissions fundamentally reshaped rehabilitation service utilization. Because children with ASD remained under follow-up substantially longer than those with other developmental conditions, they accounted for an increasing share of the rehabilitation caseload, even after new admissions began to decline. These findings highlight the importance of planning rehabilitation services according to both new admissions and the cumulative demand generated by long-term follow-up.

Children and adolescents with hearing loss frequently encounter reduced auditory access and delayed language development, factors that may influence the maturation of executive functions. This study examined developmental differences in planning, a core executive function, in 98 children and adolescents with hearing loss or normal hearing aged 7 to18 years using the Tower of London task. Compared to normal hearing peers, participants with hearing loss made more unnecessary moves and rule violations and initiated problem-solving more rapidly, suggesting reduced preplanning efficiency and increased impulsivity. These group differences were most pronounced in adolescents, who showed faster initiation and greater movement inefficiency than age-matched normal hearing participants. Within the hearing loss group, adolescents displayed higher accuracy and longer initiation times than children, reflecting developmental improvements despite persistent gaps relative to hearing peers. Language development age did not alter the main effects. Findings indicate that reduced early auditory and language access may contribute to differences in planning development, highlighting the need for targeted executive functions support in educational and clinical settings for youth with hearing loss.

Down syndrome (DS) is the most common genetic cause of intellectual disability, yet age-related cortical maturation patterns that contribute to developmental delays remain poorly understood. We analyzed longitudinal resting-state EEG and developmental data from 86 children with DS and 154 typically developing (TD) children between 12 and 81 months of age. Linear mixed-effect models tested age-related trajectories of aperiodic and periodic spectral features, and manifold learning was used to characterize multivariate EEG profiles associated with age and developmental ability. Children with DS showed altered maturation across multiple EEG features. Aperiodic exponent decreased with age in DS, but not TD children, indicating possible altered maturation of cortical excitability. While TD children showed expected age-related increases in theta-alpha peak frequency and amplitude, children with DS exhibited limited alpha maturation and greater persistence of theta-only and theta+alpha peak profiles. We next asked whether multivariate EEG organization reflected chronological maturation or individual differences in developmental ability. A spectral dimension associated with chronological age in TD children was not similarly age-associated in DS. Instead, a second spectral dimension was associated with verbal developmental quotient in children with DS, independent of chronological age and nonverbal developmental ability. This language-associated profile included features considered atypical relative to TD maturation, including increased aperiodic activity and continued presence of theta activity. These findings suggest that in DS there is an altered relationship between cortical spectral organization, chronological age, and language development, extending beyond a uniform delay in typical maturation.