Tag: Autism

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Autistic traits in unaffected first-degree relatives of individuals with schizophrenia and bipolar disorder: implications for shared familial neurodevelopmental vulnerability

BackgroundAutistic traits have increasingly been linked to schizophrenia (SCH) and bipolar disorder (BD) within a shared neurodevelopmental framework. However, whether these traits are similarly expressed in unaffected first-degree relatives of individuals with SCH and BD remains poorly understood.MethodsThis cross-sectional study included 135 participants: first-degree relatives of individuals with schizophrenia (SCH-FDR, n=45), first-degree relatives of individuals with bipolar disorder (BD-FDR, n=45), and healthy controls (HCs, n=45). Autistic traits were assessed using the Autism Spectrum Quotient (AQ). Participants also underwent clinical psychiatric evaluation, including structured diagnostic assessment, to exclude psychiatric disorders and autism spectrum disorder.ResultsSignificant group differences were observed for AQ total score (p=0.002), Communication (p=0.004), and Imagination (p<0.001) subscales. Communication scores were significantly higher in SCH-FDR than in HCs (p=0.003). Imagination scores were higher in both BD-FDR (p=0.016) and SCH-FDR (p<0.001) groups compared with HCs. Total AQ scores were also higher in both relative groups than in HCs (BD-FDR: p=0.015; SCH-FDR: p=0.003). The proportion of participants with AQ scores ≥26 was higher in SCH-FDR (17.8%) and BD-FDR (13.3%) than in HCs (2.2%; p=0.045).ConclusionsAutistic traits were more pronounced in SCH-FDR and BD-FDR than in healthy controls. Differences were most evident in total AQ scores and the Imagination subscale across both relative groups, whereas communication difficulties were specifically elevated in schizophrenia relatives. These findings are consistent with the concept of shared familial neurodevelopmental vulnerability across schizophrenia and bipolar disorder.
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Comparison of subject-to-template registration schemes using CT and MR radiotherapy images with brain lesions

IntroductionVoxel-based analyses have been used more widely in radiotherapy in recent years. The purpose of this study is to compare eight different methods of registering images on to a template space for such analyses. A novel way, using both CT and MR data, is proposed.MethodsCT and MR brain images from 85 participants in the CoDe-B-Rad study (NCT06466720) were registered on an age-specific template. The registration schemes used included sCT-Template (linear and non-linear); MR-Template (linear, non-linear, masked, and enantiomorphic); and Dual-Template (linear and non-linear). The registrations were compared qualitatively and quantitatively against the template MR images with scores ranging from 1 (lowest) to 5 (highest) and quantitatively (via Jaccard, ASD, and HD95).ResultsQualitatively, the best registration scheme was the Dual-Template-non-linear registration, with 60 participants scoring above 4. The second best was the MR-Template-enantiomorphic, with 53 participants scoring above 4. Quantitatively, the Dual-Template-non-linear method outperformed on the mean (±SD) for the ASD and HD95, with 0.918 (±0.1774) and 2.965 (±0.5392) respectively. For ASD the difference compared to other methods was significant (p = 0.03). The MR-Template-masked outperformed on the Jaccard mean (±SD), median (IQR), and ASD, achieving values of 0.567 (±0.0557), 0.555 (0.055), and 0.808 (0.162) respectively. The Dual-Template-non-linear and MR-Template-masked and non-linear had the same result for the median HD95: 2.639. The performance of all linear schemes was inadequate both quantitatively and qualitatively. All non-linear registration schemes had issues with distortions of tissue and landmarks, however, for the Dual-Template scheme these were minimal.ConclusionThe Dual-Template-non-linear registration scheme is a new way of registering lesioned brain images for use with voxel-wise techniques in radiotherapy, which utilises both CT and MR image data. The scheme provides fidelity of the underlying soft tissue as well as the surrounding skull, minimising anatomical and dosimetric distortions.
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Synaptic mechanisms for differential severity of social preference deficits in male and female mice induced by diminished activity-dependent BDNF

Males are more commonly diagnosed with autism spectrum disorder (ASD) than females with a ratio of about 4–1. However, the neural mechanisms underlying the sex differences in ASD are unknown. Social deficits are the core symptoms of patients with ASD. Previous studies showed that diminished activity-dependent brain-derived neurotrophic factor (BDNF) signaling induced differential severity of autism-like social preference deficits in male and female mice by using a mouse model with genetic knock-in of human BDNF methionine (Met) allele, which significantly decreased activity-dependent BDNF release without affecting basal BDNF secretion. Here, we investigated the synaptic mechanisms for diminished activity-dependent BDNF-induced differential severity of social preference deficits in males and females. The prefrontal cortex (PFC) is a critical brain region for social behaviors. Whole-cell patch-clamp brain slice recordings showed that diminished activity-dependent BDNF signaling differentially increased the frequency of spontaneous action potentials (sAPs) of pyramidal neurons in the PFC of male and female BDNF+/Met mice. The frequency of sAPs in male BDNF+/Met mice was higher than in female BDNF+/Met mice. Diminished activity-dependent BDNF signaling differentially enhanced excitatory synaptic transmission and dampened inhibitory synaptic transmission of pyramidal neurons at pre- and post- synapses in males and females, which were mediated by dysregulated transcriptional levels of key synaptic genes. Chemogenetic inhibition of pyramidal neurons in the PFC of BDNF+/Met mice was sufficient to ameliorate autism-like social preference deficits in males and females. This study reveals synaptic mechanisms underlying the differential severity of social preference deficit in male and female BDNF+/Met mice, which provides a potential neural basis for sex differences in male and female ASD patients with and without the BDNF Val66Met SNP.
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Immersive wearable virtual reality for autism: a systematic review of current evidence

IntroductionImmersive and wearable virtual reality (VR) is an emerging technology with growing potential to support assessment and intervention ifor autistic people. The methodological heterogeneity of existing studies limits the interpretation and generalization of current evidence.MethodsA systematic review with a narrative synthesis was conducted in accordance with the PRISMA guidelines. Electronic searches were performed in PubMed, Scopus, IEEE Xplore, Web of Science, and Google Scholar, identifying studies published between 2015 and August 2025. Twenty-two studies investigating wearable and immersive VR interventions in children and adults with ASD met the eligibility criteria.ResultsThe included studies demonstrated that wearable VR interventions may improve social communication, joint attention, emotional regulation, daily living skills, executive functioning, and user engagement. Innovative technologies, including eye-tracking and artificial intelligence-based systems, also enabled objective assessment of gaze behaviour, social interaction, and physiological responses. Nevertheless, the evidence was characterized by considerable methodological heterogeneity, predominantly small sample sizes, limited use of randomized controlled designs, and scarce long-term follow-up, reducing the generalizability of the findings.DiscussionWearable VR represents a promising tool for personalized assessment and intervention in ASD. Based on the current evidence, we propose a structured pre-intervention assessment integrating sensory, cognitive, emotional, and VR tolerance profiles to support individualized intervention planning. Future research should prioritize standardized outcome measures, rigorous study designs, and longitudinal investigations to strengthen the clinical translation of VR-based interventions in autism.
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NeuroCon-AutismNet: a privacy-preserving multimodal framework toward autism screening via diffusion-regularized EEG biomarkers and empathy-aware multilingual dialogue

IntroductionAutism Spectrum Disorder (ASD) screening requires multimodal biomarkers to capture the heterogeneous neurological and behavioral phenotypes. Current screening approaches remain siloed across EEG analysis and conversational assessment, limiting integrated diagnostic architecture. Privacy-preserving machine learning frameworks for mental health screening are underdeveloped, particularly for multilingual deployment contexts. This paper presents NeuroCon-AutismNet, a candidate multimodal architecture integrating diffusion-regularized EEG synthesis, multilingual conversational screening, and formal differential privacy as architectural proof-of-concept. No diagnostic discrimination capability is claimed; all validation is scoped to synthetic evaluation.MethodsNeuroCon-AutismNet comprises four modules: (1) Temporal Diffusion Biomarker Generator (TDBG), a latent diffusion model over VAE-encoded 19-channel EEG; (2) Multilingual Affective Dialogue Screening Network (MADSN), a fine-tuned GPT-2-small module deployed in English, Spanish, and Hindi; (3) Neuro-Linguistic Fusion Transformer (NLFT), enforcing positional alignment as a design prior rather than learned cross-modal association; and (4) Adaptive Mixture-of-Experts Layer (AMEL-X) for entropy-regularized multimodal fusion. Formal (ε, δ)-differential privacy (ε = 1.0, δ = 1e-5) is verified via DP-SGD RDP composition (σ = 1.2, q = 0.0914, T = 550 steps, verified ε = 0.97). Privacy verification establishes architectural readiness for future real-data deployment; no real patient records are present in the training set.Results and DiscussionWithin closed synthetic evaluation, held-out diagnostic AUC is 0.503 (95% CI: 0.487–0.519, DeLong p = 0.67), statistically indistinguishable from chance and the central limitation of this study. Two partial external benchmarks are provided. Spectral comparison against three independently published real ASD EEG studies yields Pearson r = 0.87 across five frequency bands; delta and alpha directions are reproduced, but theta and gamma reproduce poorly with large amplitude errors (delta MAE 14.79%, alpha MAE 11.57%). Expert evaluation of MADSN outputs by 50 annotators under single-blind protocol yields 90% empathy satisfaction and Cohen’s κ = 0.82, reflecting text quality rather than clinical screening validity. The null diagnostic AUC and synthetic-only evaluation prevent any current screening or clinical-utility claims. Real-data EEG validation, clinician-caregiver interaction studies for MADSN, and DP-protected training on real patient records are prerequisites for future clinical deployment.