1. Al-Mazidi S, Alhowikan A, Elamin N, Abualnaja A, Al-Mnaizel A, Alharbi T, Al-Ayadhi L. Cognitive function and retinal biomarkers as novel approach to diagnosing and assessing autism spectrum disorder. Sci Rep. 2025; 15(1): 17946.

The retina is invariably considered an extension of the central nervous system and can predict cognitive impairment in neurodevelopmental and neurodegenerative disorders. This is due to the physiological and embryological link between the retina and the brain. Since this correlation was not previously tested in autism spectrum disorder (ASD), we aim to provide evidence for a correlation between retinal dysfunction and cognitive impairment in ASD children through previously reported retina and cognitive dysfunction biomarkers. 80 children were recruited to test biomarkers of the retinal function, Ciliary neurotrophic factor (CNTF), and cognitive function A Disintegrin and Metalloproteases 10 (ADAM10). These biomarkers were correlated with the Childhood Autism Rating Score (CARS) to distinguish ASD from cognitive impairment disorders and the Short Sensory Profile (SSP) as a sensory impairment indicator, including vision. ADAM10 was significantly decreased in ASD children compared to neurotypical children (p < 0.01). It also decreased as the severity of autism increased, as measured by CARS. We also found that CNTF decreases in ASD children with moderate severity compared to neurotypical and severe ASD groups, indicating that CNTF can be an early indicator of ASD. ADAM10 was directly related to CNTF, implying the direct correlation between the eye and cognitive function in ASD. ADAM10 is a potential indicator of cognitive function in ASD, and CNTF can be an indicator of retina function. The relationship between both biomarkers might serve as early diagnosis biomarkers and a potential therapeutic target in ASD.

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2. Denisova K, Wolpert DM. Protocol to investigate sensorimotor features in young children with autism using functional and resting-state fMRI data from the NIMH Data Archive. STAR Protoc. 2025; 6(2): 103827.

Head movements cause artifacts in infant neuroimaging that can often render acquired data unusable. Here, we present a protocol that harnesses head motion from fMRI and resting-state (rs)-fMRI NIMH Data Archive (NDA) data to obtain quantitative measures of sensorimotor function in young children and associate them with future cognitive and autism outcomes. We describe steps for downloading, organizing, and pre-processing fMRI data to yield data on in-scan head motion. We then detail procedures for preparing phenotypic data to link with sensorimotor data. For complete details on the use and execution of this protocol, please refer to Denisova and Wolpert.(1).

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3. Ferreira GJ. Commentary: Toward a more comprehensive autism assessment: the survey of autistic strengths, skills, and interests. Front Psychiatry. 2025; 16: 1552960.

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4. Hadad E, Segal O. Theory of Mind Abilities and Comprehension of Mental Terms in Subgroups of Children With Autism Spectrum Disorder and Developmental Language Disorder. J Speech Lang Hear Res. 2025: 1-15.

PURPOSE: This study examined how subgroups of children with autism spectrum disorder (ASD) and developmental language disorder (DLD) perform on theory of mind (ToM) tasks and comprehend mental terms. METHOD: Eighty Hebrew-speaking children aged 5-6 years were divided into four groups: children with DLD, ASD and language impairment (ASD-LI), and ASD and typical language abilities (ASD-LN) and typically developing (TD) peers. Language was assessed using the Hebrew Goralnik test. All participants had an average nonverbal IQ (> 85). Comprehension of mental terms, including the factive verb know, the nonfactive verbs think and guess, and the adjective sure, was evaluated contrasting these terms by using 12 paired stimuli organized into three sets. RESULTS: TD children scored highest on the Theory of Mind Task Battery (ToMTB), followed by ASD-LN, ASD-LI, and DLD groups. For factive and nonfactive terms (FNFTs), ASD-LN performed highest, followed by TD, DLD, and ASD-LI. One-way analyses of covariance controlling for nonverbal IQ revealed significant group differences. Pairwise comparisons demonstrated that TD and ASD-LN outperformed ASD-LI and DLD on the ToMTB and FNFTs. Hierarchical regression analysis indicated that both nonverbal intelligence and language ability significantly predicted ToM performance. The addition of FNFT comprehension increased the explanatory power of the model. CONCLUSIONS: This study underscores differences in ToM and FNFT comprehension across subgroups and highlights similarities between ASD-LI and DLD. These findings emphasize the strong link between language skills and ToM abilities, with FNFT comprehension playing a crucial role in ToM development.

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5. K VRP, Hima Bindu C, Devi KRM. An Interpretable Deep Learning Approach for Autism Spectrum Disorder Detection in Children Using NASNet-Mobile. Biomed Phys Eng Express. 2025.

Autism spectrum disorder (ASD) is a multifaceted neurodevelopmental disorder featuring impaired social interactions and communication abilities engaging the individuals in a restrictive or repetitive behaviour. Though incurable early detection and intervention can reduce the severity of symptoms. Structural magnetic resonance imaging (sMRI) can improve diagnostic accuracy, facilitating early diagnosis to offer more tailored care. With the emergence of deep learning (DL), neuroimaging-based approaches for ASD diagnosis have been focused. However, many existing models lack interpretability of their decisions for diagnosis. The prime objective of this work is to perform ASD classification precisely and to interpret the classification process in a better way so as to discern the major features that are appropriate for the prediction of disorder. The proposed model employs neural architecture search network – mobile(NASNet-Mobile) model for ASD detection, which is integrated with an explainable artificial intelligence (XAI) technique called local interpretable model-agnostic explanations (LIME) for increased transparency of ASD classification. The model is trained on sMRI images of two age groups taken from autism brain imaging data exchange-I (ABIDE-I) dataset. The proposed model yielded accuracy of 0.9607, F1-score of 0.9614, specificity of 0.9774, sensitivity of 0.9451, negative predicted value (NPV) of 0.9429, positive predicted value (PPV) of 0.9783 and the diagnostic odds ratio of 745.59 for 2 to 11 years age group compared to 12 to 18 years group. These results are superior compared to other state of the art models Inception v3 and SqueezeNet.

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6. Kang X, Chen K, Wang F, Mu L, Lei Z, Zhang R, Wang Z, Zhang T. rTMS-induced neuroimaging changes measured with structural and functional MRI in autism. Front Neurosci. 2025; 19: 1582354.

INTRODUCTION: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by deficits in social communication, repetitive behaviors, and restricted interests. Despite increasing prevalence, effective therapeutic interventions remain limited. Repetitive transcranial magnetic stimulation (rTMS) has emerged as a promising non-invasive neuromodulation technique; however, its neural mechanisms and clinical efficacy in children with ASD require further investigation. METHODS: This study enrolled 14 children diagnosed with ASD to undergo a structured rTMS intervention. Neuroimaging data-including voxel-based morphometry (VBM) and resting-state functional connectivity (FC)-as well as behavioral assessments were collected before and after the intervention to evaluate changes in brain structure, function, and symptomatology. RESULTS: Post-intervention analyses revealed significant increases in gray matter volume (GMV) in the cerebellar Vermis, Caudate nucleus, and Postcentral gyrus. Additionally, enhanced functional connectivity was observed between the Fusiform gyrus, Temporal cortex, Frontal cortex, and Precuneus. Correlation analyses indicated that these neuroimaging changes were significantly associated with improvements in behavioral scores. DISCUSSION: These findings suggest that rTMS may exert therapeutic effects in children with ASD by modulating cerebellar development and cognitive control networks. The observed structural and functional brain changes support the potential utility of rTMS as a neuromodulatory intervention for ASD. Further studies with larger cohorts are needed to confirm these preliminary results and elucidate the mechanisms underlying rTMS-induced symptom improvement.

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7. Konopka G. Introduction to the Special Section on the Genetics of Autism. Autism Res. 2025; 18(5): 896-7.

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8. Lamônica D, Rosa KG, Ribeiro E, da Rocha E, Martins MF, Giacheti CM. Clinical features, behaviour and language in Wolf-Hirschhorn syndrome. BMJ Case Rep. 2025; 18(5).

Wolf-Hirschhorn syndrome (WHS) is associated with intellectual disability and multiple congenital anomalies. A female patient with WHS was evaluated at two different times, in childhood and adolescence. Clinical examinations of various medical specialties and assessments of language and behaviour were carried out. In childhood, she showed signs of autism spectrum disorder, as well as other phenotypic characteristics. The impact of this chromosomal anomaly has had repercussions on neurodevelopment and needs to be better understood. This case highlights the serious impairment in both language and behaviour, despite investments in lifelong intervention processes. More research is required to understand WHS’ deleterious effects on development, specifically on language and behaviour.

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9. Medeiros S, Cohn N, Foulsham T, Coderre EL. Association of autistic traits with inference generation in visual narratives. Sci Rep. 2025; 15(1): 17746.

Individuals with higher levels of autistic traits sometimes demonstrate differences with narrative comprehension compared to those with lower levels of autistic traits. One particular aspect of narrative processing that is thought to be affected by autistic traits is inferencing. Some studies using verbal narratives (i.e., written or spoken stories) have documented differences in inferencing skills among autistic participants. However, fewer studies have investigated how inferencing abilities using visual narratives (e.g., comics) are modulated by autistic traits, despite mounting evidence that narrative comprehension shares similar cognitive mechanisms across verbal and visual domains. Here, we report two studies examining inference generation during visual narrative comprehension in adults with a range of autistic traits. Experiment 1 used a deletion recognition paradigm to examine participants’ accuracy (ACC) and reaction time (RT) to identify where a panel had been removed from a visual sequence. Experiment 2 used a self-paced viewing paradigm to examine viewing times on sequences that required an inference; ACC and RT on comprehension questions were also examined. In both experiments, individual differences in autistic traits and visual language fluency were examined. In Experiment 1 we did not see any effects of these predictors; however, for Experiment 2 we found that autistic traits and visual language fluency may be influential in narrative comprehension for measures of offline processing. Subsequent analyses identified differences in imaginative abilities as potentially underlying these modulations.

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10. Meng X, Zhou X, Luo J, Li J, Zhou L, Zhang Y. A bibliometric analysis of the current state of research on family interventions for ASD. Front Psychiatry. 2025; 16: 1435612.

In recent years, family intervention has become a hot research direction in the field of autism spectrum disorder (ASD) treatment. A large amount of research literature shows that family intervention is effective in ASD rehabilitation. Still, the concept of family intervention is vaguely defined, and there is a lack of descriptions of specific intervention programs and treatment pathways and a diversity of intervention programs have been reported. In this study, we conducted an econometric analysis of the literature on family intervention for ASD to clarify the concept of family intervention and to analyze and explore the research hotspots, effective family intervention models for ASD, intervention techniques, and possible future research directions in this field. METHODS: A metrological analysis of the literature related to ASD family interventions on the Web of Science from 1987 to 2024 was conducted using CiteSpace software to map the network of countries/institutions, journals, authors, co-cited literature, and keywords in the field. The results were visualized and analyzed. RESULTS: A total of 1,891 documents were retrieved. The United States (1,028) led in the number and relevance of publications, followed by Canada (254) and Australia (209). The trend of publications was upward. Baranek was the most published author (19) and the University of California System was the most published university. Developed countries dominate the research. According to the timeline graph, it can be learned that the current research hotspots in this field are mostly focused on early intervention in family-based, psychological stress in parents of children with autism. CONCLUSION: This visual analysis identifies the most influential institutions and countries, as well as cited journals and authors in the field of family therapy autism research. The direction of research in family therapy for autism should be to find effective treatments for autism based on the home environment, and currently, the most prominent family therapy for autism is telemedicine and parent-mediated intervention. The future direction of this research area could be taken by artificial intelligence techniques specifically applied to children with autism in a computer context.

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11. Paolizzi E, Perzolli S, Bentenuto A. Mothers and fathers’ perception of social-responsive behaviors of autistic individuals. Res Dev Disabil. 2025; 163: 105045.

BACKGROUND: The interplay between behavioral differences presented by autistic males and females, and gender norms might influence caregivers’ behavior perceptions, contributing to the later identification of autistic females. AIM: Our study aims to investigate differences in mothers’ and fathers’ perceptions of children’s behaviors typically associated with autism. Further, we aim to analyze parental perception of children’s behaviors in relation to their offspring’s sex. Second, our objective is to examine differences in the perception of behaviors of males and females to better understand females’ phenotypes and potential reasons for their underdiagnosis METHODS: The sample consisted of 40 children and adolescents (M chronological age = 8.75 years, SD = 1.10, Range = 4-16.75), 20 males and 20 females, with their mothers and fathers. Parental perceptions are studied through the Social Responsiveness Scale, a quantitative report instrument that assesses autistic characteristics. RESULTS: Mothers and fathers reported similar profiles of their children. However, females presented better abilities in relation to Social Communication and fewer Mannerisms than males. However, clinicians’ observations scores related to the ADOS-2 did not show evidence of differences in behavioural characteristics typically associated with autism. CONCLUSIONS: These mechanisms should be further explored as they might partly determine females’ later diagnosis. Children’s age plays a significant role, as older individuals present more severe behaviors associated with autism in the dimensions previously mentioned and Social Motivation. Hence, a late diagnosis can exacerbate behavioral presentation of autism.

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12. Plate SN. The State of Natural Language Sampling in Autism Research: A Scoping Review. Autism Dev Lang Impair. 2025; 10: 23969415251341247.

BACKGROUND AND AIMS: Caregiver reports and standardized assessments have been the primary methods used to study language development in autism. However, these forms of measurement are often coarse, complicated by floor effects and reporter bias, and limited by the fact that they only capture how children can use language at a single moment in time, rather than how children actually use language during everyday interactions. These limitations have led to recent calls for the use of natural language sampling (NLS) as a fine-grained, developmentally appropriate, and contextually relevant measure of everyday communication. The number of studies using NLS to study language in autism has increased substantially in the last 15 years, resulting in a wide array of sampling methods and measures. Given both the increasing prevalence of NLS methods in the autism literature and the variability in sampling approaches and measures, this scoping review addresses the following questions: 1. What populations have been studied using NLS?2. Which data collection methods are most prevalent in NLS research?3. How are measures of language derived from NLS? METHOD: Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines, a search for studies published in the last 15 years across three databases was conducted. After removing duplicates, 4,671 titles and abstracts were screened and 59 papers met inclusion criteria. Sample characteristics, natural language collection methods, and derived measures were extracted and tabled for each study. The most prevalent NLS methods and measures in autism language research are reviewed and the benefits and drawbacks of various methods are discussed. MAIN CONTRIBUTION: This scoping review highlights subgroups of the autistic population that have been underrepresented in NLS studies-in particular, minimally/nonspeaking school-aged autistic children. This article also examines means to collect a « naturalistic » sample of language. Notably, studies did not address whether autistic children exhibit different social communication skills when talking to different types of social partners. Broadly, research has underreported key methodological details, making comparisons across studies difficult. CONCLUSIONS: This review highlights the appropriate use of NLS across development in autism and makes recommendations for NLS future research. IMPLICATIONS: Additional work is needed to address the gaps described in this article and replicate previous findings to identify patterns of natural language across the literature.

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13. Pokhrel P, Joshi S, Fatima L. Artificial intelligence in autism spectrum disorder: A path to early detection and improved outcomes. Asian J Psychiatr. 2025; 109: 104530.

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14. Swarup G, Andreae S, Pickett K, Columna L. Exploring yoga attitudes and social influences among mothers of autistic children through the theory of planned behavior. Disabil Health J. 2025: 101852.

BACKGROUND: Mothers of autistic children face physiological and psychological health concerns and encounter significant barriers to engaging in health-enhancing behaviors. While yoga may improve physical and emotional well-being in parents with children with disabilities, research on yoga programs designed specifically for mothers of autistic children remains limited. Developing accessible and motivating yoga interventions requires an understanding of attitudes toward yoga within this population. OBJECTIVE: The purpose of this study was to explore the attitudes of mothers of autistic children toward yoga and investigate how yoga was perceived within their social environment. METHODS: The Theory of Planned Behavior guided this descriptive-qualitative study, in which participants were mothers (N = 12) of autistic children aged 3-22 years. Data were collected through semi-structured interviews, transcribed verbatim, and analyzed using line-by-line thematic analysis. RESULTS: Three major themes were constructed: (1) Positive beginnings with yoga; (2) Yoga’s impact on holistic well-being; and (3) Influence of social circles on yoga attitudes. CONCLUSIONS: Mothers expressed positive attitudes towards yoga, influenced by their past experiences and perceived benefits. Yoga was positively regarded within mothers’ social networks, which reinforced their attitudes. Despite positive attitudes and supportive subjective norms, most mothers were not actively practicing yoga. This suggests the need to explore potential barriers, which may restrict mothers’ participation in yoga.

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15. Zhang B, Geddes CE, Jin X. Complementary corticostriatal circuits orchestrate action repetition and switching. Sci Adv. 2025; 11(21): eadt0854.

Action sequencing is fundamental to behavior. A critical decision for survival and reproduction is whether to repeat a current action or switch to a different one. However, the neural mechanisms governing action repetition and switching remain largely unknown. In mice trained to perform heterogeneous action sequences, we found that the M1-DLS circuit regulates action repetition, while the PrL-DMS pathway controls action switching. These distinct functions arise from preferential innervation of striatal D1-SPNs by M1 and D2-SPNs by PrL, respectively. In a Shank3 knockout mouse model of ASD, the D1/D2 innervation ratio in the PrL-DMS pathway was reversed, leading to impaired action switching and repetitive behaviors. Genetic restoration of Shank3 in the DMS rescued both physiological and behavioral deficits. These findings reveal how the brain orchestrates action sequencing in health and disease.

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