Analyzing direct and indirect genetic effects on early neurodevelopmental traits – a commentary on Hegemann et al / Yalan LI in Journal of Child Psychology and Psychiatry, 67-6 (June 2026)  

Public ISBD [article]  inJournal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.998-1000 Titre : Analyzing direct and indirect genetic effects on early neurodevelopmental traits – a commentary on Hegemann et al Type de document : texte imprimé Auteurs : Yalan LI, Auteur ; Tianjiao LIU, Auteur ; Xin LI, Auteur Article en page(s) : p.998-1000 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : The study by Hegemann et al. advances understanding of the genetic architecture underlying early neurodevelopmental traits by distinguishing direct and indirect genetic effects using Trio-GCTA and polygenic score models. Findings reveal that indirect genetic effects are particularly pronounced for hyperactivity and restricted and repetitive behaviors, while direct effects dominate in language and motor development. Notably, associations between parental cognitive and educational attainment polygenic scores and child outcomes suggest potential protective genetic influences. However, several methodological considerations may affect interpretation. Excluding closely related individuals could limit the detection of extended familial effects, and reliance on polygenic scores derived from predominantly European GWAS may constrain generalizability. Furthermore, current PGS explain only a portion of trait heritability, possibly underrepresenting true genetic contributions. Future studies incorporating extended family structures, diverse populations, and alternative methods to model gene?environment interplay are essential for refining insights into early neurodevelopmental processes. En ligne : https://doi.org/10.1111/jcpp.70070 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587 [article] Analyzing direct and indirect genetic effects on early neurodevelopmental traits – a commentary on Hegemann et al [texte imprimé] / Yalan LI, Auteur ; Tianjiao LIU, Auteur ; Xin LI, Auteur . - p.998-1000. Langues : Anglais (eng) in Journal of Child Psychology and Psychiatry > 67-6 (June 2026) . - p.998-1000 Index. décimale : PER Périodiques Résumé : The study by Hegemann et al. advances understanding of the genetic architecture underlying early neurodevelopmental traits by distinguishing direct and indirect genetic effects using Trio-GCTA and polygenic score models. Findings reveal that indirect genetic effects are particularly pronounced for hyperactivity and restricted and repetitive behaviors, while direct effects dominate in language and motor development. Notably, associations between parental cognitive and educational attainment polygenic scores and child outcomes suggest potential protective genetic influences. However, several methodological considerations may affect interpretation. Excluding closely related individuals could limit the detection of extended familial effects, and reliance on polygenic scores derived from predominantly European GWAS may constrain generalizability. Furthermore, current PGS explain only a portion of trait heritability, possibly underrepresenting true genetic contributions. Future studies incorporating extended family structures, diverse populations, and alternative methods to model gene?environment interplay are essential for refining insights into early neurodevelopmental processes. En ligne : https://doi.org/10.1111/jcpp.70070 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=587

Deep Neural Network Reveals the World of Autism From a First-Person Perspective / Mindi RUAN in Autism Research, 14-2 (February 2021)  

Public ISBD [article]  inAutism Research > 14-2 (February 2021) . - p.333-342 Titre : Deep Neural Network Reveals the World of Autism From a First-Person Perspective Type de document : texte imprimé Auteurs : Mindi RUAN, Auteur ; Paula J. WEBSTER, Auteur ; Xin LI, Auteur ; Shuo WANG, Auteur Article en page(s) : p.333-342 Langues : Anglais (eng) Mots-clés : artificial intelligence  attention  autism spectrum disorder  deep neural network  faces  photos  saliency Index. décimale : PER Périodiques Résumé : People with autism spectrum disorder (ASD) show atypical attention to social stimuli and aberrant gaze when viewing images of the physical world. However, it is unknown how they perceive the world from a first-person perspective. In this study, we used machine learning to classify photos taken in three different categories (people, indoors, and outdoors) as either having been taken by individuals with ASD or by peers without ASD. Our classifier effectively discriminated photos from all three categories, but was particularly successful at classifying photos of people with >80% accuracy. Importantly, visualization of our model revealed critical features that led to successful discrimination and showed that our model adopted a strategy similar to that of ASD experts. Furthermore, for the first time we showed that photos taken by individuals with ASD contained less salient objects, especially in the central visual field. Notably, our model outperformed classification of these photos by ASD experts. Together, we demonstrate an effective and novel method that is capable of discerning photos taken by individuals with ASD and revealing aberrant visual attention in ASD from a unique first-person perspective. Our method may in turn provide an objective measure for evaluations of individuals with ASD. LAY SUMMARY: People with autism spectrum disorder (ASD) demonstrate atypical visual attention to social stimuli. However, it remains largely unclear how they perceive the world from a first-person perspective. In this study, we employed a deep learning approach to analyze a unique dataset of photos taken by people with and without ASD. Our computer modeling was not only able to discern which photos were taken by individuals with ASD, outperforming ASD experts, but importantly, it revealed critical features that led to successful discrimination, revealing aspects of atypical visual attention in ASD from their first-person perspective. En ligne : http://dx.doi.org/10.1002/aur.2376 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441 [article] Deep Neural Network Reveals the World of Autism From a First-Person Perspective [texte imprimé] / Mindi RUAN, Auteur ; Paula J. WEBSTER, Auteur ; Xin LI, Auteur ; Shuo WANG, Auteur . - p.333-342. Langues : Anglais (eng) in Autism Research > 14-2 (February 2021) . - p.333-342 Mots-clés : artificial intelligence  attention  autism spectrum disorder  deep neural network  faces  photos  saliency Index. décimale : PER Périodiques Résumé : People with autism spectrum disorder (ASD) show atypical attention to social stimuli and aberrant gaze when viewing images of the physical world. However, it is unknown how they perceive the world from a first-person perspective. In this study, we used machine learning to classify photos taken in three different categories (people, indoors, and outdoors) as either having been taken by individuals with ASD or by peers without ASD. Our classifier effectively discriminated photos from all three categories, but was particularly successful at classifying photos of people with >80% accuracy. Importantly, visualization of our model revealed critical features that led to successful discrimination and showed that our model adopted a strategy similar to that of ASD experts. Furthermore, for the first time we showed that photos taken by individuals with ASD contained less salient objects, especially in the central visual field. Notably, our model outperformed classification of these photos by ASD experts. Together, we demonstrate an effective and novel method that is capable of discerning photos taken by individuals with ASD and revealing aberrant visual attention in ASD from a unique first-person perspective. Our method may in turn provide an objective measure for evaluations of individuals with ASD. LAY SUMMARY: People with autism spectrum disorder (ASD) demonstrate atypical visual attention to social stimuli. However, it remains largely unclear how they perceive the world from a first-person perspective. In this study, we employed a deep learning approach to analyze a unique dataset of photos taken by people with and without ASD. Our computer modeling was not only able to discern which photos were taken by individuals with ASD, outperforming ASD experts, but importantly, it revealed critical features that led to successful discrimination, revealing aspects of atypical visual attention in ASD from their first-person perspective. En ligne : http://dx.doi.org/10.1002/aur.2376 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=441

Visual Perspective Taking Training Improves Theory of Mind in Autistic Children / Mi TIAN in Autism Research, 19-8 (August 2026)  

Public ISBD [article]  inAutism Research > 19-8 (August 2026) . - p.e70309 Titre : Visual Perspective Taking Training Improves Theory of Mind in Autistic Children Type de document : texte imprimé Auteurs : Mi TIAN, Auteur ; Shiyue CAO, Auteur ; Xin LI, Auteur ; Wenyu XIA, Auteur ; Him CHEUNG, Auteur ; Xuezhen XIAO, Auteur ; Tianrui LUO, Auteur Article en page(s) : p.e70309 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  children  theory of mind  training  visual perspective taking Index. décimale : PER Périodiques Résumé : ABSTRACT Autistic children exhibit developmental differences in theory of mind (ToM), which is associated with social impairment. While numerous interventions have targeted other ToM precursor skills, few studies have explored the effect of visual perspective taking (VPT) training on ToM. The present study aims to investigate the effectiveness of VPT training on ToM in autistic children. Sixty-six autistic children were initially recruited and randomly assigned to three groups. Forty-eight children (mean age?=?5.75?years) completed the study and were included in the final analyses, comprising the VPT training group (n?=?16), thought-bubble training group (n?=?16), and control group (n?=?16). Each training comprised 12 sessions of 30?min. Both the VPT and thought-bubble training groups demonstrated significant improvements in VPT and ToM compared to the control group. The present study is the first to directly examine the effectiveness of VPT training using table blocks in enhancing ToM performance in autistic children, thereby providing a novel approach for ToM development. En ligne : https://doi.org/10.1002/aur.70309 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=589 [article] Visual Perspective Taking Training Improves Theory of Mind in Autistic Children [texte imprimé] / Mi TIAN, Auteur ; Shiyue CAO, Auteur ; Xin LI, Auteur ; Wenyu XIA, Auteur ; Him CHEUNG, Auteur ; Xuezhen XIAO, Auteur ; Tianrui LUO, Auteur . - p.e70309. Langues : Anglais (eng) in Autism Research > 19-8 (August 2026) . - p.e70309 Mots-clés : autism spectrum disorder  children  theory of mind  training  visual perspective taking Index. décimale : PER Périodiques Résumé : ABSTRACT Autistic children exhibit developmental differences in theory of mind (ToM), which is associated with social impairment. While numerous interventions have targeted other ToM precursor skills, few studies have explored the effect of visual perspective taking (VPT) training on ToM. The present study aims to investigate the effectiveness of VPT training on ToM in autistic children. Sixty-six autistic children were initially recruited and randomly assigned to three groups. Forty-eight children (mean age?=?5.75?years) completed the study and were included in the final analyses, comprising the VPT training group (n?=?16), thought-bubble training group (n?=?16), and control group (n?=?16). Each training comprised 12 sessions of 30?min. Both the VPT and thought-bubble training groups demonstrated significant improvements in VPT and ToM compared to the control group. The present study is the first to directly examine the effectiveness of VPT training using table blocks in enhancing ToM performance in autistic children, thereby providing a novel approach for ToM development. En ligne : https://doi.org/10.1002/aur.70309 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=589

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