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Détail de l'auteur
Auteur Shuo WANG |
Documents disponibles écrits par cet auteur (2)
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Deep Neural Network Reveals the World of Autism From a First-Person Perspective / Mindi RUAN in Autism Research, 14-2 (February 2021)
[article]
Titre : Deep Neural Network Reveals the World of Autism From a First-Person Perspective Type de document : Texte imprimé et/ou numérique 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
in Autism Research > 14-2 (February 2021) . - p.333-342[article] Deep Neural Network Reveals the World of Autism From a First-Person Perspective [Texte imprimé et/ou numérique] / 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 Reduced Pupil Oscillation During Facial Emotion Judgment in People with Autism Spectrum Disorder / Sai SUN in Journal of Autism and Developmental Disorders, 53-5 (May 2023)
[article]
Titre : Reduced Pupil Oscillation During Facial Emotion Judgment in People with Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Sai SUN, Auteur ; Paula J. WEBSTER, Auteur ; Yu WANG, Auteur ; Hongbo YU, Auteur ; Rongjun YU, Auteur ; Shuo WANG, Auteur Article en page(s) : p.1963-1973 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : People with autism spectrum disorder (ASD) show abnormal face perception and emotion recognition. However, it remains largely unknown whether these differences are associated with abnormal physiological responses when viewing faces. In this study, we employed a sensitive emotion judgment task and conducted a detailed investigation of pupil dilation/constriction and oscillation in high-functioning adult participants with ASD and matched controls. We found that participants with ASD showed normal pupil constriction to faces; however, they demonstrated reduced pupil oscillation, which was independent of stimulus properties and participants' perception of the emotion. Together, our results have revealed an abnormal physiological response to faces in people with ASD, which may in turn be associated with impaired face perception previously found in many studies. En ligne : https://doi.org/10.1007/s10803-022-05478-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=501
in Journal of Autism and Developmental Disorders > 53-5 (May 2023) . - p.1963-1973[article] Reduced Pupil Oscillation During Facial Emotion Judgment in People with Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Sai SUN, Auteur ; Paula J. WEBSTER, Auteur ; Yu WANG, Auteur ; Hongbo YU, Auteur ; Rongjun YU, Auteur ; Shuo WANG, Auteur . - p.1963-1973.
Langues : Anglais (eng)
in Journal of Autism and Developmental Disorders > 53-5 (May 2023) . - p.1963-1973
Index. décimale : PER Périodiques Résumé : People with autism spectrum disorder (ASD) show abnormal face perception and emotion recognition. However, it remains largely unknown whether these differences are associated with abnormal physiological responses when viewing faces. In this study, we employed a sensitive emotion judgment task and conducted a detailed investigation of pupil dilation/constriction and oscillation in high-functioning adult participants with ASD and matched controls. We found that participants with ASD showed normal pupil constriction to faces; however, they demonstrated reduced pupil oscillation, which was independent of stimulus properties and participants' perception of the emotion. Together, our results have revealed an abnormal physiological response to faces in people with ASD, which may in turn be associated with impaired face perception previously found in many studies. En ligne : https://doi.org/10.1007/s10803-022-05478-2 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=501