Comparison of three different eye-tracking tasks for distinguishing autistic from typically developing children and autistic symptom severity / J. KOU in Autism Research, 12-10 (October 2019)  

Public ISBD [article]  inAutism Research > 12-10 (October 2019) . - p.1529-1540 Titre : Comparison of three different eye-tracking tasks for distinguishing autistic from typically developing children and autistic symptom severity Type de document : texte imprimé Auteurs : J. KOU, Auteur ; J. LE, Auteur ; M. FU, Auteur ; C. LAN, Auteur ; Z. CHEN, Auteur ; Q. LI, Auteur ; Weihua ZHAO, Auteur ; Lei XU, Auteur ; B. BECKER, Auteur ; K.M. KENDRICK, Auteur Article en page(s) : p.1529-1540 Langues : Anglais (eng) Mots-clés : Chinese children  attentional preference bias  autism spectrum disorder  dynamic social stimuli  eye-tracking Index. décimale : PER Périodiques Résumé : Altered patterns of visual social attention preference detected using eye-tracking and a variety of different paradigms are increasingly proposed as sensitive biomarkers for autism spectrum disorder. However, few eye-tracking studies have compared the relative efficacy of different paradigms to discriminate between autistic compared with typically developing children and their sensitivity to specific symptoms. To target this issue, the current study used three common eye-tracking protocols contrasting social versus nonsocial stimuli in young (2-7 years old) Chinese autistic (n = 35) and typically developing (n = 34) children matched for age and gender. Protocols included dancing people versus dynamic geometrical images, biological motion (dynamic light point walking human or cat) versus nonbiological motion (scrambled controls), and child playing with toy versus toy alone. Although all three paradigms differentiated autistic and typically developing children, the dancing people versus dynamic geometry pattern paradigm was the most effective, with autistic children showing marked reductions in visual preference for dancing people and correspondingly increased one for geometric patterns. Furthermore, this altered visual preference in autistic children was correlated with the Autism Diagnostic Observation Schedule social affect score and had the highest discrimination accuracy. Our results therefore indicate that decreased visual preference for dynamic social stimuli may be the most effective visual attention-based paradigm for use as a biomarker for autism in Chinese children. Clinical trial ID: NCT03286621 (clinicaltrials.gov); Clinical trial name: Development of Eye-tracking Based Markers for Autism in Young Children. Autism Res 2019, 12: 1529-1540. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Eye-tracking measures may be useful in aiding diagnosis and treatment of autism, although it is unclear which specific tasks are optimal. Here we compare the ability of three different social eye-gaze tasks to discriminate between autistic and typically developing young Chinese children and their sensitivity to specific autistic symptoms. Our results show that a dynamic task comparing visual preference for social (individuals dancing) versus geometric patterns is the most effective both for diagnosing autism and sensitivity to its social affect symptoms. En ligne : http://dx.doi.org/10.1002/aur.2174 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=408 [article] Comparison of three different eye-tracking tasks for distinguishing autistic from typically developing children and autistic symptom severity [texte imprimé] / J. KOU, Auteur ; J. LE, Auteur ; M. FU, Auteur ; C. LAN, Auteur ; Z. CHEN, Auteur ; Q. LI, Auteur ; Weihua ZHAO, Auteur ; Lei XU, Auteur ; B. BECKER, Auteur ; K.M. KENDRICK, Auteur . - p.1529-1540. Langues : Anglais (eng) in Autism Research > 12-10 (October 2019) . - p.1529-1540 Mots-clés : Chinese children  attentional preference bias  autism spectrum disorder  dynamic social stimuli  eye-tracking Index. décimale : PER Périodiques Résumé : Altered patterns of visual social attention preference detected using eye-tracking and a variety of different paradigms are increasingly proposed as sensitive biomarkers for autism spectrum disorder. However, few eye-tracking studies have compared the relative efficacy of different paradigms to discriminate between autistic compared with typically developing children and their sensitivity to specific symptoms. To target this issue, the current study used three common eye-tracking protocols contrasting social versus nonsocial stimuli in young (2-7 years old) Chinese autistic (n = 35) and typically developing (n = 34) children matched for age and gender. Protocols included dancing people versus dynamic geometrical images, biological motion (dynamic light point walking human or cat) versus nonbiological motion (scrambled controls), and child playing with toy versus toy alone. Although all three paradigms differentiated autistic and typically developing children, the dancing people versus dynamic geometry pattern paradigm was the most effective, with autistic children showing marked reductions in visual preference for dancing people and correspondingly increased one for geometric patterns. Furthermore, this altered visual preference in autistic children was correlated with the Autism Diagnostic Observation Schedule social affect score and had the highest discrimination accuracy. Our results therefore indicate that decreased visual preference for dynamic social stimuli may be the most effective visual attention-based paradigm for use as a biomarker for autism in Chinese children. Clinical trial ID: NCT03286621 (clinicaltrials.gov); Clinical trial name: Development of Eye-tracking Based Markers for Autism in Young Children. Autism Res 2019, 12: 1529-1540. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Eye-tracking measures may be useful in aiding diagnosis and treatment of autism, although it is unclear which specific tasks are optimal. Here we compare the ability of three different social eye-gaze tasks to discriminate between autistic and typically developing young Chinese children and their sensitivity to specific autistic symptoms. Our results show that a dynamic task comparing visual preference for social (individuals dancing) versus geometric patterns is the most effective both for diagnosing autism and sensitivity to its social affect symptoms. En ligne : http://dx.doi.org/10.1002/aur.2174 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=408

Facial emotion training as an intervention in autism spectrum disorder: A meta-analysis of randomized controlled trials / Qianqian ZHANG in Autism Research, 14-10 (October 2021)  

Public ISBD [article]  inAutism Research > 14-10 (October 2021) . - p.2169-2182 Titre : Facial emotion training as an intervention in autism spectrum disorder: A meta-analysis of randomized controlled trials Type de document : texte imprimé Auteurs : Qianqian ZHANG, Auteur ; Renjing WU, Auteur ; S. ZHU, Auteur ; J. LE, Auteur ; Y. CHEN, Auteur ; C. LAN, Auteur ; S. YAO, Auteur ; Weihua ZHAO, Auteur ; K.M. KENDRICK, Auteur Article en page(s) : p.2169-2182 Langues : Anglais (eng) Mots-clés : Autism Spectrum Disorder/therapy  Emotions  Facial Recognition  Humans  Randomized Controlled Trials as Topic  Social Skills  autism spectrum disorder  emotion expression  emotion recognition  emotion understanding  facial emotion training  meta-analysis  social skills Index. décimale : PER Périodiques Résumé : A large number of computer-based training programs have been developed as an intervention to help individuals with autism spectrum disorders (ASD) improve their facial emotion recognition ability, as well as social skills. However, it is unclear to what extent these facial emotion training programs can produce beneficial, long-lasting, and generalizable results. Using standard meta-analytic techniques, we investigated the effects of facial emotion training including generalization and maintenance restricted to randomized control trial studies comprising a total of 595 individuals with ASD. Our findings revealed that the intervention resulted in a robust improvement in emotion recognition for individuals receiving training compared with controls. However, while there was also some evidence for generalization of training effects, the small number of studies which conducted follow-ups and assessed social skills reported that improvements were not maintained and there was no evidence for general improvement in social skills. Overall, the analysis revealed a medium effect size in training improvement indicating that facial emotion training may be an effective method for enhancing emotion recognition skills in ASD although more studies are required to assess maintenance of effects and possible general improvements in social skills. LAY SUMMARY: Facial emotion training as an intervention may be a potential way to help improve emotion recognition in autism spectrum disorder (ASD), however robust empirical support for its efficacy has not been sufficiently established. Here, we conducted a meta-analysis of previous studies to summarize the effects of facial emotion training on ASD. Our results show that the training produces a robust improvement in subsequent emotion recognition, while maintenance and generalization effects still need further investigation. To date, no experimentally verified improvements in social skills have been reported. En ligne : http://dx.doi.org/10.1002/aur.2565 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=450 [article] Facial emotion training as an intervention in autism spectrum disorder: A meta-analysis of randomized controlled trials [texte imprimé] / Qianqian ZHANG, Auteur ; Renjing WU, Auteur ; S. ZHU, Auteur ; J. LE, Auteur ; Y. CHEN, Auteur ; C. LAN, Auteur ; S. YAO, Auteur ; Weihua ZHAO, Auteur ; K.M. KENDRICK, Auteur . - p.2169-2182. Langues : Anglais (eng) in Autism Research > 14-10 (October 2021) . - p.2169-2182 Mots-clés : Autism Spectrum Disorder/therapy  Emotions  Facial Recognition  Humans  Randomized Controlled Trials as Topic  Social Skills  autism spectrum disorder  emotion expression  emotion recognition  emotion understanding  facial emotion training  meta-analysis  social skills Index. décimale : PER Périodiques Résumé : A large number of computer-based training programs have been developed as an intervention to help individuals with autism spectrum disorders (ASD) improve their facial emotion recognition ability, as well as social skills. However, it is unclear to what extent these facial emotion training programs can produce beneficial, long-lasting, and generalizable results. Using standard meta-analytic techniques, we investigated the effects of facial emotion training including generalization and maintenance restricted to randomized control trial studies comprising a total of 595 individuals with ASD. Our findings revealed that the intervention resulted in a robust improvement in emotion recognition for individuals receiving training compared with controls. However, while there was also some evidence for generalization of training effects, the small number of studies which conducted follow-ups and assessed social skills reported that improvements were not maintained and there was no evidence for general improvement in social skills. Overall, the analysis revealed a medium effect size in training improvement indicating that facial emotion training may be an effective method for enhancing emotion recognition skills in ASD although more studies are required to assess maintenance of effects and possible general improvements in social skills. LAY SUMMARY: Facial emotion training as an intervention may be a potential way to help improve emotion recognition in autism spectrum disorder (ASD), however robust empirical support for its efficacy has not been sufficiently established. Here, we conducted a meta-analysis of previous studies to summarize the effects of facial emotion training on ASD. Our results show that the training produces a robust improvement in subsequent emotion recognition, while maintenance and generalization effects still need further investigation. To date, no experimentally verified improvements in social skills have been reported. En ligne : http://dx.doi.org/10.1002/aur.2565 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=450

Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder / Peng QING in Molecular Autism, 15 (2024)  

Public ISBD [article]  inMolecular Autism > 15 (2024) . - 43p. Titre : Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder Type de document : texte imprimé Auteurs : Peng QING, Auteur ; Xiaodong ZHANG, Auteur ; Qi LIU, Auteur ; Linghong HUANG, Auteur ; Dan XU, Auteur ; Jiao LE, Auteur ; Keith M. KENDRICK, Auteur ; Hua LAI, Auteur ; Weihua ZHAO, Auteur Article en page(s) : 43p. Langues : Anglais (eng) Mots-clés : Humans  White Matter/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/physiopathology/diagnostic imaging  Male  Female  Diffusion Tensor Imaging  Adolescent  Child  Adult  Young Adult  Structure-Activity Relationship  Magnetic Resonance Imaging  Autism spectrum disorder  Diffusion tensor  Functional connectivity tensor  Structure-function coupling  White matter tracts Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored. METHODS: In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone). RESULTS: In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores. CONCLUSION: This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD. En ligne : https://dx.doi.org/10.1186/s13229-024-00620-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538 [article] Structure-function coupling in white matter uncovers the hypoconnectivity in autism spectrum disorder [texte imprimé] / Peng QING, Auteur ; Xiaodong ZHANG, Auteur ; Qi LIU, Auteur ; Linghong HUANG, Auteur ; Dan XU, Auteur ; Jiao LE, Auteur ; Keith M. KENDRICK, Auteur ; Hua LAI, Auteur ; Weihua ZHAO, Auteur . - 43p. Langues : Anglais (eng) in Molecular Autism > 15 (2024) . - 43p. Mots-clés : Humans  White Matter/diagnostic imaging/pathology/physiopathology  Autism Spectrum Disorder/physiopathology/diagnostic imaging  Male  Female  Diffusion Tensor Imaging  Adolescent  Child  Adult  Young Adult  Structure-Activity Relationship  Magnetic Resonance Imaging  Autism spectrum disorder  Diffusion tensor  Functional connectivity tensor  Structure-function coupling  White matter tracts Index. décimale : PER Périodiques Résumé : BACKGROUND: Autism Spectrum Disorder (ASD) is a neurodevelopmental disorder associated with alterations in structural and functional coupling in gray matter. However, despite the detectability and modulation of brain signals in white matter, the structure-function coupling in white matter in autism remains less explored. METHODS: In this study, we investigated structural-functional coupling in white matter (WM) regions, by integrating diffusion tensor data that contain fiber orientation information from WM tracts, with functional connectivity tensor data that reflect local functional anisotropy information. Using functional and diffusion magnetic resonance images, we analyzed a cohort of 89 ASD and 63 typically developing (TD) individuals from the Autism Brain Imaging Data Exchange II (ABIDE-II). Subsequently, the associations between structural-functional coupling in WM regions and ASD severity symptoms assessed by Autism Diagnostic Observation Schedule-2 were examined via supervised machine learning in an independent test cohort of 29 ASD individuals. Furthermore, we also compared the performance of multi-model features (i.e. structural-functional coupling) with single-model features (i.e. functional or structural models alone). RESULTS: In the discovery cohort (ABIDE-II), individuals with ASD exhibited widespread reductions in structural-functional coupling in WM regions compared to TD individuals, particularly in commissural tracts (e.g. corpus callosum), association tracts (sagittal stratum), and projection tracts (e.g. internal capsule). Notably, supervised machine learning analysis in the independent test cohort revealed a significant correlation between these alterations in structural-functional coupling and ASD severity scores. Furthermore, compared to single-model features, the integration of multi-model features (i.e., structural-functional coupling) performed best in predicting ASD severity scores. CONCLUSION: This work provides novel evidence for atypical structural-functional coupling in ASD in white matter regions, further refining our understanding of the critical role of WM networks in the pathophysiology of ASD. En ligne : https://dx.doi.org/10.1186/s13229-024-00620-6 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=538

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