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Auteur Kai CHEN |
Documents disponibles écrits par cet auteur (2)
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Identification and analysis of autism spectrum disorder via large-scale dynamic functional network connectivity / Wenwen ZHUANG in Autism Research, 16-8 (August 2023)
[article]
Titre : Identification and analysis of autism spectrum disorder via large-scale dynamic functional network connectivity Type de document : Texte imprimé et/ou numérique Auteurs : Wenwen ZHUANG, Auteur ; Hai JIA, Auteur ; Yunhong LIU, Auteur ; Jing CONG, Auteur ; Kai CHEN, Auteur ; Dezhong YAO, Auteur ; Xiaodong KANG, Auteur ; Peng XU, Auteur ; Tao ZHANG, Auteur Article en page(s) : p.1512-1526 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with severe cognitive impairment. Several studies have reported that brain functional network connectivity (FNC) has great potential for identifying ASD from healthy control (HC) and revealing the relationships between the brain and behaviors of ASD. However, few studies have explored dynamic large-scale FNC as a feature to identify individuals with ASD. This study used a time-sliding window method to study the dynamic FNC (dFNC) on the resting-state fMRI. To avoid arbitrarily determining the window length, we set a window length range of 10-75 TRs (TR=2?s). We constructed linear support vector machine classifiers for all window length conditions. Using a nested 10-fold cross-validation framework, we obtained a grand average accuracy of 94.88% across window length conditions, which is higher than those reported in previous studies. In addition, we determined the optimal window length using the highest classification accuracy of 97.77%. Based on the optimal window length, we found that the dFNCs were located mainly in dorsal and ventral attention networks (DAN and VAN) and exhibited the highest weight in classification. Specifically, we found that the dFNC between DAN and temporal orbitofrontal network (TOFN) was significantly negatively correlated with social scores of ASD. Finally, using the dFNCs with high classification weights as features, we construct a model to predict the clinical score of ASD. Overall, our findings demonstrated that the dFNC could be a potential biomarker to identify ASD and provide new perspectives to detect cognitive changes in ASD. En ligne : https://doi.org/10.1002/aur.2974 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=510
in Autism Research > 16-8 (August 2023) . - p.1512-1526[article] Identification and analysis of autism spectrum disorder via large-scale dynamic functional network connectivity [Texte imprimé et/ou numérique] / Wenwen ZHUANG, Auteur ; Hai JIA, Auteur ; Yunhong LIU, Auteur ; Jing CONG, Auteur ; Kai CHEN, Auteur ; Dezhong YAO, Auteur ; Xiaodong KANG, Auteur ; Peng XU, Auteur ; Tao ZHANG, Auteur . - p.1512-1526.
Langues : Anglais (eng)
in Autism Research > 16-8 (August 2023) . - p.1512-1526
Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is a prevalent neurodevelopmental disorder with severe cognitive impairment. Several studies have reported that brain functional network connectivity (FNC) has great potential for identifying ASD from healthy control (HC) and revealing the relationships between the brain and behaviors of ASD. However, few studies have explored dynamic large-scale FNC as a feature to identify individuals with ASD. This study used a time-sliding window method to study the dynamic FNC (dFNC) on the resting-state fMRI. To avoid arbitrarily determining the window length, we set a window length range of 10-75 TRs (TR=2?s). We constructed linear support vector machine classifiers for all window length conditions. Using a nested 10-fold cross-validation framework, we obtained a grand average accuracy of 94.88% across window length conditions, which is higher than those reported in previous studies. In addition, we determined the optimal window length using the highest classification accuracy of 97.77%. Based on the optimal window length, we found that the dFNCs were located mainly in dorsal and ventral attention networks (DAN and VAN) and exhibited the highest weight in classification. Specifically, we found that the dFNC between DAN and temporal orbitofrontal network (TOFN) was significantly negatively correlated with social scores of ASD. Finally, using the dFNCs with high classification weights as features, we construct a model to predict the clinical score of ASD. Overall, our findings demonstrated that the dFNC could be a potential biomarker to identify ASD and provide new perspectives to detect cognitive changes in ASD. En ligne : https://doi.org/10.1002/aur.2974 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=510 Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder / Jinping XU in Autism Research, 13-3 (March 2020)
[article]
Titre : Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Jinping XU, Auteur ; Chao WANG, Auteur ; Ziyun XU, Auteur ; Tian LI, Auteur ; Fangfang CHEN, Auteur ; Kai CHEN, Auteur ; Jingjing GAO, Auteur ; Jiaojian WANG, Auteur ; Qingmao HU, Auteur Article en page(s) : p.410-422 Langues : Anglais (eng) Mots-clés : autism spectrum disorders coactivation-based parcellation functional characterization middle temporal gyrus resting-state functional connectivity Index. décimale : PER Périodiques Résumé : As one of the key regions in the "social brain" network, the middle temporal gyrus (MTG) has been widely reported to be associated with autism spectrum disorder (ASD), but there have been contradictory results in terms of whether it shows hyperconnectivity or hypoconnectivity. Delineating roles of MTG at the subregional level may eliminate the observed inconsistencies and provide a new avenue to reveal the neurophysiologic mechanism of ASD. Thus, we first performed connectivity-based parcellation using the BrainMap database to identify fine-grained functional topography of the MTG. Then, the MTG subregions were used to investigate differences in the functional connectivity in children and adults with ASD using two data sets from Autism Brain Imaging Data Exchange database. Four distinct subregions in the human left and right MTG were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with ASD than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. Together, these results suggest a potential objective way to explore sub-regional differences associated with such disorders. Autism Res 2020, 13: 410-422. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Four distinct subregions in the human left and right middle temporal gyrus (MTG) were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with autism spectrum disorder (ASD) than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. En ligne : http://dx.doi.org/10.1002/aur.2239 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=421
in Autism Research > 13-3 (March 2020) . - p.410-422[article] Specific Functional Connectivity Patterns of Middle Temporal Gyrus Subregions in Children and Adults with Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Jinping XU, Auteur ; Chao WANG, Auteur ; Ziyun XU, Auteur ; Tian LI, Auteur ; Fangfang CHEN, Auteur ; Kai CHEN, Auteur ; Jingjing GAO, Auteur ; Jiaojian WANG, Auteur ; Qingmao HU, Auteur . - p.410-422.
Langues : Anglais (eng)
in Autism Research > 13-3 (March 2020) . - p.410-422
Mots-clés : autism spectrum disorders coactivation-based parcellation functional characterization middle temporal gyrus resting-state functional connectivity Index. décimale : PER Périodiques Résumé : As one of the key regions in the "social brain" network, the middle temporal gyrus (MTG) has been widely reported to be associated with autism spectrum disorder (ASD), but there have been contradictory results in terms of whether it shows hyperconnectivity or hypoconnectivity. Delineating roles of MTG at the subregional level may eliminate the observed inconsistencies and provide a new avenue to reveal the neurophysiologic mechanism of ASD. Thus, we first performed connectivity-based parcellation using the BrainMap database to identify fine-grained functional topography of the MTG. Then, the MTG subregions were used to investigate differences in the functional connectivity in children and adults with ASD using two data sets from Autism Brain Imaging Data Exchange database. Four distinct subregions in the human left and right MTG were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with ASD than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. Together, these results suggest a potential objective way to explore sub-regional differences associated with such disorders. Autism Res 2020, 13: 410-422. (c) 2019 International Society for Autism Research, Wiley Periodicals, Inc. LAY SUMMARY: Four distinct subregions in the human left and right middle temporal gyrus (MTG) were identified, including the anterior MTG (aMTG), middle-anterior MTG (maMTG), middle-posterior MTG, and posterior MTG (pMTG). The bilateral pMTG was more vulnerable in both children and adults with autism spectrum disorder (ASD) than in the typically developing (TD) group, mainly showing hypoconnectivity with different brain regions. In addition, the bilateral aMTG and right maMTG also showed altered functional connectivity in adults with ASD compared to the TD group. Moreover, all these altered MTG subregions were mainly associated with social cognition and language, as revealed by functional characterization. Further correlation analyses also showed trends of association between altered connectivity of the left aMTG and the Autism Diagnostic Observation Schedule scores in adults with ASD. En ligne : http://dx.doi.org/10.1002/aur.2239 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=421