Auditory language comprehension among children and adolescents with autism spectrum disorder: An ALE meta-analysis of fMRI studies / Zihui HUA in Autism Research, 17-3 (March 2024)  

Public ISBD [article]  inAutism Research > 17-3 (March 2024) . - p.482-496 Titre : Auditory language comprehension among children and adolescents with autism spectrum disorder: An ALE meta-analysis of fMRI studies Type de document : Texte imprimé et/ou numérique Auteurs : Zihui HUA, Auteur ; Jun HU, Auteur ; Huanke ZENG, Auteur ; Jiahui LI, Auteur ; Yibo CAO, Auteur ; Yiqun GAN, Auteur Article en page(s) : p.482-496 Langues : Anglais (eng) Index. décimale : PER Périodiques Résumé : Abstract Difficulties in auditory language comprehension are common among children and adolescents with autism spectrum disorder. However, findings regarding the underlying neural mechanisms remain mixed, and few studies have systematically explored the overall patterns of these findings. Therefore, this study aims to systematically review and meta-analyze the functional magnetic resonance imaging evidence of neural activation patterns while engaging in auditory language comprehension tasks among children and adolescents with autism. Using activation likelihood estimation, we conducted a series of meta-analyses to investigate neural activation patterns during auditory language comprehension tasks compared to baseline conditions in autism and non-autism groups and compared the activation patterns of the groups, respectively. Eight studies were included in the within-group analyses, and seven were included in the between-group analysis. The within-group analyses revealed that the bilateral superior temporal gyrus was activated during auditory language comprehension tasks in both groups, whereas the left superior frontal gyrus and dorsal medial prefrontal cortex were activated only in the non-autism group. Furthermore, the between-group analysis showed that children and adolescents with autism, compared to those without autism, showed reduced activation in the right superior temporal gyrus, left middle temporal gyrus, and insula, whereas the autism group did not show increased activation in any of the regions relative to the non-autism group. Overall, these findings contribute to our understanding of the potential neural mechanisms underlying difficulties in auditory language comprehension in children and adolescents with autism and provide practical implications for early screening and language-related interventions for children and adolescents with autism. En ligne : https://doi.org/10.1002/aur.3055 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=525 [article] Auditory language comprehension among children and adolescents with autism spectrum disorder: An ALE meta-analysis of fMRI studies [Texte imprimé et/ou numérique] / Zihui HUA, Auteur ; Jun HU, Auteur ; Huanke ZENG, Auteur ; Jiahui LI, Auteur ; Yibo CAO, Auteur ; Yiqun GAN, Auteur . - p.482-496. Langues : Anglais (eng) in Autism Research > 17-3 (March 2024) . - p.482-496 Index. décimale : PER Périodiques Résumé : Abstract Difficulties in auditory language comprehension are common among children and adolescents with autism spectrum disorder. However, findings regarding the underlying neural mechanisms remain mixed, and few studies have systematically explored the overall patterns of these findings. Therefore, this study aims to systematically review and meta-analyze the functional magnetic resonance imaging evidence of neural activation patterns while engaging in auditory language comprehension tasks among children and adolescents with autism. Using activation likelihood estimation, we conducted a series of meta-analyses to investigate neural activation patterns during auditory language comprehension tasks compared to baseline conditions in autism and non-autism groups and compared the activation patterns of the groups, respectively. Eight studies were included in the within-group analyses, and seven were included in the between-group analysis. The within-group analyses revealed that the bilateral superior temporal gyrus was activated during auditory language comprehension tasks in both groups, whereas the left superior frontal gyrus and dorsal medial prefrontal cortex were activated only in the non-autism group. Furthermore, the between-group analysis showed that children and adolescents with autism, compared to those without autism, showed reduced activation in the right superior temporal gyrus, left middle temporal gyrus, and insula, whereas the autism group did not show increased activation in any of the regions relative to the non-autism group. Overall, these findings contribute to our understanding of the potential neural mechanisms underlying difficulties in auditory language comprehension in children and adolescents with autism and provide practical implications for early screening and language-related interventions for children and adolescents with autism. En ligne : https://doi.org/10.1002/aur.3055 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=525

Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning / Guomei XU in Autism Research, 17-10 (October 2024)  

Public ISBD [article]  inAutism Research > 17-10 (October 2024) . - p.1962-1973 Titre : Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning Type de document : Texte imprimé et/ou numérique Auteurs : Guomei XU, Auteur ; Guohong GENG, Auteur ; Ankang WANG, Auteur ; Zhangyong LI, Auteur ; Zhichao LIU, Auteur ; Yanping LIU, Auteur ; Jun HU, Auteur ; Wei WANG, Auteur ; Xinwei LI, Auteur Article en page(s) : p.1962-1973 Langues : Anglais (eng) Mots-clés : autism spectrum disorders  graph theory  gray matter network  heterogeneity  semi-supervised machine learning Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case?control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity. En ligne : https://doi.org/10.1002/aur.3183 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=536 [article] Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning [Texte imprimé et/ou numérique] / Guomei XU, Auteur ; Guohong GENG, Auteur ; Ankang WANG, Auteur ; Zhangyong LI, Auteur ; Zhichao LIU, Auteur ; Yanping LIU, Auteur ; Jun HU, Auteur ; Wei WANG, Auteur ; Xinwei LI, Auteur . - p.1962-1973. Langues : Anglais (eng) in Autism Research > 17-10 (October 2024) . - p.1962-1973 Mots-clés : autism spectrum disorders  graph theory  gray matter network  heterogeneity  semi-supervised machine learning Index. décimale : PER Périodiques Résumé : Abstract Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter brain networks and provide new insights from a graph theory perspective. In this study, we extracted and normalized single-subject gray matter networks and calculated each network's topological properties. The heterogeneity through discriminative analysis (HYDRA) method was utilized to subtype all patients based on network properties. Next, we explored the differences among ASD subtypes in terms of network properties and clinical measures. Our investigation identified three distinct ASD subtypes. In the case?control study, these subtypes exhibited significant differences, particularly in the precentral gyrus, lingual gyrus, and middle frontal gyrus. In the case analysis, significant differences in global and nodal properties were observed between any two subtypes. Clinically, subtype 1 showed lower VIQ and PIQ compared to subtype 3, but exhibited higher scores in ADOS-Communication and ADOS-Total compared to subtype 2. The results highlight the distinct brain network properties and behaviors among different subtypes of male patients with ASD, providing valuable insights into the neural mechanisms underlying ASD heterogeneity. En ligne : https://doi.org/10.1002/aur.3183 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=536

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