Atypical effective connectivity of thalamo-cortical circuits in autism spectrum disorder / Heng CHEN in Autism Research, 9-11 (November 2016)  

Public ISBD [article]  inAutism Research > 9-11 (November 2016) . - p.1183-1190 Titre : Atypical effective connectivity of thalamo-cortical circuits in autism spectrum disorder Type de document : Texte imprimé et/ou numérique Auteurs : Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Youxue ZHANG, Auteur ; Xujun DUAN, Auteur ; Huafu CHEN, Auteur Article en page(s) : p.1183-1190 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  thalamus  brain development  granger causality analysis Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopment disorder characterized by atypical connectivity within and across multiple brain systems. We aimed to explore information transmission from the sensory periphery to information processing centers of the brain across thalamo-cortical circuits in ASD. A large multicenter dataset from the autism brain imaging data exchange was utilized. A thalamus template derived from the Automatic Anatomic Labeling atlas was subdivided into six subregions corresponding to six cortical regions using a “winner-takes-all” strategy. Granger causality analysis (GCA) was then applied to calculate effective connectivity from subregions of the thalamus to the corresponding cortical regions. Results demonstrate reduced effective connectivity from the thalamus to left prefrontal cortex (P?=?0.023), right posterior parietal cortex (P?=?0.03), and bilateral temporal cortex (left: P?=?0.014; right: P?=?0.015) in ASD compared with healthy control (HC) participants. The GCA values of the thalamus-bilateral temporal cortex connections were significantly negatively correlated with communication scores as assessed by the autism diagnostic observation schedule in the ASD group (left: P?=?0.037; right: P?=?0.007). Age-related analyses showed that the strengths of the thalamus-bilateral temporal cortex connections were significantly positively correlated with age in the HC group (left: P?=?0.013; right: P?=?0.016), but not in the ASD group (left: P?=?0.506; right: P?=?0.219). These results demonstrate impaired thalamo-cortical information transmission in ASD and suggest that atypical development of thalamus-temporal cortex connections may relate to communication deficits in the disorder. En ligne : http://dx.doi.org/10.1002/aur.1614 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=297 [article] Atypical effective connectivity of thalamo-cortical circuits in autism spectrum disorder [Texte imprimé et/ou numérique] / Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Youxue ZHANG, Auteur ; Xujun DUAN, Auteur ; Huafu CHEN, Auteur . - p.1183-1190. Langues : Anglais (eng) in Autism Research > 9-11 (November 2016) . - p.1183-1190 Mots-clés : autism spectrum disorder  thalamus  brain development  granger causality analysis Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a neurodevelopment disorder characterized by atypical connectivity within and across multiple brain systems. We aimed to explore information transmission from the sensory periphery to information processing centers of the brain across thalamo-cortical circuits in ASD. A large multicenter dataset from the autism brain imaging data exchange was utilized. A thalamus template derived from the Automatic Anatomic Labeling atlas was subdivided into six subregions corresponding to six cortical regions using a “winner-takes-all” strategy. Granger causality analysis (GCA) was then applied to calculate effective connectivity from subregions of the thalamus to the corresponding cortical regions. Results demonstrate reduced effective connectivity from the thalamus to left prefrontal cortex (P?=?0.023), right posterior parietal cortex (P?=?0.03), and bilateral temporal cortex (left: P?=?0.014; right: P?=?0.015) in ASD compared with healthy control (HC) participants. The GCA values of the thalamus-bilateral temporal cortex connections were significantly negatively correlated with communication scores as assessed by the autism diagnostic observation schedule in the ASD group (left: P?=?0.037; right: P?=?0.007). Age-related analyses showed that the strengths of the thalamus-bilateral temporal cortex connections were significantly positively correlated with age in the HC group (left: P?=?0.013; right: P?=?0.016), but not in the ASD group (left: P?=?0.506; right: P?=?0.219). These results demonstrate impaired thalamo-cortical information transmission in ASD and suggest that atypical development of thalamus-temporal cortex connections may relate to communication deficits in the disorder. En ligne : http://dx.doi.org/10.1002/aur.1614 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=297

Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder / Heng CHEN in Autism Research, 14-3 (March 2021)  

Public ISBD [article]  inAutism Research > 14-3 (March 2021) . - p.464-472 Titre : Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder Type de document : Texte imprimé et/ou numérique Auteurs : Heng CHEN, Auteur ; Jinjin LONG, Auteur ; Shanshan YANG, Auteur ; Bifang HE, Auteur Article en page(s) : p.464-472 Langues : Anglais (eng) Mots-clés : autism spectrum disorder  functional covariance connectivity  resting-state fMRI  white matter function Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD. En ligne : http://dx.doi.org/10.1002/aur.2435 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443 [article] Atypical Functional Covariance Connectivity Between Gray and White Matter in Children With Autism Spectrum Disorder [Texte imprimé et/ou numérique] / Heng CHEN, Auteur ; Jinjin LONG, Auteur ; Shanshan YANG, Auteur ; Bifang HE, Auteur . - p.464-472. Langues : Anglais (eng) in Autism Research > 14-3 (March 2021) . - p.464-472 Mots-clés : autism spectrum disorder  functional covariance connectivity  resting-state fMRI  white matter function Index. décimale : PER Périodiques Résumé : Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder with atypical gray matter (GM) and white matter (WM) functional developmental course. However, the functional co-developmental pattern between GM and WM in ASD is unclear. Here, we utilized a functional covariance connectivity method to explore the concordance pattern between GM and WM function in individuals with ASD. A multi-center resting-state fMRI dataset composed of 105 male children with ASD and 102 well-matched healthy controls (HCs) from six sites of the ABIDE dataset was utilized. GM and WM ALFF maps were calculated for each subject. Voxel by voxel functional covariance connectivity of the ALFF values across subjects was calculated between GM and WM for children with ASD and HCs. A Z-test combining FDR multi-comparison correction was then employed to determine whether the functional covariance is significantly different between the two groups. A "bundling" strategy was utilized to ensure that the GM/WM clusters showing atypical functional covariance were larger than 5 voxels. Finally, canonical correlation analysis was conducted to explore whether the atypical GM/WM functional covariance is related to ASD symptoms. Results showed atypical functional covariance connections between specific GM and WM regions, whereas the ALFF values of these regions indicated no significant difference between the two groups. Canonical correlation analysis revealed a significant relationship between the atypical functional covariance and stereotyped behaviors of ASD. The results indicated an altered functional co-developmental pattern between WM and GM in ASD. LAY SUMMARY: White matter (WM) and gray matter (GM) are two major human brain organs supporting brain function. WM and GM functions show a specific co-developmental pattern in typical developed individuals. This study showed that this GM/WM co-developmental pattern was altered in children with ASD, while this altered GM/WM co-developmental pattern was related to stereotyped behaviors. These findings may help understand the GM/WM functional development of ASD. En ligne : http://dx.doi.org/10.1002/aur.2435 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=443

Shared atypical default mode and salience network functional connectivity between autism and schizophrenia / Heng CHEN in Autism Research, 10-11 (November 2017)  

Public ISBD [article]  inAutism Research > 10-11 (November 2017) . - p.1776-1786 Titre : Shared atypical default mode and salience network functional connectivity between autism and schizophrenia Type de document : Texte imprimé et/ou numérique Auteurs : Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Xujun DUAN, Auteur ; Junjie ZHENG, Auteur ; Zhiliang LONG, Auteur ; Youxue ZHANG, Auteur ; Xiaonan GUO, Auteur ; Yan ZHANG, Auteur ; Jingping ZHAO, Auteur ; Huafu CHEN, Auteur Article en page(s) : p.1776-1786 Langues : Anglais (eng) Mots-clés : schizophrenia  autism spectrum disorder  functional connectivity  multivariate pattern analysis  default mode network  salience network Index. décimale : PER Périodiques Résumé : Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6?±?1.8 years old) and 31 healthy controls (15.4?±?1.6 years old). Data from 22 participants with ASD (13.1?±?3.1 years old) and 21 healthy controls (12.9?±?2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy?=?83%; ASD dataset: accuracy?=?80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p?=?0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776–1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Lay summary Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1002/aur.1834 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=322 [article] Shared atypical default mode and salience network functional connectivity between autism and schizophrenia [Texte imprimé et/ou numérique] / Heng CHEN, Auteur ; Lucina Q. UDDIN, Auteur ; Xujun DUAN, Auteur ; Junjie ZHENG, Auteur ; Zhiliang LONG, Auteur ; Youxue ZHANG, Auteur ; Xiaonan GUO, Auteur ; Yan ZHANG, Auteur ; Jingping ZHAO, Auteur ; Huafu CHEN, Auteur . - p.1776-1786. Langues : Anglais (eng) in Autism Research > 10-11 (November 2017) . - p.1776-1786 Mots-clés : schizophrenia  autism spectrum disorder  functional connectivity  multivariate pattern analysis  default mode network  salience network Index. décimale : PER Périodiques Résumé : Schizophrenia and autism spectrum disorder (ASD) are two prevalent neurodevelopmental disorders sharing some similar genetic basis and clinical features. The extent to which they share common neural substrates remains unclear. Resting-state fMRI data were collected from 35 drug-naïve adolescent participants with first-episode schizophrenia (15.6?±?1.8 years old) and 31 healthy controls (15.4?±?1.6 years old). Data from 22 participants with ASD (13.1?±?3.1 years old) and 21 healthy controls (12.9?±?2.9 years old) were downloaded from the Autism Brain Imaging Data Exchange. Resting-state functional networks were constructed using predefined regions of interest. Multivariate pattern analysis combined with multi-task regression feature selection methods were conducted in two datasets separately. Classification between individuals with disorders and controls was achieved with high accuracy (schizophrenia dataset: accuracy?=?83%; ASD dataset: accuracy?=?80%). Shared atypical brain connections contributing to classification were mostly present in the default mode network (DMN) and salience network (SN). These functional connections were further related to severity of social deficits in ASD (p?=?0.002). Distinct atypical connections were also more related to the DMN and SN, but showed different atypical connectivity patterns between the two disorders. These results suggest some common neural mechanisms contributing to schizophrenia and ASD, and may aid in understanding the pathology of these two neurodevelopmental disorders. Autism Res 2017, 10: 1776–1786. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. Lay summary Autism spectrum disorder (ASD) and schizophrenia are two common neurodevelopmental disorders which share several genetic and behavioral features. The present study identified common neural mechanisms contributing to ASD and schizophrenia using resting-state functional MRI data. The results may help to understand the pathology of these two neurodevelopmental disorders. En ligne : http://dx.doi.org/10.1002/aur.1834 Permalink : https://www.cra-rhone-alpes.org/cid/opac_css/index.php?lvl=notice_display&id=322

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