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Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders

INTRODUCTION: Understanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effe...

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Autores principales: Wei, Lei, Zhang, Yao, Zhai, Wensheng, Wang, Huaning, Zhang, Junchao, Jin, Haojie, Feng, Jianfei, Qin, Qin, Xu, Hao, Li, Baojuan, Liu, Jian
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745118/
https://www.ncbi.nlm.nih.gov/pubmed/36523439
http://dx.doi.org/10.3389/fnins.2022.987248
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author Wei, Lei
Zhang, Yao
Zhai, Wensheng
Wang, Huaning
Zhang, Junchao
Jin, Haojie
Feng, Jianfei
Qin, Qin
Xu, Hao
Li, Baojuan
Liu, Jian
author_facet Wei, Lei
Zhang, Yao
Zhai, Wensheng
Wang, Huaning
Zhang, Junchao
Jin, Haojie
Feng, Jianfei
Qin, Qin
Xu, Hao
Li, Baojuan
Liu, Jian
author_sort Wei, Lei
collection PubMed
description INTRODUCTION: Understanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effective connectivity which measures the causal interactions of these networks is also impaired in these patients remains unclear. OBJECTS: The main purpose of this study was to investigate the effective connectivity of large-scale brain networks in patients with ASD during resting state. MATERIALS AND METHODS: The subjects were 42 autistic children and 127 age-matched normal children from the ABIDE II dataset. We investigated effective connectivity of 7 large-scale brain networks including visual network (VN), default mode network (DMN), cerebellum, sensorimotor network (SMN), auditory network (AN), salience network (SN), frontoparietal network (FPN), with spectral dynamic causality model (spDCM). Parametric empirical Bayesian (PEB) was used to perform second-level group analysis and furnished group commonalities and differences in effective connectivity. Furthermore, we analyzed the correlation between the strength of effective connectivity and patients’ clinical characteristics. RESULTS: For both groups, SMN acted like a hub network which demonstrated dense effective connectivity with other large-scale brain network. We also observed significant causal interactions within the “triple networks” system, including DMN, SN and FPN. Compared with healthy controls, children with ASD showed decreased effective connectivity among some large-scale brain networks. These brain networks included VN, DMN, cerebellum, SMN, and FPN. In addition, we also found significant negative correlation between the strength of the effective connectivity from right angular gyrus (ANG_R) of DMN to left precentral gyrus (PreCG_L) of SMN and ADOS-G or ADOS-2 module 4 stereotyped behaviors and restricted interest total (ADOS_G_STEREO_BEHAV) scores. CONCLUSION: Our research provides new evidence for the pathogenesis of children with ASD from the perspective of effective connections within and between large-scale brain networks. The attenuated effective connectivity of brain networks may be a clinical neurobiological feature of ASD. Changes in effective connectivity of brain network in children with ASD may provide useful information for the diagnosis and treatment of the disease.
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spelling pubmed-97451182022-12-14 Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders Wei, Lei Zhang, Yao Zhai, Wensheng Wang, Huaning Zhang, Junchao Jin, Haojie Feng, Jianfei Qin, Qin Xu, Hao Li, Baojuan Liu, Jian Front Neurosci Neuroscience INTRODUCTION: Understanding the neurological basis of autism spectrum disorder (ASD) is important for the diagnosis and treatment of this mental disorder. Emerging evidence has suggested aberrant functional connectivity of large-scale brain networks in individuals with ASD. However, whether the effective connectivity which measures the causal interactions of these networks is also impaired in these patients remains unclear. OBJECTS: The main purpose of this study was to investigate the effective connectivity of large-scale brain networks in patients with ASD during resting state. MATERIALS AND METHODS: The subjects were 42 autistic children and 127 age-matched normal children from the ABIDE II dataset. We investigated effective connectivity of 7 large-scale brain networks including visual network (VN), default mode network (DMN), cerebellum, sensorimotor network (SMN), auditory network (AN), salience network (SN), frontoparietal network (FPN), with spectral dynamic causality model (spDCM). Parametric empirical Bayesian (PEB) was used to perform second-level group analysis and furnished group commonalities and differences in effective connectivity. Furthermore, we analyzed the correlation between the strength of effective connectivity and patients’ clinical characteristics. RESULTS: For both groups, SMN acted like a hub network which demonstrated dense effective connectivity with other large-scale brain network. We also observed significant causal interactions within the “triple networks” system, including DMN, SN and FPN. Compared with healthy controls, children with ASD showed decreased effective connectivity among some large-scale brain networks. These brain networks included VN, DMN, cerebellum, SMN, and FPN. In addition, we also found significant negative correlation between the strength of the effective connectivity from right angular gyrus (ANG_R) of DMN to left precentral gyrus (PreCG_L) of SMN and ADOS-G or ADOS-2 module 4 stereotyped behaviors and restricted interest total (ADOS_G_STEREO_BEHAV) scores. CONCLUSION: Our research provides new evidence for the pathogenesis of children with ASD from the perspective of effective connections within and between large-scale brain networks. The attenuated effective connectivity of brain networks may be a clinical neurobiological feature of ASD. Changes in effective connectivity of brain network in children with ASD may provide useful information for the diagnosis and treatment of the disease. Frontiers Media S.A. 2022-11-29 /pmc/articles/PMC9745118/ /pubmed/36523439 http://dx.doi.org/10.3389/fnins.2022.987248 Text en Copyright © 2022 Wei, Zhang, Zhai, Wang, Zhang, Jin, Feng, Qin, Xu, Li and Liu. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Wei, Lei
Zhang, Yao
Zhai, Wensheng
Wang, Huaning
Zhang, Junchao
Jin, Haojie
Feng, Jianfei
Qin, Qin
Xu, Hao
Li, Baojuan
Liu, Jian
Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title_full Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title_fullStr Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title_full_unstemmed Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title_short Attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
title_sort attenuated effective connectivity of large-scale brain networks in children with autism spectrum disorders
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9745118/
https://www.ncbi.nlm.nih.gov/pubmed/36523439
http://dx.doi.org/10.3389/fnins.2022.987248
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