Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder

Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and be...

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Main Authors: Qian, Xing, Castellanos, Francisco Xavier, Uddin, Lucina Q., Loo, Beatrice Rui Yi, Liu, Siwei, Koh, Hui Li, Fung, Daniel, Guan, Cuntai, Lee, Tih-Shih, Lim, Choon Guan, Zhou, Juan, Poh, Wendy Xue Wei
Other Authors: School of Computer Science and Engineering
Format: Article
Language:English
Published: 2019
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Online Access:https://hdl.handle.net/10356/83148
http://hdl.handle.net/10220/49110
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-831482020-03-07T11:48:55Z Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder Qian, Xing Castellanos, Francisco Xavier Uddin, Lucina Q. Loo, Beatrice Rui Yi Liu, Siwei Koh, Hui Li Fung, Daniel Guan, Cuntai Lee, Tih-Shih Lim, Choon Guan Zhou, Juan Poh, Wendy Xue Wei School of Computer Science and Engineering Functional Connectivity Engineering::Computer science and engineering Attention-deficit/Hyperactivity Disorder Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and between-network functional connectivity (FC) changes in children with ADHD combined (ADHD-C) or inattentive (ADHD-I) subtypes and their associations with ADHD symptoms. We studied the task-free functional magnetic resonance imaging (fMRI) data of 58 boys with ADHD and 28 demographically matched healthy controls. We measured within- and between-network connectivity of both low-level (sensorimotor) and high-level (cognitive) large-scale intrinsic connectivity networks and network modularity. We found that children with ADHD-C but not those with ADHD-I exhibited hyper-connectivity within the anterior default mode network (DMN) compared with controls. Additionally, children with ADHD-C had higher inter-network FC between the left executive control (ECN) and the salience (SN) networks, between subcortical and visual networks, and between the DMN and left auditory networks than controls, while children with ADHD-I did not show differences compared with controls. Similarly, children with ADHD-C but not ADHD-I showed lower network modularity compared with controls. Importantly, these observed abnormal inter-network connectivity and network modularity metrics were associated with Child Behavioral Checklist (CBCL) attention-deficit/hyperactivity problems and internalizing problems in children with ADHD. This study revealed relatively greater loss of brain functional network segregation in childhood ADHD combined subtype compared to the inattentive subtype, suggesting differential large-scale functional brain network topology phenotype underlying childhood ADHD heterogeneity. NMRC (Natl Medical Research Council, S’pore) MOH (Min. of Health, S’pore) Published version 2019-07-03T06:18:35Z 2019-12-06T15:12:45Z 2019-07-03T06:18:35Z 2019-12-06T15:12:45Z 2018 Journal Article Qian, X., Castellanos, F. X., Uddin, L. Q., Loo, B. R. Y., Liu, S., Koh, H. L., . . . Zhou, J. (2019). Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder. NeuroImage: Clinical, 21, 101600-. doi:10.1016/j.nicl.2018.11.010 https://hdl.handle.net/10356/83148 http://hdl.handle.net/10220/49110 10.1016/j.nicl.2018.11.010 en NeuroImage: Clinical © 2018 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/BY-NC-ND/4.0/). 8 p. application/pdf
institution Nanyang Technological University
building NTU Library
country Singapore
collection DR-NTU
language English
topic Functional Connectivity
Engineering::Computer science and engineering
Attention-deficit/Hyperactivity Disorder
spellingShingle Functional Connectivity
Engineering::Computer science and engineering
Attention-deficit/Hyperactivity Disorder
Qian, Xing
Castellanos, Francisco Xavier
Uddin, Lucina Q.
Loo, Beatrice Rui Yi
Liu, Siwei
Koh, Hui Li
Fung, Daniel
Guan, Cuntai
Lee, Tih-Shih
Lim, Choon Guan
Zhou, Juan
Poh, Wendy Xue Wei
Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
description Accumulating evidence suggests brain network dysfunction in attention-deficit/hyperactivity disorder (ADHD). Whether large-scale brain network connectivity patterns reflect clinical heterogeneity in ADHD remains to be fully understood. This study aimed to characterize the differential within- and between-network functional connectivity (FC) changes in children with ADHD combined (ADHD-C) or inattentive (ADHD-I) subtypes and their associations with ADHD symptoms. We studied the task-free functional magnetic resonance imaging (fMRI) data of 58 boys with ADHD and 28 demographically matched healthy controls. We measured within- and between-network connectivity of both low-level (sensorimotor) and high-level (cognitive) large-scale intrinsic connectivity networks and network modularity. We found that children with ADHD-C but not those with ADHD-I exhibited hyper-connectivity within the anterior default mode network (DMN) compared with controls. Additionally, children with ADHD-C had higher inter-network FC between the left executive control (ECN) and the salience (SN) networks, between subcortical and visual networks, and between the DMN and left auditory networks than controls, while children with ADHD-I did not show differences compared with controls. Similarly, children with ADHD-C but not ADHD-I showed lower network modularity compared with controls. Importantly, these observed abnormal inter-network connectivity and network modularity metrics were associated with Child Behavioral Checklist (CBCL) attention-deficit/hyperactivity problems and internalizing problems in children with ADHD. This study revealed relatively greater loss of brain functional network segregation in childhood ADHD combined subtype compared to the inattentive subtype, suggesting differential large-scale functional brain network topology phenotype underlying childhood ADHD heterogeneity.
author2 School of Computer Science and Engineering
author_facet School of Computer Science and Engineering
Qian, Xing
Castellanos, Francisco Xavier
Uddin, Lucina Q.
Loo, Beatrice Rui Yi
Liu, Siwei
Koh, Hui Li
Fung, Daniel
Guan, Cuntai
Lee, Tih-Shih
Lim, Choon Guan
Zhou, Juan
Poh, Wendy Xue Wei
format Article
author Qian, Xing
Castellanos, Francisco Xavier
Uddin, Lucina Q.
Loo, Beatrice Rui Yi
Liu, Siwei
Koh, Hui Li
Fung, Daniel
Guan, Cuntai
Lee, Tih-Shih
Lim, Choon Guan
Zhou, Juan
Poh, Wendy Xue Wei
author_sort Qian, Xing
title Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
title_short Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
title_full Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
title_fullStr Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
title_full_unstemmed Large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
title_sort large-scale brain functional network topology disruptions underlie symptom heterogeneity in children with attention-deficit/hyperactivity disorder
publishDate 2019
url https://hdl.handle.net/10356/83148
http://hdl.handle.net/10220/49110
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