Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits.
Aberrant Time-Varying Cross-Network Interactions in Children With Attention-Deficit/Hyperactivity Disorder and the Relation to Attention Deficits.
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DOI：
10.1016/j.bpsc.2017.10.005
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发表时间：
2018-03
期刊：
影响因子：
--
通讯作者：
Menon V
中科院分区：
文献类型：
--
作者：
Cai W;Chen T;Szegletes L;Supekar K;Menon V
注意力缺陷/多动障碍(ADHD)被认为源于大规模认知控制网络的异常。然而，涉及这些控制网络的异常脑回路动力学的确切性质还知之甚少。运用基于显著度的认知控制三重网络模型，我们检验了ADHD儿童显著(SN)、中央执行(CEN)和默认模式(DMN)网络之间的动态跨网络交互作用存在失调的假设，并探讨了这些失调是如何导致注意力不集中的。在病例对照设计中，我们使用了来自两个队列(主队列=80个；复制队列=60个)的140名ADHD儿童和典型发育中(TD)儿童的fMRI数据，分别检查了每个队列中时间平均和动态时变的跨网络交互作用。与TD儿童相比，ADHD儿童以SN为中心的跨网络互动的时间平均测量显着降低，并且与注意力不集中症状的严重程度相关。ADHD儿童表现出更多动态的跨网络互动模式，包括不那么持久的大脑状态，显著缩短的大脑状态的平均寿命，以及间歇性较弱的跨网络互动。重要的是，跨网络互动的动态时变测量与注意力不集中症状的相关性比功能连通性的时间平均测量更强。至关重要的是，我们在ADHD和TD儿童的两个独立队列中复制了这些发现。SNN与CEN和DMN的时变接触是儿童ADHD症状的强大和临床相关的神经生物学特征。三重网络神经认知模型为表征儿童ADHD和注意力不集中提供了一种新颖的、可复制的和简约的动力系统神经科学框架。
Attention-Deficit/Hyperactivity Disorder (ADHD) is thought to stem from aberrancies in large-scale cognitive control networks. However, the exact nature of aberrant brain circuit dynamics involving these control networks is poorly understood. Using a saliency-based triple-network model of cognitive control, we test the hypothesis that dynamic cross-network interactions among the salience (SN), central executive (CEN), and default mode (DMN) networks are dysregulated in children with ADHD, and investigate how these dysregulations contribute to inattention. Using fMRI data from 140 children with ADHD and typically developing (TD) children from two cohorts (Primary cohort = 80; Replication Cohort = 60) in a case-control design, we examined both time-averaged and dynamic time-varying cross-network interactions in each cohort separately. Time-averaged measures of SN-centered cross-network interactions were significantly lower in children with ADHD compared to TD children and were correlated with severity of inattention symptoms. Children with ADHD displayed more variable dynamic cross-network-interaction patterns, including less persistent brain states, significantly shorter mean lifetimes of brain states, and intermittently weaker cross-network interactions. Importantly, dynamic time-varying measures of cross-network interactions were more strongly correlated with inattention symptoms than time-averaged measures of functional connectivity. Crucially, we replicated these findings in the two independent cohorts of children with ADHD and TD children Aberrancies in time-varying engagement of the SN with the CEN and DMN are a robust and clinically-relevant neurobiological signature of childhood ADHD symptoms. The triple-network neurocognitive model provides a novel, replicable and parsimonious dynamical systems neuroscience framework for characterizing childhood ADHD and inattention.
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影响因子：
10.6
作者：
Fair, Damien A.;Posner, Jonathan;Nagel, Bonnie J.;Bathula, Deepti;Dias, Taciana G. Costa;Mills, Kathryn L.;Blythe, Michael S.;Giwa, Aishat;Schmitt, Colleen F.;Nigg, Joel T.
通讯作者：
Nigg, Joel T.
影响因子：
4.7
作者：
Dias, Taciana G. Costa;Iyer, Swathi P.;Carpenter, Samuel D.;Cary, Robert P.;Wilson, Vanessa B.;Mitchell, Suzanne H.;Nigg, Joel T.;Fair, Damien A.
通讯作者：
Fair, Damien A.
DOI：
10.1111/ejn.12764
发表时间：
2015-01
期刊：
The European journal of neuroscience
影响因子：
--
作者：
Chen T;Michels L;Supekar K;Kochalka J;Ryali S;Menon V
通讯作者：
Menon V
DOI：
10.1111/j.1469-7610.2006.01671.x
发表时间：
2006-10-01
影响因子：
7.6
作者：
Dickstein, Steven G.;Bannon, Katie;Milham, Michael P.
通讯作者：
Milham, Michael P.
影响因子：
5.3
作者：
Cai, Weidong;Ryali, Srikanth;Menon, Vinod
通讯作者：
Menon, Vinod