Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA.
Department of Psychology and Neuroscience, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA.
Neuroimage. 2021 Apr 1;229:117753. doi: 10.1016/j.neuroimage.2021.117753. Epub 2021 Jan 14.
Previous studies in children with attention-deficit/hyperactivity disorder (ADHD) have observed functional brain network disruption on a whole-brain level, as well as on a sub-network level, particularly as related to the default mode network, attention-related networks, and cognitive control-related networks. Given behavioral findings that children with ADHD have more difficulty sustaining attention and more extreme moment-to-moment fluctuations in behavior than typically developing (TD) children, recently developed methods to assess changes in connectivity over shorter time periods (i.e., "dynamic functional connectivity"), may provide unique insight into dysfunctional network organization in ADHD. Thus, we performed a dynamic functional connectivity (FC) analysis on resting state fMRI data from 38 children with ADHD and 79 TD children. We used Hidden semi-Markov models (HSMMs) to estimate six network states, as well as the most probable sequence of states for each participant. We quantified the dwell time, sojourn time, and transition probabilities across states. We found that children with ADHD spent less total time in, and switched more quickly out of, anticorrelated states involving the default mode network and task-relevant networks as compared to TD children. Moreover, children with ADHD spent more time in a hyperconnected state as compared to TD children. These results provide novel evidence that underlying dynamics may drive the differences in static FC patterns that have been observed in ADHD and imply that disrupted FC dynamics may be a mechanism underlying the behavioral symptoms and cognitive deficits commonly observed in children with ADHD.
先前针对注意力缺陷多动障碍(ADHD)儿童的研究观察到全脑水平和子网络水平的功能性脑网络破坏,特别是与默认模式网络、注意力相关网络和认知控制相关网络有关。鉴于 ADHD 儿童在维持注意力方面比正常发育(TD)儿童更困难,行为研究发现他们的行为在瞬间有更极端的波动,最近开发的评估较短时间内连接变化的方法(即“动态功能连接”),可能为 ADHD 中功能失调的网络组织提供独特的见解。因此,我们对 38 名 ADHD 儿童和 79 名 TD 儿童的静息态 fMRI 数据进行了动态功能连接(FC)分析。我们使用隐半马尔可夫模型(HSMM)来估计六个网络状态,以及每个参与者最可能的状态序列。我们量化了状态之间的停留时间、逗留时间和转移概率。我们发现,与 TD 儿童相比,ADHD 儿童在涉及默认模式网络和任务相关网络的负相关状态中停留的总时间更少,并且更快地切换出这些状态。此外,与 TD 儿童相比,ADHD 儿童在超连接状态中停留的时间更多。这些结果提供了新的证据,表明潜在的动态可能会导致 ADHD 中观察到的静态 FC 模式的差异,并暗示 FC 动态的破坏可能是 ADHD 儿童常见的行为症状和认知缺陷的机制。