注意缺陷多动障碍中与大脑状态相关的动态功能连接模式。
Brain state-dependent dynamic functional connectivity patterns in attention-deficit/hyperactivity disorder.
机构信息
Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 311121, China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou, 311121, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, 311121, China; College of Education, Hangzhou Normal University, Hangzhou, 311121, China; Department of Psychiatry, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, 310016, China.
Center for Cognition and Brain Disorders, The Affiliated Hospital of Hangzhou Normal University, Hangzhou, 311121, China; Institute of Psychological Science, Hangzhou Normal University, Hangzhou, 311121, China; Zhejiang Key Laboratory for Research in Assessment of Cognitive Impairments, Hangzhou, 311121, China; College of Education, Hangzhou Normal University, Hangzhou, 311121, China.
出版信息
J Psychiatr Res. 2021 Jun;138:569-575. doi: 10.1016/j.jpsychires.2021.05.010. Epub 2021 May 8.
Attention-deficit/hyperactivity disorder (ADHD) patients have presented aberrant static brain networks, however identifying ADHD patients based on dynamic information in brain networks is not fully clear. Data were obtained from 32 boys with ADHD and 52 sex- and age-matched typically developing controls; a sliding-window method was used to assess dynamic functional connectivity (dFC), and two reoccurring dFC states (the hot and cool states) were then identified using a k-means clustering method. The results showed that ADHD patients had significant changes in occurrence, transitions times and dFC strength of the cingulo-opercular network (CON) and sensorimotor network (SMN) in the cool state. The severity of ADHD symptoms showed significant correlations with the regional amplitude of dFC fluctuations in the ventral medial prefrontal cortex (vmPFC), anterior medial prefrontal cortex (amPFC) and precuneus. These findings could provide insights on the state-dependent dynamic changes in large-scale brain connectivity and network configurations in ADHD.
注意缺陷多动障碍（ADHD）患者的静息态脑网络存在异常，但基于脑网络中的动态信息来识别 ADHD 患者的情况尚不完全清楚。研究数据来自 32 名 ADHD 男孩和 52 名性别和年龄匹配的正常发育对照者；采用滑动窗口方法评估动态功能连接（dFC），然后使用 k-均值聚类方法识别出两种反复出现的 dFC 状态（热状态和冷状态）。结果表明，ADHD 患者在冷状态下扣带回-顶叶网络（CON）和感觉运动网络（SMN）的出现、转换时间和 dFC 强度均发生显著变化。ADHD 症状的严重程度与腹内侧前额叶皮质（vmPFC）、前内侧前额叶皮质（amPFC）和楔前叶 dFC 波动的区域幅度呈显著相关性。这些发现可以深入了解 ADHD 患者大脑连接和网络结构的状态相关动态变化。
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