Annu Int Conf IEEE Eng Med Biol Soc. 2021 Nov;2021:4358-4361. doi: 10.1109/EMBC46164.2021.9630614.
Attention-deficit/hyperactivity disorder (ADHD) is a prevalent neurodevelopmental disorder in children, usually categorized as three predominant subtypes, persistent inattention (ADHD-I), hyperactivity-impulsivity (ADHD-HI) and a combination of both (ADHD-C). Identifying reliable features to distinguish different subtypes is significant for clinical individualized treatment. In this work, we conducted a two-stage electroencephalogram (EEG) microstate analysis on 54 healthy controls and 107 ADHD children, including 54 ADHD-Is and 53 ADHD-Cs, aiming to examine the dynamic temporal alterations in ADHDs compared to healthy controls (HCs), as well as different EEG signatures between ADHD subtypes. Results demonstrated that the dynamics of resting-state EEG microstates, particularly centering on salience (state C) and frontal-parietal network (state D), were significantly aberrant in ADHDs. Specifically, the occurrence and coverage of state C were decreased in ADHDs (p=0.002; p=0.0015), while the duration and contribution of state D were observably increased (p=0.0016; p=0.0001) compared to HCs. Moreover, the transition probability between state A and C was significantly decreased (p=9.85e-7; p=2.33e-7) in ADHDs, but otherwise increased between state B and D (p=1.02e-7; p=1.07e-6). By contrast, remarkable subtype differences were found primarily on the visual network (state B) between ADHD-Is and ADHD-Cs. Specifically, ADHD-Cs have higher occurrence and coverage of state B than ADHD-Is (p=9.35e-5; p=1.51e-8), suggesting these patients more impulsively aimed to open their eyes when asked to keep eyes closed during the data collection. In summary, this work carefully leveraged EEG temporal dynamics to investigate the aberrant microstate features in ADHDs and provided a new window to look into the subtle differences between ADHD subtypes, which may help to assist precision diagnosis in future.Clinical Relevance- This work established the use of EEG microstate features to investigate ADHD dysfunction and its subtypes, providing a new window for better diagnosis of ADHD.
注意缺陷多动障碍（ADHD）是一种常见的儿童神经发育障碍，通常分为三种主要亚型，即持续注意力不集中（ADHD-I）、多动冲动（ADHD-HI）和两者的混合（ADHD-C）。识别可靠的特征来区分不同的亚型对于临床个体化治疗具有重要意义。在这项工作中，我们对 54 名健康对照者和 107 名 ADHD 儿童进行了两阶段脑电图（EEG）微状态分析，包括 54 名 ADHD-Is 和 53 名 ADHD-Cs，旨在检查 ADHD 与健康对照者（HCs）相比的静息态 EEG 微状态的动态时间变化，以及 ADHD 亚型之间的不同 EEG 特征。结果表明，ADHD 患者的静息态 EEG 微状态动力学，特别是突显网络（状态 C）和额顶网络（状态 D），存在显著异常。具体来说，ADHD 患者状态 C 的出现和覆盖减少（p=0.002;p=0.0015），而状态 D 的持续时间和贡献明显增加（p=0.0016;p=0.0001）与 HCs 相比。此外，ADHD 患者状态 A 与 C 之间的转移概率显著降低（p=9.85e-7;p=2.33e-7），而状态 B 与 D 之间的转移概率则显著增加（p=1.02e-7;p=1.07e-6）。相比之下，ADHD-Is 和 ADHD-Cs 之间在视觉网络（状态 B）上发现了显著的亚型差异。具体来说，ADHD-Cs 的状态 B 出现和覆盖高于 ADHD-Is（p=9.35e-5;p=1.51e-8），这表明这些患者在被要求在数据采集期间保持闭眼时更冲动地试图睁开眼睛。总之，这项工作仔细利用 EEG 时间动态来研究 ADHD 中的异常微状态特征，并为研究 ADHD 亚型之间的细微差异提供了一个新的窗口，这可能有助于在未来辅助 ADHD 的精确诊断。
临床相关性-这项工作建立了使用 EEG 微状态特征来研究 ADHD 功能障碍及其亚型的方法，为更好地诊断 ADHD 提供了一个新的窗口。
