Hu Zhenyan, Liu Lu, Wang Mengjing, Jia Gaoding, Li Haimei, Si Feifei, Dong Min, Qian Qiujin, Niu HaiJing
State Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing 100875, China.
Zhenyan Hu and Lu Liu contributed equally to this research.
Biomed Opt Express. 2021 Apr 29;12(5):3037-3049. doi: 10.1364/BOE.418921. eCollection 2021 May 1.
Brain signal variability (BSV) has shown to be powerful in characterizing human brain development and neuropsychiatric disorders. Multiscale entropy (MSE) is a novel method for quantifying the variability of brain signal, and helps elucidate complex dynamic pathological mechanisms in children with attention-deficit/hyperactivity disorder (ADHD). Here, multiple-channel resting-state functional near-infrared spectroscopy (fNIRS) imaging data were acquired from 42 children with ADHD and 41 healthy controls (HCs) and then BSV was calculated for each participant based on the MSE analysis. Compared with HCs, ADHD group exhibited reduced BSV in both high-order and primary brain functional networks, e.g., the default mode, frontoparietal, attention and visual networks. Intriguingly, the BSV aberrations negatively correlated with ADHD symptoms in the frontoparietal network and negatively correlated with reaction time variability in the frontoparietal, default mode, somatomotor and attention networks. This study demonstrates a wide alternation in the moment-to-moment variability of spontaneous brain signal in children with ADHD, and highlights the potential for using MSE metric as a disease biomarker.
脑信号变异性(BSV)已被证明在表征人类大脑发育和神经精神疾病方面具有强大作用。多尺度熵(MSE)是一种用于量化脑信号变异性的新方法,有助于阐明注意力缺陷多动障碍(ADHD)儿童复杂的动态病理机制。在此,从42名ADHD儿童和41名健康对照(HCs)中获取了多通道静息态功能近红外光谱(fNIRS)成像数据,然后基于MSE分析为每个参与者计算BSV。与HCs相比,ADHD组在高阶和初级脑功能网络中均表现出BSV降低,例如默认模式、额顶叶、注意力和视觉网络。有趣的是,BSV异常与额顶叶网络中的ADHD症状呈负相关,与额顶叶、默认模式、躯体运动和注意力网络中的反应时变异性呈负相关。本研究证明了ADHD儿童自发脑信号的即时变异性存在广泛改变,并强调了使用MSE指标作为疾病生物标志物的潜力。