注意缺陷多动障碍（Attention Deficit Hyperactivity Disorder, ADHD）是一种与脑神经的异常发育相关且具有复杂行为表现的疾病。同时，ADHD也是儿童期最常见的神经发育障碍。因此，对儿童时期ADHD的研究对理解异常脑功能发育至关重要。目前功能磁共振成像（Functional Magnetic Resonance Imaging, fMRI）、弥散张量成像（Diffusion Tensor Imaging，DTI）和脑电（Electroencephalogram，EEG）等神经影像技术已被广泛用于ADHD患者的研究中。然而ADHD儿童多动冲动的特点往往造成数据采集及后续数据分析的困难。功能近红外光谱成像技术（Functional Near-Infrared Spectroscopy, fNIRS）因其高度的头动容忍性、较低的身体限制和便携、耗能少价格低的优势，已经被广泛应用于认知神经科学领域的研究之中。因此，本研究将采用具备数据采集优势的fNIRS技术探究ADHD儿童脑功能异常。
静息态功能连接（Resting-State Functional Connectivity, RSFC）为我们探讨大脑认知功能内在工作机理提供了可靠的方法支撑。研究表明大脑神经疾病往往与静息态下大脑功能连接的异常相关。近年来，图论方法的出现为探讨异常功能连接提供了新的理论依据。但是目前并没有将fNIRS技术与功能连接和图论相结合探究ADHD异常脑功能连接网络的研究。此外，神经生理信号自身的特点是理解大脑功能异常的另一个途径，近年来，研究者利用fNIRS技术发现相位差和锁相能够反应早产婴儿的异常发育，表明这种信号指标可以反应大脑的神经血流耦合情况，而目前并未有人将这种方法应用于ADHD儿童的研究中。
为此，本研究采用fNIRS技术记录被试的大脑信号，分别探究ADHD儿童脑功能连接网络异常和ADHD脑信号异常。研究一中将通过功能连接和网络属性的计算比较了ADHD儿童和正常儿童（Healthy Control, HC）在功能连接和效率上的差异，结果表明ADHD儿童在功能连接和全局网络属性上都表现出显著的降低，而节点效率在视觉网络、背侧注意网络上增加，在躯体运动网络和默认网络上降低。最后，脑网络的异常改变与ADHD的症状分数存在相关；研究二中，利用希尔伯特变换计算氧合血红蛋白（Oxygenated Hemoglobin, HbO）和脱氧血红蛋白（Deoxygenated Hemoglobin, HbR）信号的相位差（hemoglobin Phase of oxygenation and deoxygenation, hPod）和锁相（phase-locking index of hPod, hPodL）,两组比较结果表明，ADHD儿童的相位差更远离于π（反向），有显著差异的区域集中在视觉网络，此外，ADHD具有更高的锁相，主要分布在额顶网络和腹侧注意网络。
研究一、二利用fNIRS技术分别从脑功能连接网络和脑信号两个角度探究了ADHD儿童脑功能异常，验证了fNIRS技术能够用于神经发育相关疾病的研究，结果表明大脑功能连接、网络属性，相位差和锁相能够反映大脑功能的异常为研究ADHD的病理机制提供依据，也为后续更加深入研究提供思路。

Attention Deficit Hyperactivity Disorder (ADHD) is a disorder associated with abnormal brain neural development and has complex behavioral manifestations In childhood, ADHD is the most common type of neurodevelopmental disorder. Therefore, the study of ADHD in childhood is essential for understanding abnormal brain function development. Neuroimaging techniques such as Functional Magnetic Resonance Imaging (fMRI), Diffusion Tensor Imaging (DTI) and Electroencephalogram (EEG) are now widely used in the study of ADHD patients. However, the characteristics of hyperactivity in children with ADHD often make it difficult for data collection and subsequent data analysis. In recent years, Functional Near-Infrared Spectroscopy (fNIRS) has been widely used in cognitive neuroscience research due to its high head-motion tolerance, low physical limitations and the advantages of portability, low energy consumption and low price. Therefore, in this study, the fNIRS technique, which has the advantages of data acquisition, was adopted to explore the abnormal brain function in ADHD children.
Resting-State Functional Connectivity (RSFC) provides a reliable way to support our exploration of the intrinsic working mechanisms of brain cognitive function. Studies have shown that neurological diseases of the brain are often associated with abnormalities in functional brain connectivity in the resting state. In recent years, the emergence of graph theory approaches has provided a new theoretical basis for exploring abnormal functional connectivity. However, there are currently no studies that combine fNIRS techniques with functional connectivity and graph theory to explore abnormal brain functional connectivity networks in ADHD. In addition, neurophysiological signals are another way of understanding abnormalities in brain function. And in recent years, researchers using fNIRS techniques have found that phase difference and phase lock can respond to abnormal development in preterm infants, suggesting that this signal indicators can respond to neurological blood flow coupling in the brain. It’s also an approach that has not yet been applied to studies of children with ADHD.
To this end, the present study used fNIRS technique to record the brain signals of the subjects to explore the abnormal brain functional connectivity network and the abnormal brain signals of ADHD children respectively. The differences in functional connectivity and efficiency between ADHD children and Healthy control (HC) were compared in Study I by calculating functional connectivity and network properties, and the results showed that ADHD children showed significant decreases in both functional connectivity and global network properties, while node efficiency increased in visual network, dorsal attention network, and decreased in somatomotor network and default mode network. Finally, abnormal changes in the brain network were correlated with the symptom scores in ADHD; in Study II, the hemoglobin phase of oxygenation and deoxygenation (hPod) and the phase-locking index of hPod (hPodL) of the signal were calculated by the Hilbert transform. And the results of the comparison between the two groups showed that the hPod in children with ADHD was further away from π (inverse), and the region with significant differences was concentrated in the visual network. In addition, ADHD had a higher hPodL in the frontoparietal network and ventral attention network.
Studies I and II used fNIRS technology to explore brain function abnormalities in children with ADHD from two perspectives: brain functional connectivity network and brain signals, respectively, and verified that fNIRS technology can be used in the study of neurodevelopmental-related diseases. The results show that brain functional connectivity, network properties, hPod and phase-locking index of hPod can reflect abnormalities in brain function. These findings provide a basis for studying the pathological mechanisms of ADHD, and also provide ideas for more in-depth research in ADHD.