Dynamic cortical connectivity alterations associated with Alzheimer's disease: An EEG and fNIRS integration study
Dynamic cortical connectivity alterations associated with Alzheimer's disease: An EEG and fNIRS integration study
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DOI：
10.1016/j.nicl.2018.101622
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发表时间：
2019-01-01
影响因子：
4.2
通讯作者：
Zhang, Yingchun
中科院分区：
文献类型：
--
作者：
Li, Rihui;Thinh Nguyen;Zhang, Yingchun
新的证据表明，阿尔茨海默病（AD）的认知缺陷与脑网络的破坏有关。因此，探索AD脑网络的改变对于理解和治疗该疾病具有重要意义。本研究采用综合功能近红外光谱（fNIRS）-脑电图（EEG）分析方法，探讨AD相关脑网络的动态，区域性改变。在数字言语广度任务（DVST）期间，同时记录了14名参与者（8名健康对照和6名轻度AD患者）的FNIRS和EEG数据。基于FNIRS的空间约束被用作EEG源定位的先验。然后从重建的EEG源计算基于图形的指数，以评估组间的区域差异。结果显示，轻度AD患者在高α带和β带的眶额和顶叶区域显示较弱和抑制的皮质连接。与年龄匹配的健康对照组相比，AD诱导的脑网络的主要特征是在所有频率范围内，额极和内侧眶额的程度较低，聚类系数较低。此外，AD组在上级颞沟的这些基于图形的指数也始终显示出较高的指数值。这些发现不仅验证了利用所提出的集成EEG-fNIRS分析来更好地理解大脑活动的时空动态的可行性，而且还有助于开发基于网络的方法来理解AD进展的机制。
Emerging evidence indicates that cognitive deficits in Alzheimer's disease (AD) are associated with disruptions in brain network. Exploring alterations in the AD brain network is therefore of great importance for understanding and treating the disease. This study employs an integrative functional near-infrared spectroscopy (fNIRS) - electroencephalography (EEG) analysis approach to explore dynamic, regional alterations in the AD-linked brain network. FNIRS and EEG data were simultaneously recorded from 14 participants (8 healthy controls and 6 patients with mild AD) during a digit verbal span task (DVST). FNIRS-based spatial constraints were used as priors for EEG source localization. Graph-based indices were then calculated from the reconstructed EEG sources to assess regional differences between the groups. Results show that patients with mild AD revealed weaker and suppressed cortical connectivity in the high alpha band and in beta band to the orbitofrontal and parietal regions. AD-induced brain networks, compared to the networks of age-matched healthy controls, were mainly characterized by lower degree, clustering coefficient at the frontal pole and medial orbitofrontal across all frequency ranges. Additionally, the AD group also consistently showed higher index values for these graph-based indices at the superior temporal sulcus. These findings not only validate the feasibility of utilizing the proposed integrated EEG-fNIRS analysis to better understand the spatiotemporal dynamics of brain activity, but also contribute to the development of network-based approaches for understanding the mechanisms that underlie the progression of AD.