基于不同状态下脑电参量拓扑特性的阿尔茨海默病早期诊断研究

Early diagnosis of Alzheimer’s disease (AD) is a challenging problem in clinical practice, while electroencephalogram (EEG) has its unique advantages in resolving this problem...AD may cause the loss of cortical synapses and abnormality of neural network.Cognitive impairments, mainly with the form of hypomnesia, occur at the early stage of AD. Memory is a kind of neural activity process. It consists of synergistic activities among many distributive functional areas in the brain from the perspective of space, and at the same time it is a neural process which is composed of many cognitive substages from the viewpoint of time...Therefore, in this study the research object is EEG signals which are sampled during resting or performing working memory tasks. By effectively integrating the available method and by exploring new parameters, single-lead EEG signals accurately show the corresponding cerebral activities and the multi-lead EEG data show functional connectivity among brain areas. Consequently, due to the impact of AD on the spatial distribution of brain activity,brain mapping or brain functional network should be built so as to dig deeply into the sensitive and specific indicators for early diagnosis of AD...In particular, as a useful complement to the traditional technique of event-related oscillation, those nonlinearity and synchrony analysis methods, which are proved to deal with short-term data effectively, are first selected in this study to track the cognitive processes of memory dynamically.This technique possesses a potentially significant value in revealing neural mechanisms of memory and cognition in patients of early-stage AD, as well as in clinical applications..

阿尔茨海默病（AD）的早期诊断在临床上是一个难题，脑电图（EEG）在解决这一问题中有独特优势。..AD会造成皮层突触丢失、神经网络异常，疾病早期患者会出现以记忆力减退为主的认知障碍，而记忆是一种在空间上包含了多个分布式脑区协同工作、在时间上又由多项认知子阶段组成的神经活动过程。因此，项目组拟以静息态和执行工作记忆任务下的EEG为研究对象，通过有效整合已有参数和探索新参数，在正确表征单导EEG对应的脑区活动水平及多导EEG反映的脑功能连接状态的基础上，充分考虑疾病对脑活动空间分布的影响，从EEG参量的拓扑特性出发，构建脑地形图或脑功能网络，深入挖掘对疾病早期诊断敏感特异的指标。..特别地，作为对传统的事件相关脑震荡技术的有益补充，项目组首次提出采用对短时程数据处理稳健有效的非线性和同步性分析方法对记忆认知过程进行动态追踪，对于揭示早期AD患者的记忆认知神经机制和临床应用具有潜在的重大价值。

阿尔兹海默症（Alzheimer’s disease，AD）是一种以进行性认知障碍为特征的神经系统疾病，是老年期痴呆最常见的类型。AD的发病率随着年龄的增长呈指数式上升；随着世界人口进入老龄化，AD的流行将给个人、家庭和社会带来沉重的负担。研究正常老化以及AD患者的脑功能变化，对于AD的早期诊断和早期干预有着极其重要的作用。 .遵循N-back工作记忆范式，项目组设计了不同难度的认知任务，并采集了健康老年人和年轻人在静息态和执行工作记忆任务下的多导脑电信号。通过对事件相关电位的分析和复杂网络分析，我们发现：正常老化主要影响着前额区；老化所致的脑网络变化在给予被试一定的认知负载下变得显著；相比于低负荷认知任务，执行高负荷认知任务时更能反映老化对脑功能特征的影响。综上所述，给被检查者施加一定的认知负荷，如执行2-back任务，将有助于早期AD患者的诊断。.项目组采用基于图论的复杂网络分析方法，分析了静息态下AD/MCI(mild cognitive impairment)患者脑功能网络的变化。利用静息态的脑电图（electroencephalogram，EEG）信号或者功能磁共振信号(functional magnetic resonance imaging, fMRI)，我们构建了二值图或者无向有权图来描述脑功能网络。我们发现MCI/AD患者的脑功能网络效率显著降低，且这种降低与患者认知功能的受损程度密切相关。对于AD患者，脑功能网络效率的显著下降可通过对常规19导联EEG信号的复杂网络分析获得；但对于MCI患者，由19导EEG信号构建的脑功能网络，并未显示出显著的效率变化。而通过对健康老年人和早期的MCI患者基于fMRI信号的脑功能性网络的深入研究，我们发现相比于健康老年人，早期的MCI患者的脑功能网络效率也呈现了显著的下降。我们的研究表明：在MCI期，患者的脑功能网络就已经发生了改变；对于AD的早期诊断，常规的19导EEG的敏感性不如fMRI；复杂网络拓扑参数，如聚类系数、全局效率、度分布熵等，可能成为评估AD症状严重程度的客观指标。.总的说来，在本基金的资助下，项目组初步建立了健康人、AD患者脑电数据库；累计发表论文19 篇, 其中被SCI收录3篇, EI收录5篇, 北大核心期刊收录5篇。