Table_1_Increased functional connectivity patterns in mild Alzheimer’s disease: A rsfMRI study.DOCX

BackgroundAlzheimer’s disease (AD) is the most common age-related neurodegenerative disorder. In view of our rapidly aging population, there is an urgent need to identify Alzheimer’s disease (AD) at an early stage. A potential way to do so is by assessing the functional connectivity (FC), i.e., the statistical dependency between two or more brain regions, through novel analysis techniques.
MethodsIn the present study, we assessed the static and dynamic FC using different approaches. A resting state (rs)fMRI dataset from the Alzheimer’s disease neuroimaging initiative (ADNI) was used (n = 128). The blood-oxygen-level-dependent (BOLD) signals from 116 regions of 4 groups of participants, i.e., healthy controls (HC; n = 35), early mild cognitive impairment (EMCI; n = 29), late mild cognitive impairment (LMCI; n = 30), and Alzheimer’s disease (AD; n = 34) were extracted and analyzed. FC and dynamic FC were extracted using Pearson’s correlation, sliding-windows correlation analysis (SWA), and the point process analysis (PPA). Additionally, graph theory measures to explore network segregation and integration were computed.
ResultsOur results showed a longer characteristic path length and a decreased degree of EMCI in comparison to the other groups. Additionally, an increased FC in several regions in LMCI and AD in contrast to HC and EMCI was detected. These results suggest a maladaptive short-term mechanism to maintain cognition.
ConclusionThe increased pattern of FC in several regions in LMCI and AD is observable in all the analyses; however, the PPA enabled us to reduce the computational demands and offered new specific dynamic FC findings.

背景
阿尔茨海默病（Alzheimer’s disease, AD）是最常见的年龄相关性神经退行性疾病。鉴于当前全球人口快速老龄化的趋势，亟需实现阿尔茨海默病的早期筛查。其中一种潜在可行的途径是通过新型分析技术评估功能连接（functional connectivity, FC）——即两个或多个脑区间的统计依赖性。
方法
本研究采用多种方法评估静态与动态功能连接。我们使用了来自阿尔茨海默病神经影像倡议（Alzheimer’s disease neuroimaging initiative, ADNI）的静息态功能磁共振成像（resting state fMRI, rs-fMRI）数据集，样本量共128例。研究提取并分析了4组受试者的116个脑区的血氧水平依赖（blood-oxygen-level-dependent, BOLD）信号，4组分别为：健康对照（healthy controls, HC，n=35）、早期轻度认知障碍（early mild cognitive impairment, EMCI，n=29）、晚期轻度认知障碍（late mild cognitive impairment, LMCI，n=30）以及阿尔茨海默病（AD，n=34）。本研究通过皮尔逊相关分析、滑动窗口相关分析（sliding-windows correlation analysis, SWA）以及点过程分析（point process analysis, PPA）提取功能连接与动态功能连接指标；此外还计算了用于探究脑网络分离性与整合性的图论指标。
结果
本研究结果显示，相较于其余各组，早期轻度认知障碍组的特征路径长度更长，且节点度更低。同时，与健康对照和早期轻度认知障碍组相比，晚期轻度认知障碍与阿尔茨海默病组的多个脑区功能连接显著增强。上述结果提示存在一种维持认知的适应不良短期机制。
结论
晚期轻度认知障碍与阿尔茨海默病组多个脑区的功能连接增强模式在所有分析中均得以验证；但点过程分析不仅降低了计算开销，还为我们提供了新的特异性动态功能连接研究发现。