College of Computer Science and Technology, Taiyuan University of Technology, Taiyuan, China.
School of Information, Shanxi University of Finance and Economics, Taiyuan, China.
J Neurophysiol. 2024 Sep 1;132(3):744-756. doi: 10.1152/jn.00027.2024. Epub 2024 Jul 17.
Alzheimer's disease (AD) is a neurodegenerative disease, and mild cognitive impairment (MCI) is considered a transitional stage between healthy aging and dementia. Early detection of MCI can help slow down the progression of AD. At present, there are few studies exploring the characteristics of abnormal dynamic brain activity in AD. This article uses a method called leading eigenvector dynamics analysis (LEiDA) to study resting-state functional magnetic resonance imaging (rs-fMRI) data of AD, MCI, and cognitively normal (CN) participants. By identifying repetitive states of phase coherence, intergroup differences in brain dynamic activity indicators are examined, and the neurobehavioral scales were used to assess the relationship between abnormal dynamic activities and cognitive function. The results showed that in the indicators of occurrence probability and lifetime, the globally synchronized state of the patient group decreased. The activity state of the limbic regions significantly detected the difference between AD and the other two groups. Compared to CN, AD and MCI have varying degrees of increase in default and visual region activity states. In addition, in the analysis related to the cognitive scales, it was found that individuals with poorer cognitive abilities were less active in the globally synchronized state and more active in limbic region activity state and visual region activity state. Taken together, these findings reveal abnormal dynamic activity of resting-state networks in patients with AD and MCI, provide new insights into the dynamic analysis of brain networks, and contribute to a deeper understanding of abnormal spatial dynamic patterns in AD patients. Alzheimer's disease (AD) is a neurodegenerative disease, but few studies have explored the characteristics of abnormal dynamic brain activity in AD patients. Here, our report reveals the abnormal dynamic activity of the patients' resting-state network, providing new insights into the dynamic analysis of brain networks and helping to gain a deeper understanding of the abnormal spatial dynamic patterns in AD patients.
阿尔茨海默病（AD）是一种神经退行性疾病，轻度认知障碍（MCI）被认为是健康衰老与痴呆之间的过渡阶段。早期发现 MCI 有助于减缓 AD 的进展。目前，很少有研究探索 AD 患者异常动态脑活动的特征。本文使用一种称为主导特征向量动力学分析（LEiDA）的方法来研究 AD、MCI 和认知正常（CN）参与者的静息态功能磁共振成像（rs-fMRI）数据。通过识别相位相干的重复状态，研究了脑动态活动指标在组间的差异，并使用神经行为量表评估了异常动态活动与认知功能之间的关系。结果表明，在出现概率和寿命的指标中，患者组的全局同步状态减少。边缘区域的活动状态显著检测到 AD 与其他两组之间的差异。与 CN 相比，AD 和 MCI 的默认和视觉区域活动状态有不同程度的增加。此外，在与认知量表相关的分析中，发现认知能力较差的个体在全局同步状态下的活动较少，而在边缘区域活动状态和视觉区域活动状态下的活动较多。总之，这些发现揭示了 AD 和 MCI 患者静息态网络的异常动态活动，为脑网络的动态分析提供了新的见解，并有助于更深入地了解 AD 患者的异常空间动态模式。
