IntroductionCognitive impairment (CI) due to Alzheimer’s disease (AD) encompasses a decline in cognitive abilities and can significantly impact an individual’s quality of life. Early detection and intervention are crucial in managing CI, both in the preclinical and prodromal stages of AD prior to dementia.MethodsIn this preliminary study, we investigated differences in resting-state functional connectivity and dynamic network properties between 23 individual with CI due to AD based on clinical assessment and 15 healthy controls (HC) using Independent Component Analysis (ICA) and Dominant-Coactivation Pattern (d-CAP) analysis. The cognitive status of the two groups was also compared, and correlations between cognitive scores and d-CAP switching probability were examined.ResultsResults showed comparable numbers of d-CAPs in the Default Mode Network (DMN), Executive Control Network (ECN), and Frontoparietal Network (FPN) between HC and CI groups. However, the Visual Network (VN) exhibited fewer d-CAPs in the CI group, suggesting altered dynamic properties of this network for the CI group. Additionally, ICA revealed significant connectivity differences for all networks. Spatial maps and effect size analyses indicated increased coactivation and more synchronized activity within the DMN in HC compared to CI. Furthermore, reduced switching probabilities were observed for the CI group in DMN, VN, and FPN networks, indicating less dynamic and flexible functional interactions.DiscussionThe findings highlight altered connectivity patterns within the DMN, VN, ECN, and FPN, suggesting the involvement of multiple functional networks in CI. Understanding these brain processes may contribute to developing targeted diagnostic and therapeutic strategies for CI due to AD.

中文翻译：

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认知障碍中静息态功能连接和动态网络特性的改变：独立成分和显性共激活模式分析研究

简介阿尔茨海默病 (AD) 引起的认知障碍 (CI) 包括认知能力下降，可显着影响个人的生活质量。早期检测和干预对于管理 CI 至关重要，无论是在痴呆之前的 AD 临床前阶段还是前驱阶段。方法在这项初步研究中，我们调查了 23 名因 AD 导致的 CI 患者之间静息态功能连接和动态网络特性的差异。使用独立成分分析 (ICA) 和显性共激活模式 (d-CAP) 分析进行临床评估和 15 名健康对照 (HC)。还比较了两组的认知状态，并检查了认知得分与 d-CAP 转换概率之间的相关性。 结果结果显示，默认模式网络 (DMN)、执行控制网络 (ECN) 和执行控制网络 (ECN) 中的 d-CAP 数量相当。 HC 组和 CI 组之间的额顶网络 (FPN)。然而，视觉网络 (VN) 在 CI 组中表现出较少的 d-CAP，表明 CI 组该网络的动态特性发生了改变。此外，ICA 还揭示了所有网络的显着连接差异。空间图和效应大小分析表明，与 CI 相比，HC 中 DMN 内的共激活增加且同步活动更加同步。此外，在 DMN、VN 和 FPN 网络中观察到 CI 组的切换概率降低，表明动态和灵活的功能交互较少。讨论研究结果强调了 DMN、VN、ECN 和 FPN 内连接模式的改变，表明多个参与CI 中的功能网络。了解这些大脑过程可能有助于针对 AD 引起的 CI 制定有针对性的诊断和治疗策略。