Department of Psychology, Concordia University, Montréal, Canada; Canadian Consortium on Neurodegeneration in Aging (CCNA), Canada; Centre for Research on Brain, Language and Music (CRBLM), Montréal, Canada; Centre for Research in Human Development (CRDH), Montréal, Canada.
Department of Psychology, Concordia University, Montréal, Canada; Canadian Consortium on Neurodegeneration in Aging (CCNA), Canada; Centre for Research on Brain, Language and Music (CRBLM), Montréal, Canada; Centre for Research in Human Development (CRDH), Montréal, Canada.
Cortex. 2024 Apr;173:313-332. doi: 10.1016/j.cortex.2024.02.005. Epub 2024 Feb 21.
Subjective cognitive decline (SCD) is characterized by subjective concerns of cognitive change despite test performance within normal range. Although those with SCD are at higher risk for developing further cognitive decline, we still lack methods using objective cognitive measures that reliably distinguish SCD from cognitively normal aging at the group level. Network analysis may help to address this by modeling cognitive performance as a web of intertwined cognitive abilities, providing insight into the multivariate associations determining cognitive status. Following previous network studies of mild cognitive impairment (MCI) and Alzheimer's dementia (AD), the current study centered upon the novel visualization and analysis of the SCD cognitive network compared to cognitively normal (CN) older adult, MCI, and AD group networks. Cross-sectional neuropsychological data from CIMA-Q and COMPASS-ND cohorts were used to construct Gaussian graphical models for CN (n = 122), SCD (n = 207), MCI (n = 210), and AD (n = 79) groups. Group networks were explored in terms of global network structure, prominent edge weights, and strength centrality indices. CN and SCD group networks were contrasted using the Network Comparison Test. Results indicate that CN and SCD groups did not differ in univariate cognitive performance or global network structure. However, measures of strength centrality, principally in executive functioning and processing speed, showed a CN-SCD-MCI gradient where subtle differences within the SCD network suggest that SCD is an intermediary between CN and MCI stages. Additional results may indicate a distinctiveness of network structure in AD, a reversal in network influence between age and general cognitive status as clinical impairment increases, and potential evidence for cognitive reserve. Together, these results provide evidence that network-specific metrics are sensitive to cognitive performance changes across the dementia risk spectrum and can help to objectively distinguish SCD group cognitive performance from that of the CN group.
主观认知衰退（SCD）的特征是尽管测试表现正常范围内，但仍存在认知改变的主观担忧。尽管 SCD 患者发生进一步认知衰退的风险更高，但我们仍然缺乏使用客观认知测量方法在组水平上可靠地区分 SCD 与认知正常衰老的方法。网络分析可能通过将认知表现建模为相互交织的认知能力网络来帮助解决这一问题，从而深入了解确定认知状态的多变量关联。继轻度认知障碍（MCI）和阿尔茨海默病（AD）的先前网络研究之后，本研究集中于与认知正常（CN）老年、MCI 和 AD 组网络相比，SCD 认知网络的新颖可视化和分析。使用 CIMA-Q 和 COMPASS-ND 队列的横断面神经心理学数据来构建 CN（n=122）、SCD（n=207）、MCI（n=210）和 AD（n=79）组的高斯图形模型。从全局网络结构、突出的边缘权重和强度中心性指数方面探讨了组网络。使用网络比较测试对比了 CN 和 SCD 组网络。结果表明，CN 和 SCD 组在单变量认知表现或全局网络结构方面没有差异。然而，强度中心性的度量标准，主要是在执行功能和处理速度方面，显示出 CN-SCD-MCI 的梯度，其中 SCD 网络内的细微差异表明 SCD 是 CN 和 MCI 阶段之间的中间阶段。其他结果可能表明 AD 的网络结构具有独特性，随着临床损伤的增加，年龄和一般认知状态之间的网络影响发生逆转，以及认知储备的潜在证据。总之，这些结果提供了证据表明，网络特定指标对痴呆风险谱内的认知表现变化敏感，并且可以帮助客观地区分 SCD 组认知表现与 CN 组。
