Lin Shayne S-H, McDonough Ian M
Department of Psychology, The University of Alabama, Tuscaloosa, Alabama, USA.
Neuropsychol Dev Cogn B Aging Neuropsychol Cogn. 2022 May;29(3):375-399. doi: 10.1080/13825585.2021.2021134. Epub 2021 Dec 28.
Intra-Individual Cognitive Variability (IICV) predicts progression in neurocognitive disorders . Given important clinical applications, we investigated the association between IICV and multiple brain metrics across 17 networks to better understand the brain mechanisms underlying this performance measure. Sixty-three middle-aged and older adults without dementia underwent a neuropsychological battery, resting-state fMRI, and structural MRI scans. In a linear mixed effect model, higher IICV was associated with lower functional connectivity in control C network relative to medial occipital network (the reference). A multivariate partial least squares analysis revealed that lower mean and higher variability were both associated with lower connectivity in sensorimotor and default mode networks, while higher mean and higher variability were associated with lower volume in default mode and limbic networks. This study suggests that IICV signals widespread network dysfunction across multiple brain networks. These brain abnormalities offer new insights into mechanisms of early cognitive dysfunction. Clinical implications are discussed.
个体内认知变异性(IICV)可预测神经认知障碍的进展。鉴于其重要的临床应用价值,我们研究了IICV与17个网络中多个脑指标之间的关联,以更好地理解这一性能指标背后的脑机制。63名无痴呆的中老年人接受了神经心理测验、静息态功能磁共振成像和结构磁共振成像扫描。在线性混合效应模型中,相对于枕内侧网络(参照网络),IICV越高,控制C网络中的功能连接性越低。多变量偏最小二乘分析显示,较低的均值和较高的变异性均与感觉运动网络和默认模式网络中较低的连接性相关,而较高的均值和较高的变异性与默认模式网络和边缘网络中较低的体积相关。本研究表明,IICV表明多个脑网络存在广泛的网络功能障碍。这些脑异常为早期认知功能障碍的机制提供了新的见解。文中还讨论了其临床意义。