College of Microelectronics, Tianjin University, Tianjin, China.
Tianjin International Joint Research Center for Neural Engineering, Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, China.
Neuroradiology. 2018 Apr;60(4):403-412. doi: 10.1007/s00234-017-1973-1. Epub 2018 Jan 30.
Many questions remain regarding how the brain develops, matures, and ages across the lifespan. The functional connectivity networks in the resting-state brain can reflect many of the characteristic changes in the brain that are associated with increasing age. Functional connectivity has been shown to be time-dependent over the course of a lifespan and even over the course of minutes. The lifespan strategies of all cognitive networks and how dynamic functional connectivity is associated with age are unclear.
In this paper, studies employing both linear and quadratic models to define new specific lifespan strategies, including early/late increase/decrease models, were conducted to explore the lifespan functional changes. A large data sample was retrieved from the publicly available data from the Nathan Kline Institute (N = 149 and ages 9-85). Both static and dynamic functional connectivity indexes were calculated including the static functional connectivity, the mean of the dynamic functional connectivity and variations in dynamic functional connectivity.
The between-network connectivity results revealed early increases in the default-mode (DF) and cingulo-opercular network (CO)-associated network connectivities and a late increase in the fronto-parietal (FP)-associated network connectivity. These results depicted various lifespan strategies for different development stages and different cognitive networks across the lifespan. Additionally, the static FC and mean dynamic FC exhibited consistent results, and their variation exhibited a constant decrease with age across the entire age range.
These results (FDR-corrected p value < 0.05) suggest that the early/late variations in lifespan strategies could reflect an association between varied and complex circumstances and brain development.
关于大脑在整个生命周期中是如何发育、成熟和衰老的,仍有许多问题尚未解决。静息状态下大脑的功能连接网络可以反映出与年龄增长相关的许多大脑特征变化。已有研究表明,功能连接在整个生命周期中甚至在几分钟内都是时间依赖的。所有认知网络的寿命策略以及动态功能连接如何与年龄相关尚不清楚。
在本文中,采用线性和二次模型来定义新的特定寿命策略,包括早期/晚期增加/减少模型,来探索寿命功能变化。从 Nathan Kline 研究所(N=149,年龄 9-85 岁)的公开数据中检索了大量数据样本。计算了静态和动态功能连接指数,包括静态功能连接、动态功能连接的平均值和动态功能连接的变化。
网络间连接的结果表明,默认模式(DF)和扣带回-脑岛网络(CO)相关网络的连接性早期增加,额顶叶(FP)相关网络的连接性晚期增加。这些结果描绘了不同发展阶段和不同认知网络在整个生命周期中的不同寿命策略。此外,静态 FC 和平均动态 FC 表现出一致的结果,其变化随着年龄的增长在整个年龄段内呈持续下降趋势。
这些结果(经 FDR 校正的 p 值<0.05)表明,寿命策略的早期/晚期变化可能反映了不同和复杂环境与大脑发育之间的关联。