Zhang Yinghui, Wang Yin, Chen Nan, Guo Man, Wang Xiuzhen, Chen Guangcai, Li Yongchao, Yang Lin, Li Shan, Yao Zhijun, Hu Bin
Gansu Provincial Key Laboratory of Wearable Computing, School of Information Science and Engineering, Lanzhou University, Lanzhou, China.
Guangyuan Mental Health Center, Guangyuan, China.
Front Aging Neurosci. 2021 Jan 18;12:607445. doi: 10.3389/fnagi.2020.607445. eCollection 2020.
Healthy aging is usually accompanied by changes in the functional modular organization of the human brain, which may result in the decline of cognition and underlying brain dysfunction. However, the relationship between age-related brain functional modular structure differences and cognition remain debatable. In this study, we investigated the age-associated differences of modules and hubs from young, middle and old age groups, using resting-state fMRI data from a large cross-sectional adulthood sample. We first divided the subjects into three age groups and constructed an individual-level network for each subject. Subsequently, a module-guided group-level network construction method was applied to form a weighted network for each group from which functional modules were detected. The intra- and inter-modular connectivities were observed negatively correlated with age. According to the detected modules, we found the number of connector hubs in the young group was more than middle-age and old group, while the quantity of provincial hubs in middle-age group was discovered more than other two groups. Further ROI-wise analysis shows that different hubs have distinct age-associated trajectories of intra- and inter-modular connections, which suggests the different types of topological role transitions in functional networks across age groups. Our results indicated an inverse association between functional segregation/integration with age, which demonstrated age-associated differences in communication effeciency. This study provides a new perspective and useful information to better understand the normal aging of brain networks.
健康衰老通常伴随着人类大脑功能模块化组织的变化，这可能导致认知能力下降和潜在的脑功能障碍。然而，与年龄相关的脑功能模块化结构差异与认知之间的关系仍存在争议。在本研究中，我们使用来自一个大型成年横断面样本的静息态功能磁共振成像数据，调查了青年、中年和老年组模块和枢纽的年龄相关差异。我们首先将受试者分为三个年龄组，并为每个受试者构建一个个体水平的网络。随后，应用一种模块引导的组水平网络构建方法，为每个组形成一个加权网络，并从中检测功能模块。观察到模块内和模块间的连通性与年龄呈负相关。根据检测到的模块，我们发现青年组中连接枢纽的数量多于中年组和老年组，而中年组中省级枢纽的数量多于其他两组。进一步的基于感兴趣区域的分析表明，不同的枢纽在模块内和模块间连接上具有不同的年龄相关轨迹，这表明不同年龄组功能网络中拓扑角色转换的类型不同。我们的结果表明功能分离/整合与年龄之间存在负相关，这证明了与年龄相关的通信效率差异。本研究为更好地理解脑网络的正常衰老提供了新的视角和有用信息。
