Zheng Gaoxing, Li Yuzhu, Qi Xiaoying, Zhang Wei, Yu Yuguo
State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Human Phenome Institute and Research Institute of Intelligent and Complex Systems, Institute of Science and Technology for Brain-Inspired Intelligence, Shanghai, 200433 China.
Department of Neurology, Zhongshan Hospital and Shanghai Medical College, Fudan University, Shanghai, 200032 China.
Phenomics. 2021 Nov 10;1(6):285-298. doi: 10.1007/s43657-021-00027-w. eCollection 2021 Dec.
Mathematical calculation usually requires sustained attention to manipulate numbers in the mind, while listening to light music has a relaxing effect on the brain. The differences in the corresponding brain functional network topologies underlying these behaviors remain rarely known. Here, we systematically examined the brain dynamics of four behaviors (resting with eyes closed and eyes open, tasks of music listening and mental calculation) using 64-channel electroencephalogram (EEG) recordings and graph theory analysis. We developed static and dynamic minimum spanning tree (MST) analysis method and demonstrated that the brain network topology under mental calculation is a more line-like structure with less tree hierarchy and leaf fraction; however, the hub regions, which are mainly located in the frontal, temporal and parietal regions, grow more stable over time. In contrast, music-listening drives the brain to exhibit a highly rich network of star structure, and the hub regions are mainly located in the posterior regions. We then adopted the dynamic dissimilarity of different MSTs over time based on the graph Laplacian and revealed low dissimilarity during mental calculation. These results suggest that the human brain functional connectivity of individuals has unique dynamic diversity and flexibility under various behaviors.
The online version contains supplementary material available at 10.1007/s43657-021-00027-w.
数学计算通常需要持续集中注意力在脑海中运算数字，而听轻音乐对大脑有放松作用。这些行为背后相应大脑功能网络拓扑结构的差异仍鲜为人知。在此，我们使用64通道脑电图（EEG）记录和图论分析系统地研究了四种行为（闭眼休息、睁眼休息、听音乐任务和心算任务）的脑动力学。我们开发了静态和动态最小生成树（MST）分析方法，并证明心算时的大脑网络拓扑结构是一种更类似线性的结构，树层次和叶分数较少；然而，主要位于额叶、颞叶和顶叶区域的枢纽区域随时间变得更加稳定。相比之下，听音乐促使大脑呈现出高度丰富的星型结构网络，且枢纽区域主要位于后部区域。然后，我们基于图拉普拉斯算子采用不同MST随时间的动态差异，并发现在心算过程中差异较低。这些结果表明，个体的人类大脑功能连接在各种行为下具有独特的动态多样性和灵活性。
在线版本包含可在10.1007/s43657-021-00027-w获取的补充材料。
