Yang Chia-Yen, Lin Ching-Po
Department of Biomedical Engineering, Ming-Chuan University, Taoyuan, Taiwan,
Brain Topogr. 2015 Jul;28(4):529-40. doi: 10.1007/s10548-015-0432-8. Epub 2015 Apr 16.
Recent studies have shown the importance of graph theory in analyzing characteristic features of functional networks of the human brain. However, many of these explorations have focused on static patterns of a representative graph that describe the relatively long-term brain activity. Therefore, this study established and characterized functional networks based on the synchronization likelihood and graph theory. Quasidynamic graphs were constructed simply by dividing a long-term static graph into a sequence of subgraphs that each had a timescale of 1 s. Irregular changes were then used to investigate differences in human brain networks between resting and math-operation states using magnetoencephalography, which may provide insights into the functional substrates underlying logical reasoning. We found that graph properties could differ from brain frequency rhythms, with a higher frequency indicating a lower small-worldness, while changes in human brain state altered the functional networks into more-centralized and segregated distributions according to the task requirements. Time-varying connectivity maps could provide detailed information about the structure distribution. The frontal theta activity represents the essential foundation and may subsequently interact with high-frequency activity in cognitive processing.
最近的研究表明了图论在分析人类大脑功能网络特征方面的重要性。然而，这些探索大多集中在描述相对长期大脑活动的代表性图的静态模式上。因此，本研究基于同步似然性和图论建立并表征了功能网络。准动态图的构建方法很简单，即将一个长期静态图划分为一系列时间尺度为1秒的子图。然后利用不规则变化，通过脑磁图研究静息状态和数学运算状态下人类大脑网络的差异，这可能为逻辑推理背后的功能基质提供见解。我们发现，图属性可能与脑电频率节律不同，频率越高，小世界特性越低，而人类大脑状态的变化会根据任务需求将功能网络改变为更集中和隔离的分布。时变连接图可以提供有关结构分布的详细信息。额叶θ活动代表了基本基础，随后可能在认知加工中与高频活动相互作用。
