Qian Yu, Cao Jiahui, Han Jing, Zhang Siyi, Chen Wentao, Lei Zhao, Cui Xiaohua, Zheng Zhigang
College of Physics and Optoelectronic Technology, Baoji University of Arts and Sciences, Baoji, China.
School of Systems Science, Beijing Normal University, Beijing, China.
Front Netw Physiol. 2024 Oct 17;4:1390319. doi: 10.3389/fnetp.2024.1390319. eCollection 2024.
The study of specific physiological processes from the perspective of network physiology has gained recent attention. Modeling the global information integration among the separated functionalized modules in structural and functional brain networks is a central problem. In this article, the preferentially cutting-rewiring operation (PCRO) is introduced to approximatively describe the above physiological process, which consists of the cutting procedure and the rewiring procedure with specific preferential constraints. By applying the PCRO on the classical Erdös-Rényi random network (ERRN), three types of isolated nodes are generated, based on which the common leaves (CLs) are formed between the two hubs. This makes the initially homogeneous ERRN experience drastic changes and become heterogeneous. Importantly, a statistical analysis method is proposed to theoretically analyze the statistical properties of an ERRN with a PCRO. Specifically, the probability distributions of these three types of isolated nodes are derived, based on which the probability distribution of the CLs can be obtained easily. Furthermore, the validity and universality of our statistical analysis method have been confirmed in numerical experiments. Our contributions may shed light on a new perspective in the interdisciplinary field of complexity science and biological science and would be of great and general interest to network physiology.
从网络生理学的角度对特定生理过程进行研究最近受到了关注。对结构和功能脑网络中分离的功能模块之间的全局信息整合进行建模是一个核心问题。在本文中,引入了优先切割 - 重新布线操作(PCRO)来近似描述上述生理过程,它由切割过程和具有特定优先约束的重新布线过程组成。通过将PCRO应用于经典的厄多斯 - 雷尼随机网络(ERRN),生成了三种类型的孤立节点,并在此基础上在两个枢纽之间形成了公共叶(CLs)。这使得最初均匀的ERRN经历剧烈变化并变得异质。重要的是,提出了一种统计分析方法从理论上分析具有PCRO的ERRN的统计特性。具体而言,推导了这三种类型孤立节点的概率分布,并在此基础上可以轻松获得CLs的概率分布。此外,我们的统计分析方法的有效性和普遍性在数值实验中得到了证实。我们的贡献可能为复杂科学和生物科学的跨学科领域提供一个新的视角,并且对网络生理学具有重大的普遍意义。