Modular Brain Networks.
Modular Brain Networks.
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DOI：
10.1146/annurev-psych-122414-033634
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发表时间：
2016
影响因子：
24.8
通讯作者：
Betzel RF
中科院分区：
文献类型：
--
作者：
Sporns O;Betzel RF
绘制结构和功能大脑连接的新技术的发展导致了神经元回路和系统的全面网络图的创建。这些大脑网络的结构可以用各种各样的图论工具来检查和分析。检测模块或网络社区的方法特别令人感兴趣，因为它们发现了连接特别密集的主要构建块或子网络，通常对应于专门的功能组件。社区发现的方法已经有很多，并且在网络神经科学中得到了广泛的应用。本文首先调查了一些这些方法，强调他们的优点和缺点，然后总结了结构和功能的大脑网络中存在的模块的主要发现，并简要地考虑其潜在的功能作用，在大脑的进化，布线最小化，功能专业化和复杂的动力学的出现。
The development of new technologies for mapping structural and functional brain connectivity has led to the creation of comprehensive network maps of neuronal circuits and systems. The architecture of these brain networks can be examined and analyzed with a large variety of graph theory tools. Methods for detecting modules, or network communities, are of particular interest because they uncover major building blocks or subnetworks that are particularly densely connected, often corresponding to specialized functional components. A large number of methods for community detection have become available and are now widely applied in network neuroscience. This article first surveys a number of these methods, with an emphasis on their advantages and shortcomings; then it summarizes major findings on the existence of modules in both structural and functional brain networks and briefly considers their potential functional roles in brain evolution, wiring minimization, and the emergence of functional specialization and complex dynamics.