标题： 演进网络与神经系统的开发 显示英文标题

标题： Evolving Networks and the Development of Neural Systems

摘要： 现在普遍认为，自然界中大多数网络的异质性可能是通过某种优先连接方式产生的。 然而，各种其他拓扑特征（如度度相关性和相关特性）的起源通常并不明确，并被归因于特定的功能需求。 我们展示了如何分析一个非常一般的场景，在这个场景中，节点根据局部和/或全局度信息的任何（例如，非线性）函数来获得或失去边。 将我们的方法应用于两个截然不同的大脑发育例子——人类的突触修剪和线虫C. Elegans的神经网络——我们发现，简单的生物动机假设可以与实验数据很好地吻合。 特别是，线虫大脑的许多非平凡拓扑特征在临界点自然出现。 显示英文摘要

摘要： It is now generally assumed that the heterogeneity of most networks in nature probably arises via preferential attachment of some sort. However, the origin of various other topological features, such as degree-degree correlations and related characteristics, is often not clear and attributed to specific functional requirements. We show how it is possible to analyse a very general scenario in which nodes gain or lose edges according to any (e.g., nonlinear) functions of local and/or global degree information. Applying our method to two rather different examples of brain development -- synaptic pruning in humans and the neural network of the worm C. Elegans -- we find that simple biologically motivated assumptions lead to very good agreement with experimental data. In particular, many nontrivial topological features of the worm's brain arise naturally at a critical point.