标题： 基本原理驱动类脑连接结构的自组织 显示英文标题

标题： Basic principles drive self-organization of brain-like connectivity structure

摘要： 大脑可以被视为一个系统，该系统根据功能连接的效率要求动态优化解剖连接的结构。 为了说明这一原理在组织大脑结构复杂性中的强大作用，我们将功能连接描绘为当前网络结构上的扩散。 这种扩散驱动适应性重布线，导致网络发生变化以提高其效率。 网络结构的这种动态演化产生了模块化的小世界结构，并因此解释了丰富的俱乐部效应，这些是神经解剖中常见的特征。 考虑到布线长度和传播波，会导致更具体的神经结构的形成，这些结构是详细大脑功能解剖中的关键，例如并行性、发散性、收敛性、超级环和超级链。 通过展示这些结构如何出现，主要独立于其特定的生物学实现，我们提出了一个新的假设，说明自然和人工类脑结构如何可以被物理实现。 显示英文摘要

摘要： The brain can be considered as a system that dynamically optimizes the structure of anatomical connections based on the efficiency requirements of functional connectivity. To illustrate the power of this principle in organizing the complexity of brain architecture, we portray the functional connectivity as diffusion on the current network structure. The diffusion drives adaptive rewiring, resulting in changes to the network to enhance its efficiency. This dynamic evolution of the network structure generates, and thus explains, modular small-worlds with rich club effects, f eatures commonly observed in neural anatomy. Taking wiring length and propagating waves into account leads to the morphogenesis of more specific neural structures that are stalwarts of the detailed brain functional anatomy, such as parallelism, divergence, convergence, super-rings, and super-chains. By showing how such structures emerge, largely independently of their specific biological realization, we offer a new conjecture on how natural and artificial brain-like structures can be physically implemented.