Abstract：
Humans possess morphologically complex brains, which are spatially constrained by their many intrinsic and extrinsic physical interactions. Anatomical network analysis can be used to study these constraints and their implications. Modularity is a key issue in this framework, namely, the presence of groups of elements that undergo morphological evolution in a concerted way. An array of community detection algorithms was tested on a previously designed anatomical network model of the human brain in order to provide a detailed assessment of modularity in this context. The algorithms that provide the highest quality partitions also reveal general phenotypic patterns underlying the topology of human brain morphology. Taken together, the community detection algorithms highlight the simultaneous presence of a longitudinal and a vertical modular partition of the brain\'s topology, the combination of which matches the organization of the enveloping braincase. Specifically, the longitudinal organization is in line with the different morphogenetic environments of the three endocranial fossae, while the vertical arrangement corresponds to the distinct developmental processes associated with the cranial base and vault, respectively. The results are robust and have the potential to be compared with equivalent network models of other species. Furthermore, they suggest a degree of concerted topological reciprocity in the spatial organization of brain and skull elements, and posit questions about the extent to which geometrical constraints of the cranial base and the modular partition of the corresponding brain regions may channel both evolutionary and developmental trajectories.
摘要：
人类拥有形态复杂的大脑，它们在空间上受到许多内在和外在物理相互作用的约束。解剖网络分析可用于研究这些约束及其含义。模块化是这个框架中的一个关键问题，即,以一致的方式进行形态进化的元素群的存在。在先前设计的人脑解剖网络模型上测试了一系列社区检测算法，以便在这种情况下提供对模块化的详细评估。提供最高质量分区的算法还揭示了人脑形态拓扑结构的一般表型模式。一起来看,社区检测算法突出了大脑拓扑的纵向和垂直模块化分区的同时存在，它们的组合与包围脑箱的组织相匹配。具体来说,纵向组织符合三个颅内窝的不同形态发生环境，虽然垂直排列对应于与颅底和拱顶相关的不同发育过程，分别。结果是稳健的，并且有可能与其他物种的等效网络模型进行比较。此外，他们提出了大脑和头骨元素的空间组织中一定程度的一致拓扑互惠，并提出有关颅底的几何约束和相应大脑区域的模块化分区可以在多大程度上引导进化和发育轨迹的问题。
