School of Computing Science, Newcastle University, Newcastle upon Tyne,UK.
Network. 2011;22(1-4):143-7. doi: 10.3109/0954898X.2011.638968.
Neural networks show a progressive increase in complexity during the time course of evolution. From diffuse nerve nets in Cnidaria to modular, hierarchical systems in macaque and humans, there is a gradual shift from simple processes involving a limited amount of tasks and modalities to complex functional and behavioral processing integrating different kinds of information from highly specialized tissue. However, studies in a range of species suggest that fundamental similarities, in spatial and topological features as well as in developmental mechanisms for network formation, are retained across evolution. 'Small-world' topology and highly connected regions (hubs) are prevalent across the evolutionary scale, ensuring efficient processing and resilience to internal (e.g. lesions) and external (e.g. environment) changes. Furthermore, in most species, even the establishment of hubs, long-range connections linking distant components, and a modular organization, relies on similar mechanisms. In conclusion, evolutionary divergence leads to greater complexity while following essential developmental constraints.
神经网络在进化过程中表现出复杂性的逐渐增加。从刺胞动物的弥散神经网到猕猴和人类的模块化、分层系统，存在着从涉及有限数量任务和模态的简单过程向复杂功能和行为处理的逐渐转变，这种处理整合了来自高度专业化组织的不同类型的信息。然而，在一系列物种中的研究表明，在空间和拓扑特征以及网络形成的发育机制方面，基本相似性在进化过程中得以保留。“小世界”拓扑和高度连接的区域（枢纽）在进化尺度上普遍存在，确保了有效的处理能力和对内部（例如，损伤）和外部（例如，环境）变化的弹性。此外，在大多数物种中，即使是枢纽的建立、连接遥远成分的长程连接以及模块化组织，都依赖于类似的机制。总之，进化分歧导致了更大的复杂性，同时遵循着基本的发育约束。
