Structural Abstractions in Brains and Graphs

A graph database is a software system that stores data as interconnected vertices and edges. These databases are optimized for executing graph traversal processes. The structure of graphs shares similarities with neural systems like the human brain, which can be described as networks of neurons. As graph systems scale to include more diverse data, multi-level structural understanding becomes crucial for studying graphs and designing graph systems. Neuroscience may foster an appreciation of various structural abstractions within graphs. In both cognitive neuroscience and network science, it is common to abstract away low-level connectivity patterns to identify larger functional structures. Functional motifs can be identified in real-world graphs, similar to the brain's functional areas. Graph databases are developing infrastructure capable of representing and processing complex information landscapes within a unified structure, emphasizing the importance of structural abstractions for better reasoning about graphs and designing algorithms for collective problem-solving.