A Genetic Algorithms for Optimizing Structural Brain Network Across Cognitive Tasks

The topology of structural brain networks is critical for information transmission and processing across brain regions, enabling the brain to flexibly perform diverse cognitive tasks through functional segregation and integration. While the architecture of brain networks continuously evolves and optimizes under the influence of factors such as wiring costs, it remains unclear whether cognitive tasks also impact this process. We formulate objective functions that integrate cognitive tasks with wiring cost factors and employ a genetic algorithm to iteratively optimize brain network structures. Our findings indicate that the optimized brain network structures driven by cognitive tasks closely resemble actual structural brain networks. Compared to optimizations considering individual cognitive tasks, the multi-task optimized brain network demonstrates greater similarity and topological alignment with structural brain networks. These results suggest that the formation of brain structural networks may incorporate the influence of multiple cognitive tasks, offering new insights into the close relationship between cognitive functions and brain structure.