Bees’ secret to learning may transform how robots recognize patterns

Researchers at the University of Sheffield have discovered that bees actively shape their visual perception through flight movements, rather than passively seeing their environment. By creating a computational model mimicking a bee’s brain, they showed that bees’ unique flight patterns generate distinct neural signals that enable them to recognize complex visual patterns, such as flowers and human faces, with high accuracy. This finding reveals that even tiny brains, evolved over millions of years, can perform sophisticated computations by integrating movement and sensory input, challenging assumptions about brain size and intelligence. The study builds on previous work by the same team, moving from observing bee flight behavior to uncovering the neural mechanisms behind active vision. Their model demonstrates that intelligence arises from the interaction between brain, body, and environment, rather than from brain size alone. Supporting this, Professor Lars Chittka highlighted that insect microbrains require surprisingly few neurons to accomplish complex visual discrimination tasks, including face recognition. Published in eLife and conducted in collaboration with Queen Mary University of London, this research