In a new study, neuroscientists at Princeton University have revealed a key mechanism by which the brain maintains its advantage over artificial intelligence (AI): the brain repeats the same cognitive "modules" in different tasks, and by combining and reassembling these modules, like building blocks, the brain can quickly construct new behavioral patterns. This study was published in the latest issue of the journal Nature. The most advanced AI models currently available can reach or even surpass human levels on a single task, but perform poorly when learning and executing multiple different tasks. This is because the human brain still maintains an advantage in a key aspect: cognitive flexibility. For example, humans can relatively easily adapt to new information or unfamiliar challenges, such as learning new software, following recipes to cook, or quickly getting started with a new game, while AI finds it difficult to achieve such "real-time" learning. Research has found that the reason why the brain is flexible is because it can reuse cognitive components, just like building blocks, piecing together these "cognitive blocks". For example, people who can repair bicycles will use relevant skills when learning to repair motorcycles, making them more proficient. However, there is still a lack of consistent and sufficient evidence in the scientific community on how the brain achieves this cognitive flexibility. The team trained two male rhesus monkeys to complete three related classification tasks and recorded their brain activity during the process. These tasks are similar to determining whether a blurry image on the screen resembles a rabbit or the letter 'T', or is closer to red or green. The degree of image blur varies, sometimes with significant differences and sometimes very subtle. Monkeys express their judgments by looking in different directions. The key to experimental design is that although each task is different, it shares certain cognitive elements, which can test how the brain repeats the same neural activity patterns. After analyzing multiple brain regions, the team found that the prefrontal cortex (the brain area responsible for advanced cognitive functions) contains several reusable activity patterns that correspond to different "cognitive building blocks". The brain constructs new behaviors by flexibly piecing together these "building blocks". In addition, the prefrontal cortex suppresses the activity of certain cognitive modules when they are not needed, thereby helping the brain concentrate on processing the current task. This is because cognitive resources are limited, and the brain ensures that the primary target task is not disrupted. The team claims that this combination based learning approach may be the key to humans being able to efficiently learn new skills without forgetting old ones. In contrast, current AI systems often encounter the problem of "catastrophic interference" - after learning a new task, they often overwrite their previous memories. If the modular and reconfigurable mechanism of the human brain is introduced into AI, it may be possible to develop intelligent systems that can continuously learn without forgetting. Meanwhile, this discovery also has clinical significance for understanding certain mental illnesses and brain injuries. (New Society)