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This ability to continuously acquire new skills, without forgetting or degrading old ones, comes naturally to humans but is a major challenge even for today’s most advanced artificial intelligence systems.
Now, scientists from the University of Cambridge and Columbia University have developed and experimentally verified a new mathematical theory that explains how the human brain achieves this feat. Called the COntextual INference (COIN) model, it suggests that identifying the current context is key to learning how to move our bodies.
The model describes a mechanism in the brain that is constantly trying to figure out the current context. The theory suggests that these continuously changing beliefs about context determine how to use existing memories — and whether to form new ones. The results are reported in the journal Nature.
“Imagine playing tennis with a different racket than usual or switching from tennis to squash,” said co-senior author Dr Daniel Wolpert from Columbia University. “Our theory explores how your brain adjusts to these situations and whether to treat them as distinct contexts.”
According to the COIN model, the brain maintains a repertoire of motor memories, each associated with the context in which it was created, such as playing squash versus tennis. Even for a single swing of the racket, the brain can draw upon many memories, each in proportion to how much the brain believes it is currently in the context in which that memory was created.