How Shared Representations Become Specialized: Formation, Maintenance, and Latent Susceptibility
The study investigates how shared internal representations become specialized during minimal artificial learning by examining formation, maintenance, and latent susceptibility. It finds that precise acquisition of a target drives specialization, while state-following feedback maintains it. The results suggest that present conditions sustaining specialization are more important than the formation history itself.