Experience shapes initial exploration for non-generalizable spatial learning

Abstract

Experience can change how individuals learn. Learning to solve a new problem can be accelerated by generalizing known rules in the new context, but the impact of experience on solving problems where generalization cannot be applied remains unclear. To study the impact of experience on solving new problems that are distinct from previously learned tasks, we examined how rats learned a new spatial navigation task after having previously learned different sets of spatial navigation tasks. The new task differed from the previous tasks in spatial layout and navigation rule, and could not be solved by applying previously learned rules. We found that different experience histories did not impact task performance in the new task. However, by examining navigation choices made by rats, we found exploration patterns during the early stage of learning in the new task was dependent on experience history. We identified these behavioral differences by analyzing each rat’s navigation choices and by modeling their choice sequences with a modified distance dependent Chinese restaurant process. We further pinpointed the behavioral difference to sequential turn/no turn decisions made at choice points. Our results indicate that experience can influence problem-solving strategies when learning to solve new problems. Individuals with distinct experience histories can approach new problems from different starting points but converge on the same solution.