PT - JOURNAL ARTICLE AU - Hall-McMaster, Sam AU - Tomov, Momchil AU - Gershman, Samuel J. AU - Schuck, Nicolas W. TI - Neural Prioritisation of Past Solutions Supports Generalisation AID - 10.1101/2024.06.10.598294 DP - 2024 Jan 01 TA - bioRxiv PG - 2024.06.10.598294 4099 - http://biorxiv.org/content/early/2024/07/11/2024.06.10.598294.short 4100 - http://biorxiv.org/content/early/2024/07/11/2024.06.10.598294.full AB - Generalisation from past experience is an important feature of intelligent systems. When faced with a new task, efficient generalisation can be achieved by evaluating solutions to earlier tasks as candidates for reuse. Consistent with this idea, we found that human participants (n=40) learned optimal solutions to a set of training tasks and continued to reuse them on novel test tasks. Corresponding functional magnetic resonance imaging data showed that optimal solutions from the training tasks were represented on test tasks in occipitotemporal and dorsolateral prefrontal cortex. These findings suggest that humans evaluate and generalise successful past solutions when attempting to solve new tasks.Competing Interest StatementThe authors have declared no competing interest.