RT Journal Article
SR Electronic
T1 Neural Prioritisation of Past Solutions Supports Generalisation
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 2024.06.10.598294
DO 10.1101/2024.06.10.598294
A1 Hall-McMaster, Sam
A1 Tomov, Momchil
A1 Gershman, Samuel J.
A1 Schuck, Nicolas W.
YR 2024
UL http://biorxiv.org/content/early/2024/07/11/2024.06.10.598294.abstract
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.