Building compositional tasks with shared neural subspaces.

ABSTRACT: Cognition is remarkably flexible; we are able to rapidly learn and perform many different tasks¹. Theoretical modeling has shown artificial neural networks trained to perform multiple tasks will re-use representations² and computational components³ across tasks. By composing tasks from these sub-components, an agent can flexibly switch between tasks and rapidly learn new tasks⁴. Yet, whether such compositionality is found in the brain is unknown. Here, we show the same subspaces of neural activity represent task-relevant information across multiple tasks, with each task compositionally combining these subspaces in a task-specific manner. We trained monkeys to switch between three compositionally related tasks. Neural recordings found task-relevan

SUBMITTER: Tafazoli S 

PROVIDER: S-EPMC10862921 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature