Reusable modular architecture enables flexible cognitive operations.

ABSTRACT: Complex behaviors are thought to be built by combining simpler cognitive components. Computational modeling has shown that artificial neural networks can perform a variety of tasks by flexibly combining small functional modules of neurons, each specialized for a specific computation, to construct a complex task. However, empirical evidence for such reusable modular networks in the brain has been lacking. Here, we show that mice performing a delayed match-to-sample with delayed report (DMS-dr) task reuse subspaces of neural activity that were specialized for stimulus processing and memory maintenance. These subspaces were reused during the task to represent new stimulus inputs and different types of memories, respectively. Clustering analyses showed each subspace was supported by a function

SUBMITTER: Osako Y 

PROVIDER: S-EPMC12458543 | biostudies-literature | 2025 Sep

REPOSITORIES: biostudies-literature