K. A. Norman

The paper develops a normative model of prospective memory that integrates reinforcement learning and evidence accumulation to optimize task performance with noisy perception and memory.

This study shows that larger reward prediction errors improve memory and learning, but these effects operate through separate mechanisms.

The paper investigates how episodic memory reactivation during working memory maintenance affects recognition performance, finding that it introduces context and leads to errors and slower responses.