One system for learning and remembering episodes and rules
This challenges cognitive science theories by suggesting that trade-offs in learning and memory arise from capacity limitations, not inherent incompatibility.
The study tackled the problem of whether separate systems are needed for learning and remembering episodes versus rules, showing that a single system with sufficient capacity can handle both tasks.
Humans can learn individual episodes and generalizable rules and also successfully retain both kinds of acquired knowledge over time. In the cognitive science literature, (1) learning individual episodes and rules and (2) learning and remembering are often both conceptualized as competing processes that necessitate separate, complementary learning systems. Inspired by recent research in statistical learning, we challenge these trade-offs, hypothesizing that they arise from capacity limitations rather than from the inherent incompatibility of the underlying cognitive processes. Using an associative learning task, we show that one system with excess representational capacity can learn and remember both episodes and rules.