Neural and computational evidence for a predictive learning account of the testing effect
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Testing enhances memory more than studying. Although numerous studies have demonstrated the robustness of this classic effect, its neural and computational origin remains debated.
Predictive learning is a potential mechanism behind this phenomenon: Because predictions and prediction errors (mismatch between predictions and feedback) can only be generated in testing (and not in studying), testing can benefit from predictive learning. We shed light on the testing effect from a multi-level analysis perspective via a combination of cognitive neuroscience experiments (fMRI) and computational modeling. At the neural level, we find that testing activates the canonical brain area related to reward prediction error, namely the ventral striatum. Crucially, activation in the ventral striatum fully mediates the testing effect.
Computationally, only a model incorporating predictive learning can account for the full breadth of behavioral patterns observed in the data. These results provide strong and converging evidence for a predictive learning account of the testing effect.
Significance Statement
An exam is not a neutral measurement of memory. The testing effect entails that a test (e.g., an exam), is more effective than study for learning and memory. The same effect can be harnessed also before events of significance take place, rendering it an important aspect of an active learning strategy. Nevertheless, its origin remains unknown. We propose a novel predictive learning account, which posits that testing (but not studying) facilitates predictions about study material and promotes learning from prediction errors. Computationally, the testing effect was explained through a predictive-learning-based neural network. Neurally, the testing effect was mediated by the ventral striatum, a key brain region encoding prediction errors. This account may extend beyond testing to support active learning.
