What is it about?
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 predictive learning account, which posits that testing (vs 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, testing and prediction error activate common neural areas, which in turn enhance declarative memory. This account may extend beyond testing to support active learning.
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Why is it important?
This study makes two key contributions: (1) situating the testing effect within a predictive learning and dopamine framework, and (2) demonstrating that signed and unsigned prediction errors coexist in distinct neural regions, offering new insight into the signed versus unsigned debate.
Perspectives
We hope this study opens the door to investigating the testing effect within a broader predictive learning and dopamine framework. The mechanisms by which predictive learning and dopamine support the testing effect are far more intriguing than we initially expected, and there is still a long way to go.
Haopeng Chen
Ghent University
Read the Original
This page is a summary of: Neural and computational evidence for a predictive learning account of the testing effect, Proceedings of the National Academy of Sciences, August 2025, Proceedings of the National Academy of Sciences,
DOI: 10.1073/pnas.2506530122.
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