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Cost-benefit tradeoff mediates the transition from rule-based to memory-based processing during practice

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  • Guochun Yang
  • Jiefeng Jiang

Abstract

Practice not only improves task performance but also changes task execution from rule- to memory-based processing by incorporating experiences from practice. However, how and when this change occurs is unclear. We test the hypothesis that strategy transitions in task learning can result from decision-making guided by cost-benefit analysis. Participants learn 2 task sequences and are then queried about the task type at a cued sequence and position. Behavioral improvement with practice can be accounted for by a computational model implementing cost-benefit analysis and the model-predicted strategy transition points align with the observed behavioral slowing. Model comparisons using behavioral data show that strategy transitions are better explained by a cost-benefit analysis across alternative strategies rather than solely on memory strength. Model-guided fMRI findings suggest that the brain encodes a decision variable reflecting the cost-benefit analysis and that different strategy representations are double-dissociated. Further analyses reveal that strategy transitions are associated with activation patterns in the dorsolateral prefrontal cortex and increased pattern separation in the ventromedial prefrontal cortex. Together, these findings support cost-benefit analysis as a mechanism of practice-induced strategy shift.Practice improves task performance and changes task execution from rule-based to memory-based processing by incorporating experiences from practice. This computational neuroimaging study reveals how the brain learns to perform a task more efficiently with a cost-benefit analysis that selects the optimal strategy.

Suggested Citation

  • Guochun Yang & Jiefeng Jiang, 2025. "Cost-benefit tradeoff mediates the transition from rule-based to memory-based processing during practice," PLOS Biology, Public Library of Science, vol. 23(1), pages 1-24, January.
  • Handle: RePEc:plo:pbio00:3002987
    DOI: 10.1371/journal.pbio.3002987
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    References listed on IDEAS

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    1. Ming Bo Cai & Nicolas W Schuck & Jonathan W Pillow & Yael Niv, 2019. "Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias," PLOS Computational Biology, Public Library of Science, vol. 15(5), pages 1-30, May.
    2. Jiefeng Jiang & Shao-Fang Wang & Wanjia Guo & Corey Fernandez & Anthony D. Wagner, 2020. "Prefrontal reinstatement of contextual task demand is predicted by separable hippocampal patterns," Nature Communications, Nature, vol. 11(1), pages 1-12, December.
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