Performance-contingent monetary rewards undermine the facilitating effects of practice on retention
Bibliographic record
Abstract
It is generally conceived that the amount of practice trials and the delivery of performance-contingent monetary rewards are key drivers of long-term retention of motor memories. While these two factors likely interact to promote retention, this possibility has never been tested. Here, we tested this hypothesis by using a gradual visuomotor adaptation paradigm where the amount of practice trials (i.e., either 400 or 800) as well as the delivery of performance-contingent monetary rewards (i.e., either rewards or no reward) were manipulated. Participants took part in two experimental sessions separated by a 24-hour interval. During initial acquisition, performance and short-term retention were assessed via vision and no-vision catch trials, respectively. Long-term retention was measured the following day by using no vision trials. Expectedly, results revealed that performance-contingent rewards enhanced performance during the first 400 acquisition trials. Counter-intuitively, although performance remained similar between groups, levels of short-term retention were lower in the rewarded as compared to the unrewarded group during the last 400 acquisition trials. Unexpectedly, practicing for 800 trials with performance-contingent rewards impaired long-term retention as compared to when rewards were not delivered. Anticipatedly, practicing for 800 trials led to better long-term retention than practicing for 400 trials. The present results suggest that extrinsic rewards can undermine the formation of long-term motor memories, an idea that finds support in cellular/molecular studies, as well as work stemming from experimental psychology. Overall, these findings challenge classic reinforcement learning theories by showing that long-term retention does not always benefit from reward delivery during acquisition.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".