Success modulates consolidation of a visuomotor adaptation task.
Bibliographic record
Abstract
Consolidation is a time-dependent process that is responsible for the storage of information in long-term memory. As such, it plays a crucial role in motor learning. Prior research suggests that some consolidation processes are triggered only when the learner experiences some success during practice. In the present study, we tested whether consolidation processes depend on the objective performance of the learner or on the learner's subjective evaluation of his or her own performance (i.e., how successful the learner believes he or she is). Four groups of participants performed 2 sessions of a visuomotor adaptation task for which they had to learn a new internal model of limb kinematics; these sessions were either 5 min or 24 hr apart. The task was identical for all participants, but each group was given a difficult or an easy objective that affected the participants' evaluation of their own performance during the initial practice session. All groups adapted their movements similarly to the rotation of the visual feedback during the first session. However, when retested the following day, participants who had a 24-hr rest interval and had initially experienced success performed significantly better than those who did not feel successful or who were given a 5-min rest interval. Our results indicate that a certain level of subjective success must be experienced to trigger certain consolidation processes.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".