Enhancing endurance performance with combined imagined and actual physical practice
Bibliographic record
Abstract
Endurance sports require the sustained maintenance of high effort until the point of task failure. Psychological factors, particularly the perception of effort, exert considerable influence in determining task failure. Training interventions that blend physical and cognitive tasks yielded promising results in enhancing endurance performance. Motor imagery stands out as a method capable of modulating the perception of effort. However, the precise extent to which combining motor imagery and physical training can improve endurance performance remains to be understood. In a pre-post training design, this study aimed to investigate the impact of combining motor imagery with physical training on endurance performance, compared to physical training alone. Two groups of participants were constituted (motor imagery: n = 16; control: n = 17). Both groups performed physical exercises (i.e. isometric wall squat of incremental duration, with 12 training sessions over a period of 14 days), with participants from the motor imagery group also performing motor imagery sessions. Each participant visited the laboratory for experimental procedures twice before and twice after training, during which we assessed endurance performance through a sustained submaximal isometric contraction of the right knee extensors performed until task failure (time to task failure, TTF) at either 20 or 40% of the maximal voluntary contraction. Perceptions of effort and muscle pain were measured regularly during the endurance exercise. We reported no changes in endurance performance for the control group. Endurance performance in the motor imagery group exhibited significant improvements when the intensity of the sustained isometric TTF test closely matched that used in training (i.e. 20% of MVC). However, these enhancements were less pronounced when considering higher exercise intensities (i.e. 40% of MVC). No reduction in perception of effort was observed in both groups. There was a noticeable decrease in muscle pain perception within the motor imagery group following the training. Overall, combining motor imagery and physical training may thus offer a promising avenue for enhancing endurance performance and managing pain in various contexts, from sports to clinical rehabilitation.
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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 | 0.000 | 0.001 |
| 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".