The influence of kinesthetic motor imagery and effector specificity on the long-latency stretch response
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Bibliographic record
Abstract
Mechanical perturbations to the arms produce short (SLFR; 25-50ms) and long-latency (LLFR; 50-100ms) feedback responses in stretched muscles. The SLFR is generated by spinal circuitry and remains immutable to intention. By contrast, the LLFR engages supra-spinal regions shared with voluntary control and possesses the capacity to modulate in a manner similar to volition (Pruszynski et al., 2008). The present study investigated whether the overt execution of a voluntary response in stretched muscle is required for facilitation of the LLFR. Participants engaged in kinesthetic motor imagery of a compensate task (Experiment 1) or were instructed to execute voluntary responses in a non-stretched contralateral muscle (Experiment 2). The LLFR in stretched right wrist flexors were compared on Imagery and Contralateral trials to standard "Not-Intervene" and "Compensate" conditions. Our findings revealed that on ~40% of Imagery and ~50% of Contralateral trials, a partial voluntary response "leaked-out" into the stretched right wrist flexor muscle. On these "leaked" trials, the early portion of the LLFR (R2: 50-75ms) was increased compared to the Not-Intervene condition and appeared indistinguishable to the facilitation observed on Compensate trials. The latter portion of the LLFR (R3: 75-100ms) showed further modulation that mirrored the patterns of voluntary activity. By contrast, the LLFR on "non-leaked" Imagery and Contralateral trials appeared similar to the Not-Intervene condition. These findings suggest that even though a hastened voluntary response cannot account for all LLFR facilitation, the overt execution of a voluntary response in stretched muscle is required for instruction-dependent modulation of this rapid feedback response.Acknowledgments: NSERC
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it