The influence of kinesthetic motor imagery and effector specificity on the long-latency stretch response
Bibliographic record
Abstract
Abstract The long-latency “reflexive” response (LLR) following an upper-limb mechanical disturbance is generated by neural circuitry shared with voluntary control. This feedback response supports many task-dependent behaviours and permits the expression of goal-directed corrections at latencies shorter than voluntary reaction time. An extensive body of literature has demonstrated that the LLR shows flexibility akin to voluntary control, but it has never been tested whether instruction-dependent LLR changes can also occur in the absence of an overt voluntary response. The present study used kinesthetic motor imagery (Experiment 1) and instructed participants to execute a voluntary response in a non-stretched contralateral muscle (Experiment 2) to explore the relationship between the overt production of a voluntary response and LLR facilitation. Activity in stretched right wrist flexors were compared 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 LLR (R2) was facilitated and displayed a similar increase to compensate trials. The latter half of the LLR (R3) showed further modulation, mirroring the patterns of voluntary response activity. By contrast, the LLR on “non-leaked” imagery and contralateral trials did not modulate. We suggest that even though a hastened voluntary response cannot account for all instruction-dependent LLR modulation, the overt execution of a voluntary response in the same muscle(s) as the LLR is a pre-requisite for facilitation of this rapid feedback response. New and Noteworthy We examined volitional modulation of the long-latency stretch response (LLR) using two novel approaches: motor imagery and the execution of contralateral movements. The LLR was only facilitated on imagery or contralateral trials when a voluntary response “leaked-out” into stretched muscle suggesting that a voluntary response in the same muscle as the LLR is a prerequisite for facilitation. Our findings also demonstrate an important distinction between the early (R2) and late (R3) portions of the LLR.
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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 | 0.002 |
| 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) | 0.002 | 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".