The long-latency reflex is composed of at least two functionally independent processes
Bibliographic record
Abstract
The nervous system counters mechanical perturbations applied to the arm with a stereotypical sequence of muscle activity, starting with the short-latency stretch reflex and ending with a voluntary response. Occurring between these two events is the enigmatic long-latency reflex. Although researchers have been fascinated by the long-latency reflex for over 60 years, some of the most basic questions about this response remain unresolved and often debated. In the present study we help resolve one such question by providing clear evidence that the human long-latency reflex during a naturalistic motor task is not a single functional response; rather, it appears to reflect the output of (at least) two functionally independent processes that overlap in time and sum linearly. One of these functional components shares an important attribute of the short-latency reflex (i.e., automatic gain scaling, sensitivity to background load), and the other shares a defining feature of voluntary control (i.e., task dependency, sensitivity to goal target position). We further show that the task-dependent component of long-latency activity reflects a feedback control process rather than the simplest triggered reaction to a mechanical stimulus.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".