Lateral-line activity during undulatory body motions suggests a feedback link in closed-loop control of sea lamprey swimming
Bibliographic record
Abstract
The lateral-line system is common to most aquatic organisms. It plays an important role in behaviours involving detection of other animals and obstacles. In gnathostome fishes, these behaviours appear to be dependent on an efferent inhibitory system that filters out stimuli caused by the animal’s own movement. Sea lampreys ( Petromyzon marinus L., 1758), the most basal extant vertebrate, possess a functional lateral-line system. Yet they completely lack the inhibitory efferent system. Thus, they may use the lateral line to sense their own swimming movements, helping to stabilize swimming. To test this hypothesis, we first investigated the kinematics of free-swimming lampreys. In an intact tethered preparation, we then generated undualatory body motions of comparable amplitude and frequency to swimming, while monitoring the evoked responses of the posterior lateral-line nerve. Last, we tested the effect of eliminating lateral-line inputs by cobalt treatment. In the tethered preparation, we recorded distinctive and consistent activity in the lateral-line nerve that was strongly dependent on characteristics of the motion. We found that distinct characteristics of the rhythmic movements are encoded in the temporal characteristics of the response. Swimming kinematics of cobalt-treated animals differed from controls, suggesting a complex, yet necessary role of the lateral-line system in closed-loop control of swimming.
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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 | 0.000 |
| 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) | 0.001 | 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".