Bilateral flight muscle activity predicts wing kinematics and 3-dimensional body orientation of locusts responding to looming objects
Bibliographic record
Abstract
We placed locusts in a wind tunnel using a loose tether design that allowed for motion in all three rotational degrees of freedom during presentation of a computer-generated looming disc. High-speed video allowed us to extract wing kinematics, abdomen position and 3-dimensional body orientation. Concurrent electromyographic (EMG) recordings monitored bilateral activity from the first basalar depressor muscles (m97) of the forewings, which are implicated in flight steering. Behavioural responses to a looming disc included cessation of flight (wings folded over the body), glides and active steering during sustained flight in addition to a decrease and increase in wingbeat frequency prior to and during, respectively, an evasive turn. Active steering involved shifts in bilateral m97 timing, wing asymmetries and whole-body rotations in the yaw (ψ), pitch (χ) and roll (η) planes. Changes in abdomen position and hindwing asymmetries occurred after turns were initiated. Forewing asymmetry and changes in η were most highly correlated with m97 spike latency. Correlations also increased as the disc approached, peaking prior to collision. On the inside of a turn, m97 spikes occurred earlier relative to forewing stroke reversal and bilateral timing corresponded to forewing asymmetry as well as changes in whole-body rotation. Double spikes in each m97 occurred most frequently at or immediately prior to the time the locusts turned, suggesting a behavioural significance. These data provide information on mechanisms underlying 3-dimensional flight manoeuvres and will be used to drive a closed loop flight simulator to study responses of motion-sensitive visual neurons during production of realistic behaviours.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".