Visual stimuli induced by self-motion and object-motion modify odour-guided flight of male moths (<i>Manduca sexta</i> L.)
Bibliographic record
Abstract
Animals rely on multimodal sensory integration for proper orientation within their environment. For example, odour-guided behaviours often require appropriate integration of concurrent visual cues. To gain a further understanding of mechanisms underlying sensory integration in odour-guided behaviour, our study examined the effects of visual stimuli induced by self-motion and object-motion on odour-guided flight in male M. sexta. By placing stationary objects (pillars) on either side of a female pheromone plume, moths produced self-induced visual motion during odour-guided flight. These flights showed a reduction in both ground and flight speeds and inter-turn interval when compared with flight tracks without stationary objects. Presentation of an approaching 20 cm disc, to simulate object-motion, resulted in interrupted odour-guided flight and changes in flight direction away from the pheromone source. Modifications of odour-guided flight behaviour in the presence of stationary objects suggest that visual information, in conjunction with olfactory cues, can be used to control the rate of counter-turning. We suggest that the behavioural responses to visual stimuli induced by object-motion indicate the presence of a neural circuit that relays visual information to initiate escape responses. These behavioural responses also suggest the presence of a sensory conflict requiring a trade-off between olfactory and visually driven behaviours. The mechanisms underlying olfactory and visual integration are discussed in the context of these behavioural responses.
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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".