Responses of a locust visual interneuron correlate with simple and compound object motion within the vertical plane
Bibliographic record
Abstract
Animals living in complex visual environments must contend with multiple visual cues that signal potential threats by detecting approaching objects and generating adaptive avoidance responses. One collision detection system in locusts is composed of the lobula giant movement detector (LGMD) and its postsynaptic partner, the descending contralateral movement detector (DCMD). Extensive work on this pathway has revealed that it is preferentially selective to visual stimuli generated by an approaching object (looming) and triggers avoidance behaviours such as jumping and flight steering. Recent work has shown that this pathway also responds characteristically to complex object motion that includes trajectory changes in the horizontal plane. To test the hypothesis that responses of this pathway correlate to motion in the vertical plane, we recorded from the DCMD while presenting combinations of simple looming as well as translation and transitions from and to looming. We found that the DCMD responses occurred earlier and were more robust for vertical translation in the lateral visual field, perpendicular to the centre of the eye. We also found strong correlations for the timing and firing rate as well as the duration and number of spikes of described phases of the response. These findings fit with our existing understanding of how this pathway conveys visual information to downstream elements initiating and controlling escape behaviours and provide further information on how this tractable system adds to our understanding of fundamental mechanisms that underly visually evoked behaviours.
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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".