Habituated visual neurons in locusts remain sensitive to novel looming objects
Bibliographic record
Abstract
Many animals must contend with visual cues that provide information about the spatiotemporal dynamics of multiple objects in their environment. Much research has been devoted to understanding how an identified pair of interneurons in the locust, the Descending Contralateral Movement Detectors (DCMDs), respond to objects on an impending collision course. However, little is known about how these neurons respond when challenged with multiple, looming objects of different complex shapes. I presented locusts with objects resembling either another locust or a bird approaching on a direct collision course at 3 m s-1 while recording from the DCMD axon within the mesothoracic ganglion. Stimulus presentations were designed to test: (i) whether DCMD habituation was related to the frequency of approach, (ii) if habituated DCMDs were able to respond to a novel stimulus and (iii) if non-looming motion within complex objects (internal object motion) during approach affects habituation. DCMD responses to simulated locusts or birds habituated more when the time interval between consecutive approaches within similar sequences decreased from 34 s to 4 s. Strongly habituated DCMDs were, however, able to respond to the same object approaching along a new trajectory or to a larger object approaching along the same trajectory. Habituation was not affected by internal object motion. These data are consistent with earlier findings that DCMD habituation occurs at localized synapses, which permits maintained sensitivity to multiple objects in the animal's environment.
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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 | 0.001 |
| 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".