Repetitive aggressive encounters generate a long-lasting internal state in <i>Drosophila melanogaster</i> males
Bibliographic record
Abstract
; however, little is known about the effects of chronic fighting experience. Here, we investigated if repeated fighting encounters would induce an internal state that could affect the expression of subsequent behavior. We trained wild-type males to become winners or losers by repeatedly pairing them with hypoaggressive or hyperaggressive opponents, respectively. As described previously, we observed that chronic losers tend to lose subsequent fights, while chronic winners tend to win them. Olfactory conditioning experiments showed that winning is perceived as rewarding, while losing is perceived as aversive. Moreover, the effect of chronic fighting experience generalized to other behaviors, such as gap-crossing and courtship. We propose that in response to repeatedly winning or losing aggressive encounters, male flies form an internal state that displays persistence and generalization; fight outcomes can also have positive or negative valence. Furthermore, we show that the activities of the PPL1-γ1pedc dopaminergic neuron and the MBON-γ1pedc>α/β mushroom body output neuron are required for aversion to an olfactory cue associated with losing fights.
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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".