Individuality across environmental context in Drosophila melanogaster
Bibliographic record
Abstract
Abstract Over the past decade, several studies have demonstrated that idiosyncratic animal behaviors remain stable over long time periods. The stability of individually variable behaviors over time is often referred to as an animal’s individuality, or personality. However, most studies have focused on individuality in a single, well-defined environmental context, whereas it is well-established from population studies that animal behavior is highly context-dependent. The ongoing ‘person-situation debate’ in humans raises the question whether also animal behavior remains stable across different situations, such as changing environmental contexts. For instance, one individual might be generally more visually guided than another, or rely only on one particular visual cue, or even on this very cue only in a specific environmental context. Here we use a combination of both well-established and novel behavioral assays to investigate the relationship between individual behavior and environmental context. The stability of three individual traits (exploration, attention, and anxiety) was investigated under changing environmental contexts (temperature, visual cues, arena shape), in both walking and flying Drosophila melanogaster. We find that individuality is highly context-dependent, but even under the most extreme environmental alterations tested, stability of behavior always persisted in at least one of the traits. Furthermore, our quantification reveals a hierarchical order of environmental features influencing individuality. In summary, our work demonstrates that similar to humans, animal individuality persists across different contexts, and individual differences shape behavior across variable environments.
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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".