Alarm cues and alarmed conspecifics: neural activity during social learning from different cues in Trinidadian guppies
Bibliographic record
Abstract
Learning to respond appropriately to novel dangers is often essential to survival and success, but carries risks. Learning about novel threats from others (social learning) can reduce these risks. Many species, including the Trinidadian guppy ( Poecilia reticulata ), respond defensively to both conspecific chemical alarm cues and conspecific anti-predator behaviours, and in other fish such social information can lead to a learned aversion to novel threats. However, relatively little is known about the neural substrates underlying social learning and the degree to which different forms of learning share similar neural mechanisms. Here, we explored the neural substrates mediating social learning of novel threats from two different conspecific cues (i.e. social cue-based threat learning). We first demonstrated that guppies rapidly learn about threats paired with either alarm cues or with conspecific threat responses (demonstration). Then, focusing on acquisition rather than recall, we discovered that phospho-S6 expression, a marker of neural activity, was elevated in guppies during learning from alarm cues in the putative homologue of the mammalian lateral septum and the preoptic area. Surprisingly, these changes in neural activity were not observed in fish learning from conspecific demonstration. Together, these results implicate forebrain areas in social learning about threat but raise the possibility that circuits contribute to such learning in a stimulus-specific manner.
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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".