Taste discrimination in conditioned taste aversion of the pond snail<i>Lymnaea stagnalis</i>
Bibliographic record
Abstract
Conditioned taste aversion (CTA) in the pond snail Lymnaea stagnalis has been widely used as a model for gaining an understanding of the molecular and behavioral mechanisms underlying learning and memory. At the behavioral level, however, it is still unclear how taste discrimination and CTA interact. We thus examined how CTA to one taste affected the feeding response induced by another appetitive food stimulus. We first demonstrated that snails have the capacity to recognize sucrose and carrot juice as distinct appetitive stimuli. We then found that snails can become conditioned (i.e. CTA) to avoid one of the stimuli and not the other. These results show that snails can distinguish between appetitive stimuli during CTA, suggesting that taste discrimination is processed upstream of the site where memory consolidation in the snail brain occurs. Moreover, we examined second-order conditioning with two appetitive stimuli and one aversive stimulus. Snails acquired second-order conditioning and were still able to distinguish between the different stimuli. Finally, we repeatedly presented the conditional stimulus alone to the conditioned snails, but this procedure did not extinguish the long-term memory of CTA in the snails. Taken together, our data suggest that CTA causes specific, irreversible and rigid changes from appetitive stimuli to aversive ones in the conditioning procedure.
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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".