Strain-specific differences of the effects of stress on memory in <i>Lymnaea</i>
Bibliographic record
Abstract
ABSTRACT Stress alters the ability to form, recall and maintain memory according to the Yerkes–Dodson/Hebb (YDH) law. The effects of environmentally relevant stressors, such as low environmental calcium and crowding, on learning and memory have previously been described in a laboratory-reared ‘average’ strain of Lymnaea stagnalis (i.e. the Dutch strain) as well as two strains of freshly collected L. stagnalis with enhanced memory formation abilities (i.e. ‘smart’ snails). Here, we use L. stagnalis to study the effects of other environmentally relevant stressors on memory formation in two other strains of freshly collected snails, one ‘smart’ and one ‘average’. The stressors we examined are thermal, resource restriction combined with food odour, predator detection and, for the first time, tissue injury (shell damage). We show that the same stressor has significantly different effects on memory formation depending on whether snails are ‘smart’ or ‘average’. Specifically, our data suggest that a stressor or a combination of stressors act to enhance memory in ‘average’ snails but obstruct memory formation in ‘smart’ snails. These results are consistent with the YDH law and our hypothesis that ‘smart’ snails are more easily stressed than ‘average’ snails.
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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".