Shell damage leads to enhanced memory formation in <i>Lymnaea</i>
Bibliographic record
Abstract
Ecologically relevant stressors alter the ability of the pond snail, Lymnaea stagnalis, to form long-term memory (LTM). Here we show that an environmentally relevant stressor, shell damage, has a dramatic effect on the enhancement of LTM formation. Damage in the form of a shell clip 24h before operant conditioning training results in a single 0.5h training session (TS) to cause long-term memory (LTM) formation. Typically, in these snails two 0.5h TSs with a 1h interval between the sessions are required to cause LTM formation. We show here that even with a 72h interval between shell clip and training, memory enhancement still occurs. The stress associated with shell clip can be mitigated by an ongoing high Ca++ pond water environment, an injection of propranolol, and a DNA methylation blocker. However, use of an anesthetic (MgCl2) during the clip or intermittent exposure to the high Ca++ pond water environment does not mitigate the stress associated with the shell clip. Shell clip is also sufficient to cause juvenile snails, which neither learn nor form memory, to gain the capacity to form LTM. Together the experiments demonstrate that shell clipping is an environmentally relevant stressor that can cause enhancement of LTM formation.
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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) | 0.002 | 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".