The effect of rearing environment on memory formation
Bibliographic record
Abstract
Lymnaea stagnalis is a well-studied model system for determining how changes in the environment influence associative learning and memory formation. For example, some wild strains of Lymnaea, collected from separate geographic locations show superior memory-forming abilities compared to others. Here, we have studied memory formation in two laboratory-bred Lymnaea strains, derived from the same original population in The Netherlands. The two strains were reared in two different laboratories at the University of Calgary (C-strain) and at Brock University (B-strain) for many years and were found to differ in their memory-forming ability. Specifically, the C-strain required only two training sessions to form long-term memory (LTM) whereas the B-strain required four sessions to form LTM. Additionally, the LTM formed by the B-strain persisted for a shorter amount of time than the memory formed by the C-strain. Thus, despite being derived from the same original population, the C- and B-strains have developed different memory-forming abilities. Next, we raised the two strains from embryos ‘Away’ from home (i.e. in the other laboratory) over two generations and assessed their memory-forming abilities. The B-strain reared and maintained at the University of Calgary demonstrated improved memory-forming ability within a single generation, while the C-strain reared at Brock University retained their normal LTM forming ability across two subsequent generations. This suggests that local environmental factors may contribute to the behavioural divergence observed between these two laboratory-bred strains.
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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 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".