Configural learning: a higher form of learning in<i>Lymnaea</i>
Bibliographic record
Abstract
Events typically occur in a specific context and the ability to assign importance to this occurrence plays a significant role in memory formation and recall. When the scent of a crayfish predator (CE) is encountered in Lymnaea strains known to be predator-experienced (e.g. the W-strain), enhancement of memory formation and depression of feeding occurs, which are part of a suite of anti-predator behaviours. We hypothesized that Lymnaea possess a form of higher-order conditioning, namely configural learning. We tested this by simultaneously exposing W-strain Lymnaea to a carrot food-odour (CO) and predator scent (CE). Two hours later we operantly conditioned these snails with a single 0.5h training session in CO to determine whether training in CO results in long-term memory (LTM). In W-strain snails two 0.5h training sessions are required to cause LTM formation. A series of control experiments followed and demonstrated that only the CO+CE snails trained in CO had acquired enhanced memory forming ability. Additionally, following CE+CO pairing, CO no longer elicited an increased feeding response. Hence, snails have the ability to undergo configural learning. Following configural learning, CO becomes risk-signaling and evokes behavioural responses phenotypically similar to those elicited by exposure to CE.
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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 | 0.001 |
| 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".