From likes to dislikes: conditioned taste aversion in the great pond snail (<i>Lymnaea</i><i>stagnalis</i>)
Bibliographic record
Abstract
The neural circuitry comprising the central pattern generator (CPG) that drives feeding behavior in the great pond snail (Lymnaea stagnalis (L., 1758)) has been worked out. Because the feeding behavior undergoes associative learning and long-term memory (LTM) formation, it provides an excellent opportunity to study the causal neuronal mechanisms of these two processes. In this review, we explore some of the possible causal neuronal mechanisms of associative learning of conditioned taste aversion (CTA) and its subsequent consolidation processes into LTM in L. stagnalis. In the CTA training procedure, a sucrose solution, which evokes a feeding response, is used as the conditioned stimulus (CS) and a potassium chloride solution, which causes a withdrawal response, is used as the unconditioned stimulus (US). The pairing of the CS–US alters both the feeding response of the snail and the function of a pair of higher order interneurons in the cerebral ganglia. Following the acquisition of CTA, the polysynaptic inhibitory synaptic input from the higher order interneurons onto the feeding CPG neurons is enhanced, resulting in suppression of the feeding response. These changes in synaptic efficacy are thought to constitute a “memory trace” for CTA in L. stagnalis.
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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".