Oiling the gears of memory: quercetin exposure during memory formation, consolidation, and recall enhances memory in <i>Lymnaea stagnalis</i>
Bibliographic record
Abstract
Abstract Memory formation (short-term, intermediate-term, and long-term) is an integral process of cognition which allows individuals to retain important information and is influenced by various intrinsic and extrinsic factors. A major extrinsic factor influencing cognition across taxa is diet, which may contain rich sources of molecular agents with antioxidant, anti-inflammatory, and memory enhancing properties that potentially enhance cognitive ability. A common and abundant flavonoid present in numerous food substances is quercetin (Q) which is also known to upregulate cyclic AMP response element binding protein (CREB) in several animals including our model system Lymnaea stagnalis . Since CREB is known to be involved in long term memory (LTM) formation, we investigated the role of Q-exposure on memory formation, consolidation, and recall during operant conditioning of aerial respiratory behaviour in Lymnaea . Snails were exposed to Q 3h before or after training to ascertain its effects on LTM. Additionally, we investigated the effect of the combined presentation of a single reinforcing stimulus (at 24h post-training or 24h before training) and Q-exposure on both LTM formation and reconsolidation. Our data indicate that Q-exposure acts on the different phases of memory formation, consolidation, and recall leading to enhanced LTM formation. Summary Statement Quercetin enhances long-term memory formation acting on the different phases of memory formation, consolidation, and recall.
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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".