Inverse Relationship between Basal Pacemaker Neuron Activity and Aversive Long-Term Memory Formation in Lymnaea stagnalis
Bibliographic record
Abstract
Learning and memory formation are essential physiological functions. While quiescent neurons have long been the focus of investigations into the mechanisms of memory formation, there is increasing evidence that spontaneously active neurons also play key roles in this process and possess distinct rules of activity-dependent plasticity. In this study, we used a well-defined aversive learning model of aerial respiration in the mollusc Lymnaea stagnalis (L. stagnalis) to study the role of basal firing activity of the respiratory pacemaker neuron Right Pedal Dorsal 1 (RPeD1) as a determinant of aversive long-term memory (LTM) formation. We investigated the relationship between basal aerial respiration behaviour and RPeD1 firing activity, and examined aversive LTM formation and neuronal plasticity in animals exhibiting different basal aerial respiration behaviour. We report that animals with higher basal aerial respiration behaviour exhibited early responses to operant conditioning and better aversive LTM formation. Early behavioural response to the conditioning procedure was associated with biphasic enhancements in the membrane potential, spontaneous firing activity and gain of firing response, with an early phase spanning the first two hours after conditioning and a late phase that is observed at 24 hours. Taken together, we provide the first evidence suggesting that lower neuronal activity at the time of learning may be correlated with better memory formation in spontaneously active neurons. Our findings provide new insights into the diversity of cellular rules of plasticity underlying memory 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) | 0.000 | 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".