Olfactory learning in the rat pup: A model that may permit visualization of a mammalian memory trace
Bibliographic record
Abstract
Over the past 10 years considerable insight into intracellular interactions leading to long-term memory formation have been gleaned from various neural circuits within invertebrate and vertebrate species. This review suggests that, while certain intracellular signaling pathways are commonly involved across species, it is important to analyze specific neural systems because critical differences among systems appear to exist. The olfactory bulb has been used by our group to estimate the influence of neuromodulatory systems (serotonin and norepinephrine) on intracellular processes leading to learning. We describe here how activation of noradrenergic input to mitral cells increases cAMP leading to CREB phosphorylation when paired with a conditioning stimulus, odor. CREB phosphorylation is causal in odor preference learning leading to long-term memory for the odor. However, the relationship between cAMP activation and CREB phosphorylation is not straight forward; overstimulation of cAMP pathways impedes learning and prevents CREB phosphorylation. Excessive CREB phosphorylation also interferes with learning.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".