Two Forms of Learning following Training to a Single Odorant in Caenorhabditis elegans AWC Neurons
Bibliographic record
Abstract
The nematode Caenorhabditis elegans can adapt to both the AWC-sensed odorants benzaldehyde (Bnz) and isoamyl alcohol (IsoA) and can reciprocally cross-adapt. Yet we reveal that these four adaptation scenarios actually represent two distinct forms of learning: nonassociative habituation and associative learning by pairing with a starvation unconditioned stimulus. Training to the single odorant IsoA leads to both associative and nonassociative memory traces, which can be preferentially accessed by either a Bnz or IsoA retrieval stimulus, respectively. This represents the first demonstration in which the form of learning displayed after training to a single stimulus is a function of the retrieval stimulus used. Furthermore, these two forms of learning can be genetically double dissociated despite both forms occurring within the AWC primary sensory neuron. We find that associative learning requires the cGMP-dependent kinase egl-4 and insulin signaling, which acts downstream of egl-4. In contrast, nonassociative learning requires neither of these genes, but does require the TRPV channel osm-9, which is dispensable for associative learning. In addition, we find that the arrestin arr-1 is promiscuous between associative and nonassociative learning in mediating the adaptive response to the IsoA retrieval stimulus, suggesting that distinct forms of memory may nonetheless use common downstream effectors.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".