Habituation as an adaptive shift in response strategy mediated by neuropeptides
Bibliographic record
Abstract
Abstract Habituation is a non-associative form of learning characterized by a decremented response to repeated stimulation. It is typically framed as a process of selective attention, allowing animals to ignore irrelevant stimuli in order to free up limited cognitive resources. However, habituation can also occur to threatening and toxic stimuli, suggesting that habituation may serve other functions. Here we took advantage of a high-throughput Caenorhabditis elegans learning assay to investigate habituation to noxious stimuli. Using real-time computer vision software for automated behavioral tracking and optogenetics for controlled activation of a polymodal nociceptor, ASH, we found that neuropeptides mediated habituation and performed an RNAi screen to identify candidate receptors. Through subsequent mutant analysis and cell-type-specific gene expression, we found that pigment-dispersing factor (PDF) neuropeptides function redundantly to promote habituation via PDFR-1-mediated cAMP signaling in both neurons and muscles. Behavioral analysis during learning acquisition suggests that response habituation and sensitization of locomotion are parts of a shifting behavioral strategy orchestrated by pigment dispersing factor signaling to promote dispersal away from repeated aversive stimuli.
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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 | 0.001 |
| 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".