The attribution of incentive salience to Pavlovian alcohol cues: a shift from goal-tracking to sign-tracking
Bibliographic record
Abstract
Environmental stimuli that are reliably paired with alcohol may acquire incentive salience, a property that can operate in the use and abuse of alcohol. Here we investigated the incentive salience of Pavlovian alcohol cues using a preclinical animal model. Male, Long-Evans rats (Harlan) with unrestricted access to food and water were acclimated to drinking 15% ethanol (v/v) in their home-cages. Rats then received Pavlovian autoshaping training in which the 10 s presentation of a retractable lever served as the conditioned stimulus (CS) and 15% ethanol served as the unconditioned stimulus (US) (0.2 ml/CS; 12 CS presentations/session; 27 sessions). Next, in an operant test of conditioned reinforcement, nose pokes into an active aperture delivered presentations of the lever-CS, whereas nose pokes into an inactive aperture had no consequences. Across initial autoshaping sessions, goal-tracking behavior, as measured by entries into the fluid port where ethanol was delivered, developed rapidly. However, with extended training goal-tracking diminished, and sign-tracking responses, as measured by lever-CS activations, emerged. Control rats that received explicitly unpaired CS and US presentations did not show goal-tracking or sign-tracking responses. In the test for conditioned reinforcement, rats with CS-US pairings during autoshaping training made more active relative to inactive nose pokes, whereas rats in the unpaired control group did not. Moreover, active nose pokes were positively correlated with sign-tracking behavior during autoshaping. Extended training may produce a shift in the learned properties of Pavlovian alcohol cues, such that after initially predicting alcohol availability they acquire robust incentive salience.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".