Effect of amphetamine dose on wheel-running functioning as reinforcement or operant behavior on a multiple schedule of reinforcement
Bibliographic record
Abstract
Does the effect of amphetamine on behavior (wheel running) differ depending on the functional role (operant, reinforcement) of that behavior? This study addressed this question using a multiple schedule of reinforcement in which wheel running served as reinforcement for lever pressing in one component and as operant behavior for sucrose reinforcement in the other component. Seven female Long-Evans rats were exposed to a multiple schedule in which pressing a lever on a variable ratio 10 schedule produced the opportunity to run for 15 revolutions in one component and running 15 revolutions produced a drop of 15% sucrose solution in the other component. Doses of 0.5, 1.0, and 2.0 mg/kg D-amphetamine were administered by intraperitoneal injection 20 min prior to a session. As amphetamine dose increased, wheel running decreased in both components - showing no evidence that the effect of the drug on wheel running depended on the function of wheel activity. Notably, lever pressing for wheel-running reinforcement also decreased with amphetamine dose. Drug dose increased the initiation of operant lever pressing, but not the initiation of operant wheel running. We propose that amphetamine dose had common effects on wheel running regardless of its function (reinforcement vs. operant) because wheel-running generates automatic reinforcement and the automatic-reinforcement value of wheel activity is modulated by drug dose.
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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".