The dopamine D1 receptor agonist SKF81297 has dose-related effects on locomotor activity but is without effect in a CER trace conditioning procedure conducted with two versus four trials
Bibliographic record
Abstract
In an appetitively motivated procedure, we have previously reported that systemic treatment with the dopamine (DA) D1 receptor agonist SKF81297 (0.4 and 0.8 mg/kg) depressed acquisition at a 2 s inter-stimulus-interval (ISI), suitable to detect trace conditioning impairment. However since DA is involved in reinforcement processes, the generality of effects across appetitively- and aversively-motivated trace conditioning procedures cannot be assumed. The present study tested the effects of SKF81297 (0.4 and 0.8 mg/kg) in an established conditioned emotional response (CER) procedure. Trace-dependent conditioning was clearly shown in two experiments: while conditioning was relatively strong at a 3-s ISI, it was attenuated at a 30-s ISI. This was shown after two (Experiment 1) or four (Experiment 2) conditioning trials conducted in - as far as possible - the same CER procedure. Contrary to prediction, in neither experiment was there any indication that trace conditioning was attenuated by treatment with 0.4 or 0.8 mg/kg SKF81297. In the same rats, locomotor activity was significantly enhanced at the 0.8 mg/kg dose of SKF81297. These results suggest that procedural details of the trace conditioning variant in use are an important determinant of the profile of dopaminergic modulation.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".