Chronic administration of clozapine alleviates reversal-learning impairment in isolation-reared rats
Bibliographic record
Abstract
Isolation rearing has been used for inducing schizophrenia-like symptoms in rats. Human schizophrenics have deficits in prefrontal-dysfunction-related cognitive/behavioral flexibility. Rats with lesions of the medial prefrontal cortex perform poorly in reversal learning. It is uncertain whether isolation rearing, however, causes reversal-learning impairment in adult rats. Using the rotating T maze, this study examined the effect of chronic administration of clozapine on visual discrimination learning and reversal learning in isolation-reared and socially reared adult rats. The results show that isolation-reared rats without clozapine injection performed significantly worse than socially reared rats in reversal learning but not in acquisition learning. Chronic injection of clozapine (5 or 10 mg/kg) in isolation-reared rats significantly improved reversal learning but had no effects on acquisition learning. Further data analyses show that in both the inhibition phase and the new-strategy-acquisition phase of reversal learning, isolation-reared rats needed significantly more correct-response trials to reach the criterion than socially reared rats, and clozapine significantly reduced the isolation-induced impairment of reversal learning only in the new-strategy-acquisition phase. In socially reared rats, clozapine had a dose-related interfering effect on reversal learning but not acquisition learning. This study supports the use of isolation rearing as a model for investigating the neurodevelopmental hypothesis of schizophrenia.
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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 | 0.000 |
| Bibliometrics | 0.001 | 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".