Effects of androgens on behavioural flexibility in male rats
Bibliographic record
Abstract
Behavioural flexibility, the ability to adapt behaviour in response to environmental changes, is regulated by the mesocorticolimbic system. In strategy set shifting, subjects initially learn to use one rule to receive a reward (e.g. select the lever denoted by a cue light, known as cue rule), but then must switch to a new rule (e.g. select the left/right lever, known as response rule). Treatment with androgens, such as testosterone, impairs set shifting. Moreover, we previously showed that decreasing androgens with an androgen synthesis inhibitor (abiraterone) facilitates behavioural flexibility (shift from cue rule to response rule). The effect size of abiraterone treatment, however, was small. To increase the effect size of abiraterone, we modified the set shifting task to be more difficult. Here, we manipulated the order of the shift, the minimum number of learning trials during the initial discrimination, and the presence of reminder trials immediately prior to the set shift. Rats were assigned to one of six different set shifting tasks, which required them to perform either the cue-response shift or response-cue shift with variable numbers of minimum learning trials and with or without reminder trials. Rats performing the response-cue shift made significantly more errors to criterion compared to rats performing the cue-response shift. There were no effects of minimum number of learning trials or reminder trials. Ongoing work will examine the effects of abiraterone on the two types of shift.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".