Inhibition of androgenic pathway impairs encoding of cerebellar‐dependent motor learning in male rats
Bibliographic record
Abstract
Cerebellar-dependent learning is essential for the adaptation of motor and no motor behaviors to changing contexts, and neuroactive steroids-mainly referred to as estrogens-may regulate this process. However, the role of androgens in this process has not been established, although they may affect cerebellar physiology. Thus, this study aims to determine whether the activation of androgenic neural pathways may take part in controlling the vestibuloocular (VOR) and optokinetic reflexes (OKR), which depend on a defined cerebellar circuitry. To answer this question, we acutely blocked the activation of androgen receptors (Ars) using systemic administration of the Ars antagonist flutamide (FLUT; 20 mg/Kg) in peripubertal male rats. Then, we evaluated the FLUT effect on general oculomotor performance in the VOR and OKR as well as VOR adaptive gain increases and decreases. We used a paradigm causing fast VOR adaptation that combined in phase/out phase visuo-vestibular stimulations. We found that FLUT impaired the gain increase and decrease in VOR adaptation. However, FLUT altered neither acute nor overtime basal ocular-motor performance in the VOR or OKR. These findings indicate that the activation of androgenic neural pathways participates in phenomena leading to fast VOR adaptation, probably through the modulation of plasticity mechanisms that underlie adaptation of this reflex. Conversely, androgens may not be essential for neural information processing demands in basal ocular-motor reflexes. Moreover, our results suggest that androgens, possibly testosterone and dihydrotestosterone, could rapidly regulate motor memory encoding in the VOR adaptation, acting at both cerebellar and extracerebellar plasticity sites.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 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 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".