Effects of nicotinic cholinergic system manipulations on paired-associate learning (PAL) in mice
Bibliographic record
Abstract
Rationale: The ability to perform on the Cambridge Neuropsychological Test Automated Battery touchscreen paired-associate learning (PAL) test is predictive of Alzheimer’s disease and Mild Cognitive Impairment. Recently, an automated computer touchscreen PAL task for mice has been developed. Pharmacological validation of this task is warranted to establish it as a useful tool in future drug discovery pertaining to Alzheimer’s disease and Mild Cognitive Impairment. Objectives: This investigation provides a systematic analysis of nicotinic involvement within the PAL task for mice. Particularly, the effects of systemic administration of nicotinic cholinergic agents (agonist and antagonist) on PAL task performance in C57BL/6 mice were investigated. This was done to detect whether bidirectional modification of performance is consequent upon these manipulations. Methods: Upon acquiring the PAL task, nicotine (nicotinic receptor agonist; 0.1, 0.5, and 1.0 mg/kg) and mecamylamine (nicotinic receptor antagonist; 0.3, 1.0, and 3.0 mg/kg) were administered intraperitoneally to the mice in a within-subjects design, prior to daily sessions in the PAL task. Results: Nicotine did not have any significant effect on PAL performance improvement at any doses. However, mecamylamine did increase perseverative responding and reaction time in the mice. Such impairment effects are interpreted as being attentional in nature. Conclusion: This investigation indicates that mice indeed acquire the rodent PAL task, deeming it a valuable tool for future drug discovery. Further, the nicotinic cholinergic system appears to be implicated in PAL task performance, with greater effects seen with deactivation rather than activation of the system, and with these effects appearing to be of an attentional nature. Keywords: paired-associate learning (PAL); Alzheimer’s disease; nicotinic cholingeric system; touchscreen
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".