Low acetylcholine during early sleep is important for motor memory consolidation
Bibliographic record
Abstract
Abstract The synaptic homeostasis theory of sleep proposes that low neurotransmitter activity in sleep is optimal for memory consolidation. We tested this theory by asking whether increasing acetylcholine levels during early sleep would disrupt motor memory consolidation. We trained separate groups of adult mice on the rotarod walking and skilled reaching for food tasks, and after training, administered physostigmine, an acetylcholinesterase inhibitor, to increase cholinergic tone in subsequent sleep. Post-sleep testing suggested that physostigmine impaired motor skill acquisition. Home-cage video monitoring and electrophysiology revealed that physostigmine disrupted sleep structure, delayed non-rapid-eye-movement sleep onset, and reduced slow-wave power in the hippocampus and cortex. The impaired motor performance with physostigmine, however, was not solely due to its effects on sleep structure, as one hour of sleep deprivation after training did not impair rotarod performance. A reduction in cholinergic tone by inactivation of cholinergic neurons during early sleep also affected rotarod performance. Administration of agonists and antagonists of muscarinic and nicotinic acetylcholine receptors revealed that activation of muscarinic receptors during early sleep impaired rotarod performance. The experiments suggest that the increased slow wave activity and inactivation of muscarinic receptors during early sleep due to reduced acetylcholine contribute to motor memory consolidation.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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".