The forebrain dynamic and electrophysiological mark of sleep onset process
Bibliographic record
Abstract
As the body transitions from wakefulness to sleep, the electroencephalogram (EEG) shows major changes.Yet, specific markers precisely determining this transition during the sleep onset process (SOP) are still missing.This study proposes a novel definition of the SOP based on the dynamics of the head-direction (HD) system in mice.The HD system is a circuit involved in the navigation system of the mammalian brain, with the anterior dorsal nucleus of the thalamus being a central hub of this circuit.During sleep, HD cells fire coherently relative to wake but code for a randomly drifting direction.We make the hypothesis that the exact moment when the HD cell population stops coding for the animal's actual direction is a marker of the SOP.By linking these changes in dynamics with electromyogram (EMG) and neuronal dynamics in the hippocampus, a brain structure showing some of the largest changes in neuronal dynamics between wakefulness and sleep, this study reveals the progressive coupling between the HD system and other cortical systems while animals fall asleep.This new vision of the SOP provides a deeper and more comprehensive understanding of the physiological and cognitive processes that occur during sleep onset in mammals.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".