Neuronal properties, network operations and behavioral signs during sleep states and wakefulness
Bibliographic record
Abstract
The popular view that behavioral quiescence is the predominant sign of sleep may be valid for the full-blown state of resting sleep, but not for the preparatory period during which many animal species display complex motor behaviors directed at finding a home for sleep. However, this aspect of behavioral immobility alone cannot differentiate sleep from wakefulness since humans and other mammals are motionless at increasing levels of vigilance, especially during expectancy and hunting conditions associated with characteristic bioelectrical rhythms. The defining signs of the period when one falls asleep are peculiar changes in brain electrical activity (electroencephalogram, EEG) produced by network operations in the thalamus and cerebral cortex. These changes are the cause, rather than the reflection, of a quiescent behavioral condition. Indeed, the brain oscillations that define the transition from wakefulness to sleep are associated with long periods of inhibition in thalamocortical cells, with the consequence that the incoming messages are blocked and the cerebral cortex is deprived of information from the outside world. Following the appearance of these initial signs, other oscillatory types mark the late stage of resting sleep and they further deepen the unresponsiveness of thalamic and cortical neurons, disconnecting the brain from the external world. In this chapter, I discuss the neuronal properties and network mechanisms underlying the behavioral and bioelectrical signs of waking and two major sleep stages: sleep with high-amplitude, synchronized slow waves (SWS), and sleep with rapid eye movements (REM sleep).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".