Morning and Evening-Type Differences in Slow Waves during NREM Sleep Reveal Both Trait and State-Dependent Phenotypes
Bibliographic record
Abstract
Brain recovery after prolonged wakefulness is characterized by increased density, amplitude and slope of slow waves (SW, <4 Hz) during non-rapid eye movement (NREM) sleep. These SW comprise a negative phase, during which cortical neurons are mostly silent, and a positive phase, in which most neurons fire intensively. Previous work showed, using EEG spectral analysis as an index of cortical synchrony, that Morning-types (M-types) present faster dynamics of sleep pressure than Evening-types (E-types). We thus hypothesized that single SW properties will also show larger changes in M-types than in E-types in response to increased sleep pressure. SW density (number per minute) and characteristics (amplitude, slope between negative and positive peaks, frequency and duration of negative and positive phases) were compared between chronotypes for a baseline sleep episode (BL) and for recovery sleep (REC) after two nights of sleep fragmentation. While SW density did not differ between chronotypes, M-types showed higher SW amplitude and steeper slope than E-types, especially during REC. SW properties were also averaged for 3 NREM sleep periods selected for their decreasing level of sleep pressure (first cycle of REC [REC1], first cycle of BL [BL1] and fourth cycle of BL [BL4]). Slope was significantly steeper in M-types than in E-types in REC1 and BL1. SW frequency was consistently higher and duration of positive and negative phases constantly shorter in M-types than in E-types. Our data reveal that specific properties of cortical synchrony during sleep differ between M-types and E-types, although chronotypes show a similar capacity to generate SW. These differences may involve 1) stable trait characteristics independent of sleep pressure (i.e., frequency and durations) likely linked to the length of silent and burst-firing phases of individual neurons, and 2) specific responses to increased sleep pressure (i.e., slope and amplitude) expected to depend on the synchrony between neurons.
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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 | 0.000 |
| 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".