Spatio-temporal properties of sleep slow waves and implications for development
Bibliographic record
Abstract
Objective sleep quality can be measured by electroencephalography (EEG), a non-invasive technique to quantify electrical activity generated by the brain. With EEG, sleep depth is measured by appearance and an increase in slow wave activity (scalp-SWA). EEG slow waves (scalp-SW) are the manifestation of underlying synchronous membrane potential transitions between silent (DOWN) and active (UP) states. This bistable periodic rhythm is defined as slow oscillation (SO). During its "silent state" cortical neurons are hyperpolarized and appear inactive, while during its "active state" cortical neurons are depolarized, fire spikes and exhibit continuous synaptic activity, excitatory and inhibitory. In adults, data from high-density EEG revealed that scalp-SW propagate across the cortical mantle in complex patterns. However, scalp-SW propagation undergoes modifications across development. We present novel data from children, indicating that scalp-SW originate centro-parietally, and emerge more frontally by adolescence. Based on the concept that SO and SW could actively modify neuronal connectivity, we discuss whether they fulfill a key purpose in brain development by actively conveying modifications of the maturing brain.
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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 | 0.001 |
| 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) | 0.001 | 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".