How the Human Brain Sleeps: Direct Cortical Recordings of Normal Brain Activity
Bibliographic record
Abstract
OBJECTIVE: Regional variations in oscillatory activity during human sleep remain unknown. Using the unique ability of intracranial electroencephalography to study in situ brain physiology, this study assesses regional variations of electroencephalographic sleep activity and creates the first atlas of human sleep using recordings from the first sleep cycle. METHODS: Intracerebral electroencephalographic recordings with channels displaying physiological activity from nonlesional tissue were selected from 91 patients of 3 tertiary epilepsy centers. Sections during non-rapid eye movement sleep (stages N2 and N3) and rapid eye movement sleep (stage R) were selected from the first sleep cycle for oscillatory and nonoscillatory signal analysis. Results of 1,468 channels were grouped into 38 regions covering all cortical areas. RESULTS: We found regional differences in the distribution of sleep transients and spectral content during all sleep stages. There was a caudorostral gradient, with more slow frequencies and fewer spindles in temporoparieto-occipital than in frontal cortex. Moreover, deep-seated structures showed spectral peaks differing from the baseline electroencephalogram. The regions with >60% of channels presenting significant rhythmic activity were either mesial or temporal basal structures that contribute minimally to the scalp electroencephalogram. Finally, during deeper sleep stages, electroencephalographic analysis revealed a more homogeneous spatial distribution, with increased coupling between high and low frequencies. INTERPRETATION: This study provides a better understanding of the regional variability of sleep, and establishes a baseline for human sleep in all cortical regions during the first sleep cycle. Furthermore, the open-access atlas will be a unique resource for research (https://mni-open-ieegatlas. RESEARCH: mcgill.ca). ANN NEUROL 2020;87:289-301.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".