The paradox of Rapid Eye Movement sleep in the light of oscillatory activity and functional synchronization during phasic and tonic microstates
Bibliographic record
Abstract
Rapid Eye Movement (REM) sleep is a peculiar neural state showing a combination of muscle atonia and intense cortical activity. REM sleep is usually considered as a unitary state in neuroscientific research; however, it is composed of two different microstates: phasic and tonic REM. These differ in awakening thresholds, sensory processing, and cortical oscillations. Nevertheless, studies examining cortical oscillations during REM microstates are scarce, and used low spatial sampling. Here, we analyzed the data of 18 healthy individuals assessed by high-density sleep EEG recordings. We systematically contrasted phasic and tonic REM periods in terms of topographical distribution, source localization, as well as local, global and long-range synchronization of frequency-specific cortical activity. Tonic periods showed relatively increased high alpha and beta power over frontocentral derivations. In addition, higher frequency components of beta power exhibited increased global synchronization during tonic compared to phasic states. In contrast, in phasic periods we found increased power and synchronization of low frequency oscillations coexisting with increased and synchronized gamma activity. Source localization revealed several multimodal, higher-order associative, as well as sensorimotor areas as potential sources of increased high alpha/beta power during tonic compared to phasic REM. Increased gamma power in phasic REM was attributed to medial prefrontal and right lateralized temporal areas associated with emotional processing. Our findings emphasize the heterogeneous nature of REM sleep, expressed in two microstates with remarkably different neural activity. Considering the microarchitecture of REM sleep may provide new insights into the mechanisms of REM sleep in health and disease.
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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".