Symmetrical Serotonin Release during Asymmetrical Slow-Wave Sleep: Implications for the Neurochemistry of Sleep–Waking States
Bibliographic record
Abstract
On land, fur seals predominately display bilaterally synchronized electroencephalogram (EEG) activity during slow-wave sleep (SWS), similar to that observed in all terrestrial mammals. In water, however, fur seals exhibit asymmetric slow-wave sleep (ASWS), resembling the unihemispheric slow-wave sleep of odontocetes (toothed whales). The unique sleeping pattern of fur seals allows us to distinguish neuronal mechanisms mediating EEG changes from those mediating behavioral quiescence. In a prior study we found that cortical acetylcholine release is lateralized during ASWS in the northern fur seal, with greater release in the hemisphere displaying low-voltage (waking) EEG activity, linking acetylcholine release to hemispheric EEG activation (Lapierre et al. 2007). In contrast to acetylcholine, we now report that cortical serotonin release is not lateralized during ASWS. Our data demonstrate that bilaterally symmetric levels of serotonin are compatible with interhemispheric EEG asymmetry in the fur seal. We also find greatly elevated levels during eating and hosing the animals with water, suggesting that serotonin is more closely linked to bilateral variables, such as axial motor and autonomic control, than to the lateralized cortical activation manifested in asymmetrical 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 | 0.000 | 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".