Altered brain perfusion patterns in wakefulness and slow-wave sleep in sleepwalkers
Bibliographic record
Abstract
Study Objectives: The present study assessed brain perfusion patterns with single-photon emission computed tomography (SPECT) during sleepwalkers' post-sleep deprivation slow-wave sleep (SWS) and resting-state wakefulness. Methods: Following a 24 hr period of sleep deprivation, 10 sleepwalkers and 10 sex- and age-matched controls were scanned with a high-resolution SPECT scanner. Participants were injected with 99mTc-ethylene cysteinate dimer after 2 min of stable SWS within their first sleep cycle as well as during resting-state wakefulness, both after a subsequent 24 hr period of sleep deprivation. Results: When compared with controls' brain perfusion patterns during both SWS and resting-state wakefulness, sleepwalkers showed reduced regional cerebral perfusion in several bilateral frontal regions, including the superior frontal, middle frontal, and medial frontal gyri. Moreover, reduced regional cerebral perfusion was also found in sleepwalkers' left postcentral gyrus, insula, and superior temporal gyrus during SWS compared with controls. During resting-state wakefulness compared with controls, reduced cerebral perfusion was also found in parietal and temporal regions of sleepwalkers' left hemisphere, whereas the right parahippocampal gyrus showed increased regional cerebral perfusion. Conclusions: Our results reveal patterns of reduced regional cerebral perfusion in sleepwalkers' frontal and parietal areas when compared with controls, regions previously associated with SWS generation and episode occurrence. Additionally, reduced perfusion in the dorsolateral prefrontal cortex and insula during recovery SWS is consistent with the clinical features of somnambulistic episodes, including impaired awareness and reduced pain perception. Altered regional cerebral perfusion patterns during sleepwalkers' resting-state wakefulness may be related to daytime functional anomalies in this population.
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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) | 0.002 | 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".