0738 EFFECTS OF SLEEP DEPRIVATION ON BRAIN PERFUSION PATTERNS IN SLEEPWALKERS’ WAKEFULNESS AND SLOW WAVE SLEEP
Bibliographic record
Abstract
Several EEG-based studies have documented anomalies in the slow wave sleep (SWS) of adult sleepwalkers. Moreover, previous imaging studies have identified specific brain perfusion patterns in sleepwalkers during post sleep deprivation wakefulness as well as during a somnambulistic episode. However, neuroimaging has yet to be used to investigate sleepwalkers’ SWS. The present study measured regional cerebral blood flow (rCBF) with single photon emission computed tomography (SPECT) during sleepwalkers’ post sleep deprivation SWS and resting-state wakefulness. Following 24 hr period of sleep deprivation, 10 sleepwalkers (7F, 3M; mean age: 28.2 ± 6.9 years) and 10 sex and age-matched controls were injected with a unidose of 99mTc-ECD after 2 minutes of stable SWS within their first sleep cycle as well as during resting-state wakefulness. Participants were scanned after each injection with a high-resolution SPECT. Between group differences in rCBF were assessed using two-sample t-tests separately for SWS and wakefulness. Significance was set at p<0.005 at the voxel level uncorrected for multiple comparisons combined with >100 contiguous voxels by cluster. When compared to controls’ rCBF observed during SWS and resting-state wakefulness, sleepwalkers showed significant decreases in several bilateral frontal regions, including the superior frontal, middle frontal and medial frontal gyri. Most of these regions are included in the dorsolateral prefrontal cortex (DLPFC). During SWS, decreased rCBF was also found in sleepwalkers’ left postcentral gyrus, insula and superior temporal gyrus. During waking resting-state, decreased rCBF was also found in parietal and temporal regions of sleepwalkers’ left hemisphere. This study was the first to use neuroimaging to investigate sleepwalkers’ SWS. Decreased rCBF was found in sleepwalkers’ DLPFC and insula, two regions involved in consciousness and in the generation of slow wave activity. The data also reveal altered rCBF patterns during sleepwalkers’ resting-state wakefulness. These findings suggest that prefrontal and insular regions may be implicated in the pathophysiology of sleepwalking. This research was supported by a research grant from the Canadian Institutes of Health Research (CIHR).
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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".