Altered Regional Cerebral Blood Flow in Idiopathic Hypersomnia
Bibliographic record
Abstract
Study Objectives: Idiopathic hypersomnia is characterized by excessive daytime sleepiness, despite normal or long sleep time. Its pathophysiological mechanisms remain unclear. This pilot study aims at characterizing the neural correlates of idiopathic hypersomnia using single photon emission computed tomography. Methods: Thirteen participants with idiopathic hypersomnia and 16 healthy controls were scanned during resting wakefulness using a high-resolution single photon emission computed tomography scanner with 99mTc-ethyl cysteinate dimer to assess cerebral blood flow. The main analysis compared regional cerebral blood flow distribution between the two groups. Exploratory correlations between regional cerebral blood flow and clinical characteristics evaluated the functional correlates of those brain perfusion patterns. Significance was set at p < .05 after correction for multiple comparisons. Results: Participants with idiopathic hypersomnia showed regional cerebral blood flow decreases in medial prefrontal cortex and posterior cingulate cortex and putamen, as well as increases in amygdala and temporo-occipital cortices. Lower regional cerebral blood flow in the medial prefrontal cortex was associated with higher daytime sleepiness. Conclusions: These preliminary findings suggest that idiopathic hypersomnia is characterized by functional alterations in brain areas involved in the modulation of vigilance states, which may contribute to the daytime symptoms of this condition. The distribution of regional cerebral blood flow changes was reminiscent of the patterns associated with normal non-rapid-eye-movement sleep, suggesting the possible presence of incomplete sleep-wake transitions. These abnormalities were strikingly distinct from those induced by acute sleep deprivation, suggesting that the patterns seen here might reflect a trait associated with idiopathic hypersomnia rather than a non-specific state of sleepiness.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".