0739 GRAY MATTER ABNORMALITIES IN SLEEP WALKING
Bibliographic record
Abstract
Non-rapid eye movement (NREM) parasomnias are characterized by recurrent complex behaviors that occures during arousals from slow-wave sleep with an altered state of consciousness. The pathophysiology of NREM parasomnias are not fully understood. This study aimed to determine whether voxel-based analysis of T1 weighted MRI and diffusion tensor imaging can detect alterations of gray and white matter morphometry as well as measures of mean diffusivity and fractional anisotropy in patients with non-rapid eye movement parasomnia. Fourteen patients (age: 29 ± 4.2; disease duration 19.2 ± 7.7) with current NREM parasomnias, were recruited consecutively from referrals or follow-up visits at the Sleep Disorders Clinic at the Department of Neurology at the Medical University of Innsbruck, Austria. Diagnosis was confirmed polysomnographically. All patients underwent 3 Tesla MRI and were compared to 14 healthy subjects, matched for age and gender. Statistical parametric mapping was applied to objectively identify focal changes of MRI parameters throughout the entire brain volume. Statistical parametric mapping localized significant decreases of gray matter volume in the left dorsal posterior cingulate cortex (Brodmann area 23) and posterior midcingulate cortex (Brodmann area 24) in patients with non rapid eye movement parasomnias compared to the control group (p<0.001, corrected for multiple comparisons). No significant differences of mean diffusivity and fractional anisotropy measures were found between the non-rapid eye movement parasomnia group and the healthy control group. In the present study we identified significant gray matter volume loss of the left dorsal posterior cingulate cortex (BA 23) and posterior midcingulate cortex (BA 24) in patients with NREM parasomnias. Recently, the simultaneous co-existence of arousal or wakefulness originating from the motor and cingulate cortices and persistent sleep in associative cortical regions was suggested as a functional framework of sleepwalking. Gray matter volume decline in the dorsal posterior and posterior midcingulate cortex reported in this study might represent the neuroanatomical substrate for this condition. no support.
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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) | 0.005 | 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".