Cerebral Asymmetry in Insomnia Sufferers
Bibliographic record
Abstract
Cerebral asymmetry is used to describe the differences in electroencephalographic activity between regions of the brain. The objective of this study was to document frontal, central, and parietal asymmetry in psychophysiological (Psy-I) and paradoxical (Para-I) insomnia sufferers as well as good sleeper (GS) controls, and to compare their patterns of asymmetry to others already found in anxiety and depression. Additionally, asymmetry variations between nights were assessed. Participants were 17 Psy-I, 14 Para-I, and 19 GS (mean age = 40 years, SD = 9.4). They completed three nights of polysomnography (PSG) recordings following a clinical evaluation in a sleep laboratory. All sleep cycles of Nights 2 and 3 were retained for power spectral analysis. The absolute activity in frequency bands (0.00-125.00 Hz) was computed at multiple frontal, central, and parietal sites in rapid eye movement and non-rapid eye movement sleep to provide cerebral asymmetry measures. Mixed model ANOVAs were computed to assess differences between groups and nights. Correlations were performed with asymmetry and symptoms of depression and anxiety from self-reported questionnaires. Over the course of the two nights, Para-I tended to present hypoactivation of their left frontal region but hyperactivation of their right one compared with GS. As for Psy-I, they presented increased activation of their right parietal region compared with Para-I. Asymmetry at frontal, central, and parietal region differed between nights. On a more disrupted night of sleep, Psy-I had increased activity in their right parietal region while Para-I presented a decrease in cerebral activity in the right central region on their less disrupted night of sleep. Anxious and depressive symptoms did not correlate with asymmetry at any region. Therefore, Psy-I and Para-I present unique patterns of cerebral asymmetry that do not relate to depression or anxiety, and asymmetry varies between nights, maybe as a consequence of variability in objective sleep quality from night to night.
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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 | 0.001 |
| 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) | 0.002 | 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".