The Effect of Obstructive Sleep Apnea on Sleep-dependent Emotional Memory Consolidation
Bibliographic record
Abstract
Abstract Rationale A growing body of evidence suggests that sleep is critical for the adaptive processing and consolidation of emotional information into long-term memory. Previous research has indicated that emotional components of scenes particularly benefit from sleep in healthy groups, yet sleep-dependent emotional memory processes remain unexplored in clinical cohorts, including those with obstructive sleep apnea (OSA). This line of research is important as it will add to the understanding of how disrupted sleep in OSA contributes to both impaired cognition and emotion dysregulation. Objectives To test the hypothesis that individuals with OSA will have impaired sleep-dependent memory consolidation, with the greatest impact being on memory for emotional content. Methods In this study, a group of newly diagnosed patients with OSA (n = 26; 10 female; average age, 42.5 years) and a matched group of healthy control subjects (n = 24; 13 female; average age, 37 years) were enrolled in the study at Beth Israel Deaconess Medical Center. Participants encoded scenes with negative or neutral foreground objects placed on neutral backgrounds before a night of polysomnographically recorded sleep. In the morning, they completed a recognition test in which old and new scene objects and backgrounds, presented separately and one at a time, were judged as old, new, or similar compared with what had been previously viewed. Results Patients with OSA had a deficit in recognition memory for the scenes. Overall recognition (the ability to recognize old items as either old or similar) was impaired across all scene elements, both negative and neutral objects and backgrounds, whereas specific recognition (correctly identifying old items as old) was impaired only for negative objects. Across all participants, successful overall recognition correlated positively with sleep efficiency and rapid eye movement (REM) sleep, whereas successful specific memory recognition correlated only with REM sleep. Conclusions Our findings indicate that fragmented sleep and reduced REM sleep, both hallmarks of OSA, are associated with disruptions in general memory impairment and veridical memory for emotional content, which could alter emotional regulation and contribute to comorbid emotional distress in OSA.
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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 | 0.000 | 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".