Sex hormones play a role in vulnerability to sleep loss on emotion processing tasks
Bibliographic record
Abstract
The central aim of this study was to investigate hormones as a predictor of individual vulnerability or resiliency on emotion processing tasks following one night of sleep restriction. The restriction group was instructed to sleep 3 a.m.-7 a.m. (13 men, 13 women in follicular phase, 10 women in luteal phase of menstrual cycle), and a control group slept 11 p.m.-7 a.m. (12 men, 12 follicular women, 12 luteal women). Sleep from home was verified with actigraphy. Saliva samples were collected on the evening prior to restriction, and in the morning and afternoon following restriction, to measure testosterone, estradiol, and progesterone. In the laboratory, event-related potentials (ERPs) were recorded during presentation of images and faces to index neural processing of emotional stimuli. Compared to controls, sleep-restricted participants had a larger amplitude Late Positive Potential (LPP) ERP to positive vs neutral images, reflecting greater motivated attention towards positive stimuli. Sleep-restricted participants were also less accurate categorizing sad faces and exhibited a larger N170 to sad faces, reflecting greater neural reactivity. Sleep-restricted luteal women were less accurate categorizing all images compared to control luteal women, and progesterone was related to several outcomes. Morning testosterone in men was lower in the sleep-restricted group compared to controls; lower testosterone was associated with lower accuracy to positive images, a greater difference between positive vs neutral LPP amplitude, and lower accuracy to sad and fearful faces. In summary, women higher in progesterone and men lower in testosterone were more vulnerable to the effects of sleep restriction on emotion processing tasks. This study highlights a role for sex and sex hormones in understanding individual differences in vulnerability to sleep loss.
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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) | 0.001 | 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".