Sex Differences in Electrical Activity During Sleep: A Synthesis of Brain Wave Data Across Human Life Stages
Bibliographic record
Abstract
BACKGROUND: With the explosion of techniques for recording brain activity, including the analysis of electrical signals generated during sleep, our understanding of neural dynamics has expanded significantly. Yet, uncertainty exists regarding whether there are sex differences in brain activity during sleep across the human lifespan. We aimed to address the gap by analyzing published evidence on the topic. METHOD: We developed a search strategy to capture English language publications on the topic. Medline ALL, Embase Classic + Embase, APA PsycInfo, Scopus, and Proquest Dissertations and Theses Global were searched in November 2021. We included original studies that reported on sex differences in electrical activity in sleep. No restrictions were applied to study methodology or quality. We analyzed results by frequency bands: delta (0.5‐4 Hz), theta (4‐7 Hz), alpha (8‐12 Hz), sigma (12‐16 Hz), beta (13‐13 Hz), and gamma (30‐80+ Hz) waves. We organized results by age bins of human lifespan stages. RESULT: Two independent researchers screened 2,783 citations. We included 29 studies that met our inclusion and exclusion criteria. The most frequently studied sleep activities were delta and theta, reported in 11 studies (38%) each. Eight studies (28%) reported on sex difference in alpha and sigma activity, four (14%) on beta activity, and two (7%) on gamma activity. Within these studies, recording techniques and frequency bands assigned to electrical brain activity varied. The most frequently studied age groups were teenagers (18 studies (62%) focusing on delta and theta waves) and middle to late age adults (10 studies (34%) focusing on delta and alpha waves). No studies reported on sex differences in infancy and early childhood. Age‐dependent results, although inconsistent, supported sex difference around the timing of brain maturation and sex variability during ageing. CONCLUSION: The clinical implications of our findings are challenging to examine since most evidence had no direct links to outcomes. Nonetheless, the findings offer insight on the development of future research on sex difference in electrical activity in sleep that may be used as clinical trial outcomes, considering that cognitive, behavioral, and emotional processes are reported to differ between the sexes as they age. PROSPERO: CRD42022327644
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| 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 | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".