Menstrual cycle phase modulates causal connectivity in the resting-state brain of healthy females
Bibliographic record
Abstract
Abstract Background Ovarian hormones exert direct and indirect influences on the brain; however, little is known about how these hormones impact causal brain connectivity. Studying the female brain at a single time point may be confounded by distinct hormone phases. Despite this, the menstrual cycle is often overlooked. The primary objective of this pilot study was to evaluate resting-state causal connectivity during the early follicular and mid-luteal menstrual phases corresponding to low vs high estradiol and progesterone, respectively. Methods Fourteen healthy control females ( M = 20.36 years, SD = 2.02) participated in this study. Participants were scheduled for two resting-state electroencephalography (EEG) scans during their monthly menstrual cycle. A saliva sample was also collected at each EEG session for hormone analyses. Causal connectivity was quantified using information flow rate of EEG source data. Demographic information, emotional empathy, and sleep quality were obtained from self-report questionnaires. Results Progesterone levels were significantly higher in the mid-luteal phase compared to the early follicular phase ( p = .041). We observed distinct patterns of causal connectivity along the menstrual cycle. Connectivity in the early follicular phase was centralized and shifted posteriorly during the mid-luteal phase. During the early follicular phase, the primary regions driving activity were the right central and left/right parietal regions, with the left central region being the predominant receiver of activity. During the mid-luteal phase, connections were primarily transmitted from the right side and the main receiver region was the left occipital region. Network topology during the mid-luteal phase was found to be significantly more assortative compared to the early follicular phase. Conclusions The observed difference in causal connectivity demonstrates how network dynamics reorganize as a function of menstrual phase and level of progesterone. In the mid-luteal phase, there was a strong shift for information flow to be directed at visual spatial processing and visual attention areas, whereas in the follicular phase, there was strong information flow primarily within the sensory-motor regions. The mid-luteal phase was significantly more assortative, suggesting greater network efficiency and resilience. These results contribute to the emerging literature on brain-hormone interactions.
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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 | 0.002 |
| 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 | 0.000 | 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".