Magnetic resonance spectroscopy and the menstrual cycle: A multi-centre assessment of menstrual cycle effects on GABA & GSH
Bibliographic record
Abstract
BACKGROUND: Gamma-aminobutyric acid (GABA) and glutathione (GSH) play a significant role in the functioning of a healthy brain and can both be quantified using magnetic resonance spectroscopy (MRS). Several small-scale studies have suggested MRS measured GABA may fluctuate with the menstrual cycle, but the effects on GSH are unknown. Utilising recent developments in MRS acquisition, this multi-lab study explores this issue across 4 distinctive brain regions. NEW METHODS: Data were analysed from 12 independent sites from which a total of 30 women were scanned during three phases of their menstrual cycle corresponding to early follicular, ovulation and mid luteal phases. HERMES and HERCULES sequences were used to measure GABA and GSH in voxels located in the left motor cortex, left posterior insular, medial parietal and medial frontal. Linear mixed models were used to assess the variability contributed by site, participant and menstrual cycle phase. RESULTS: Similar variance was attributed to site and menstrual cycle phase for both GABA and GSH data. No systematic changes in GABA or GSH were revealed for any voxel as a consequence of menstrual cycle phase. COMPARISON WITH EXISTING METHODS: Despite our larger sample size and inclusion of more brain regions we fail to replicate previous findings of GABA change as a consequence of menstrual cycle phase. We also show for the first time that MRS measures of GSH so not significantly alter with cycle. CONCLUSIONS: Our findings suggest that the menstrual cycle has minimal impact on MRS measures of GABA and GSH. The presence of a menstrual cycle should not be used as justification for exclusion of women in MRS studies.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".