Neural adaptation of the reward system in primary dysmenorrhea
Bibliographic record
Abstract
Introduction: The brain’s reward system (RS) reacts differently to pain and its alleviation. This study examined the correlation between RS activity and behavior during both painful and pain-free periods in individuals with primary dysmenorrhea (PDM) to elucidate their varying responses throughout the menstrual cycle. Methods: Ninety-two individuals with PDM and 90 control participants underwent resting-state functional magnetic resonance imaging (rsfMRI) scans during their menstrual and peri-ovulatory phases. Regional homogeneity (ReHo) and amplitude of low-frequency fluctuation (ALFF) analyses were used to evaluate RS responses. Psychological evaluations were conducted using the McGill Pain Questionnaire and the Pain Catastrophizing Scale. Results: ReHo analysis showed higher values in the left putamen and right amygdala of the PDM group during the peri-ovulatory phase compared to the menstrual phase. ALFF analysis revealed lower values in the putamen of the PDM group compared to controls, regardless of phase. ReHo and ALFF values in the putamen, amygdala, and nucleus accumbens were positively correlated with pain scales during menstruation, while ALFF values in the ventral tegmental area inversely correlated with pain intensity. Those with severe PDM (pain intensity ≥7) displayed distinct amygdala ALFF patterns between pain and pain-free phases. PDM participants also had lower ReHo values in the left insula during menstruation, with no direct correlation to pain compared to controls. Discussion: Our study highlights the pivotal role of the RS in dysmenorrhea management, exhibiting varied responses between menstrual discomfort and non-painful periods among individuals with PDM. During menstruation, the RS triggers mechanisms for pain avoidance and cognitive coping strategies, while it transitions to processing rewards during the peri-ovulatory phase. This demonstrates the flexibility of the RS in adapting to the recurring pain experienced by those with PDM.
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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 | 0.001 | 0.000 |
| 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) | 0.000 | 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".