Default mode network changes in fibromyalgia patients are largely dependent on current clinical pain
Bibliographic record
Abstract
Differences in fMRI resting-state connectivity of the default mode network (DMN) seen in chronic pain patients are often interpreted as brain reorganization due to the chronic pain condition. Nevertheless, patients' pain at the time of fMRI might influence the DMN because pain, like cognitive stimuli, engages attentional mechanisms and cognitive engagement is known to alter DMN activity. Here, we aimed to dissociate the influence of chronic pain condition (trait) from the influence of current pain experience (state) on DMN connectivity in patients with fibromyalgia (FM). We performed resting-state fMRI scans to test DMN connectivity in FM patients and matched healthy controls in two separate cohorts: (1) in a cohort not experiencing pain during scanning (27 FM patients and 27 controls), (2) in a cohort with current clinical pain during scanning (16 FM patients and 16 controls). In FM patients without pain during scanning, the connectivity of the DMN did not differ significantly from controls. By contrast, FM patients with current clinical pain during the scan had significantly increased DMN connectivity to bilateral anterior insula (INS) similar to previous studies. Regression analysis showed a positive relationship between DMN-midINS connectivity and current pain. We therefore suggest that transient DMN disruptions due to current clinical pain during scanning (current pain state) may be a substantial contributor to DMN connectivity disruptions observed in chronic pain patients.
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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 | 0.000 | 0.022 |
| 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 | 0.001 |
| 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".