Grey matter alterations in migraine: A systematic review and meta-analysis
Bibliographic record
Abstract
To summarize and meta-analyze studies on changes in grey matter (GM) in patients with migraine. We aimed to determine whether there are concordant structural changes in the foci, whether structural changes are concordant with functional changes, and provide further understanding of the anatomy and biology of migraine. We searched PubMed and Embase for relevant articles published between January 1985 and November 2015, and examined the references within relevant primary articles. Following exclusion of unsuitable studies, meta-analysis were performed using activation likelihood estimation (ALE). Eight clinical studies were analyzed for structural changes, containing a total of 390 subjects (191 patients and 199 controls). Five functional studies were enrolled, containing 93 patients and 96 controls. ALE showed that the migraineurs had concordant decreases in the GM volume (GMV) in the bilateral inferior frontal gyri, the right precentral gyrus, the left middle frontal gyrus and the left cingulate gyrus. GMV decreases in right claustrum, left cingulated gyrus, right anterior cingulate, amygdala and left parahippocampal gyrus are related to estimated frequency of headache attack. Activation was found in the somatosensory, cingulate, limbic lobe, basal ganglia and midbrain in migraine patients. GM changes in migraineurs may indicate the mechanism of pain processing and associated symptoms. Changes in the frontal gyrus may predispose a person to pain conditions. The limbic regions may be accumulated damage due to the repetitive occurrence of pain-related processes. Increased activation in precentral gyrus and cingulate opposed to GMV decrease might suggest increased effort duo to disorganization of these areas and/or the use of compensatory strategies involving pain processing in migraine. Knowledge of these structural and functional changes may be useful for monitoring disease progression as well as for therapeutic interventions.
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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 | 0.009 | 0.020 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.029 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".