Region-specific changes in brain glutamate and gamma-aminobutyric acid across the migraine attack in children and adolescents
Bibliographic record
Abstract
ABSTRACT: In patients with migraine, an excitation-inhibition imbalance that fluctuates relative to attack onset has been proposed to contribute to the underlying pathophysiology of migraine, but this has yet to be explored in children and adolescents. This prospective, observational, cohort study examined glutamate and gamma-aminobutyric acid (GABA) levels across the phases of a migraine attack and interictally in children and adolescents using magnetic resonance spectroscopy. Macromolecule-suppressed GABA (sensorimotor cortex and thalamus) and glutamate (occipital cortex, sensorimotor cortex, and thalamus) were measured in children and adolescents (10-17 years) with a migraine diagnosis with or without aura 4 times over 2 weeks. Linear mixed-effects models examined changes in glutamate and GABA during the 72 hours leading up to, and after the onset of an attack. We found significant region-specific changes in glutamate and GABA. Specifically, sensorimotor GABA significantly increased leading up to the headache phase, whereas glutamate significantly decreased following the headache onset in the occipital cortex and the thalamus. Post hoc analyses examined the 24 hours leading up to or following the onset of the headache phase. In the 24 hours before the headache onset, sensorimotor glutamate, occipital glutamate, and thalamic GABA decreased. In the 24 hours post headache onset, sensorimotor glutamate continued to decrease. Our results suggest changes in glutamate and GABA that are consistent with the thalamocortical dysrhythmia hypothesis. These findings provide insight into developmental migraine pathophysiology and may open future avenues for treatment targets specific to children and adolescents.
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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 | 0.001 |
| 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) | 0.001 | 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".