Visual Contrast Gain Control in Migraine: Measures of Visual Cortical Excitability and Inhibition
Bibliographic record
Abstract
The present study examined the extent to which migraineurs demonstrate interictal visual cortical hyperexcitability as a result of poor inhibitory control in the visual system. We employed a well-established psychophysical measure of inhibition, visual contrast gain control. The task involved detecting a briefly presented target that was superimposed on a highly excitable high contrast masking pattern. The strength of inhibition was assessed by comparing target detection thresholds with and without the operation of gain controls. Migraineurs with and without aura (n=25, n=22, respectively) were compared with those with no history of migraine (n=25). Our results do not indicate a loss of inhibition in migraine; the strength of inhibitory feedback contrast gain controls was similar between migraineurs and controls. We did however, find a statistically greater masking effect in migraineurs compared with controls in the zero delay condition, suggesting cortical hyperexcitability in migraine. Possible mechanisms of cortical hyperexcitability are discussed in light of the results.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".