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Visual Contrast Gain Control in Migraine: Measures of Visual Cortical Excitability and Inhibition

2000· article· en· W2049377312 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCephalalgia · 2000
Typearticle
Languageen
FieldMedicine
TopicMigraine and Headache Studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsIctalMigraineContrast (vision)AuraVisual cortexMigraine with auraNeuroscienceInhibitory postsynaptic potentialAudiologyMasking (illustration)MedicinePsychologyElectroencephalographyInternal medicinePhysics

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.583

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.016
GPT teacher head0.293
Teacher spread0.277 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it