<p>The Psychophysical Assessment of Hierarchical Magno-, Parvo- and Konio-Cellular Visual Stream Dysregulations in Migraineurs</p>
Bibliographic record
Abstract
INTRODUCTION: Although conscious, image-forming illusions have been noted in migraine, few studies have specifically sought to collectively evaluate the role of all three parallel visual processing streams in the retinogeniculostriate pathway involved with image-forming vision and their implications in the development of migraine symptoms. METHODS: We psychophysically assessed the functionality of the inferred magnocellular (MC), parvocellular (PC), and koniocellular (KC) streams at different hierarchical loci across three clinical groups: individuals who experience migraine with aura (MA; n=13), experience migraine without aura (MWO; n=14), and Controls (n=15). Participants completed four experiments: Experiment 1 designed to assess retinal short-wavelength-sensitive (S-) cone sensitivities; Experiment 2 intended to measure postretinal temporal and spatiochromatic contrast sensitivities; Experiment 3 intended to assess postretinal spatiotemporal achromatic contrast sensitivities; and Experiment 4 designed to measure thalamocortical color discriminations along the three cone-excitation axes. RESULTS: S-cone deficits were revealed with greater retinal areas being affected in MA compared to MWO participants. Findings across the four experiments suggest a prominent retinal locus of dysfunction in MA (lesser in MWO) with potential feedforward compensations occurring within the KC visual stream. CONCLUSION: Complex, integrative network compensations need to be factored in when considering the dysregulating influences of migraine along the visual pathway.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".