Cortical hyperexcitability in migraine and aversion to patterns
Bibliographic record
Abstract
BACKGROUND: Patients with migraine are averse to certain visual stimuli, such as flicker and striped patterns that evoke paroxysmal EEG activity in patients with photosensitive epilepsy. Migraineurs demonstrate a hyper-responsiveness to such stimuli, and there is debate as to whether the aversion and hyper-responsiveness are due to a hyperexcitability of the cortex similar to that in patients with photosensitive epilepsy. In these patients grating patterns with certain spatial characteristics can be epileptogenic, depending critically on their movement. If the contours of the grating drift continually, the grating is not epileptogenic, but if the contours are static or if their direction is repeatedly and rapidly reversed so as to vibrate, the grating then becomes highly epileptogenic. METHODS: We compared aversion to vibrating, drifting and static gratings in migraineurs and controls. The contrast of each grating was gradually increased, but only until the participant felt discomfort, so as to obtain a contrast threshold for aversion with minimal exposure. RESULTS: Migraineurs had lower thresholds than the control group, indicating greater aversion. For both groups the threshold was higher (aversion was lower) for static than for both types of moving gratings. The drifting gratings were more aversive than the vibrating gratings when both groups were combined. CONCLUSION: The findings suggest that the aversion shown by migraineurs is not attributable to a cortical hyperexcitability similar to that in photosensitive epilepsy.
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.
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 | 0.001 | 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) | 0.003 | 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".