Duration and frequency of migraines affect cognitive function: evidence from neuropsychological tests and event-related potentials
Bibliographic record
Abstract
BACKGROUND: The aim of this study was to evaluate the changes in the cognitive performance of migraine patients using a comprehensive series of cognitive/behavioral and electrophysiological tests. METHOD: A randomized, cross-sectional, within subject approach was used to compare neuropsychological and electrophysiological evaluations from migrane-affected and healthy subjects. RESULTS: Thirty-four patients with migraine (6 males, 28 females, average 36 years old) were included. Migraineurs performed worse in the majority of the Montreal Cognitive Assessment (MoCA) (p = 0.007) compared to the healthy subjects, significantly in language (p = 0.005), memory (p = 0.006), executive functions (p = 0.042), calculation (p = 0.018) and orientation (p = 0.012). Migraineurs had a lower score on the memory trial of the Rey-Osterrieth complex figure test (ROCF) (p = 0.012). The P3 latency in Fz, Cz, Pz was prolonged in migraineurs compared with the normal control group (P < 0.001). In addition, we analyzed significant correlations between MoCA score and the duration of migraine. We also observed that a decrease in the MoCA-executive functions and calculation score and in the ROCF-recall score were both correlated to the frequency of migraine. Migraineurs were more anxious than healthy subjects (p = 0.001), which is independent of cognitive testing. Differences were unrelated to age, gender and literacy. CONCLUSIONS: Cognitive performance decreases during migraine, and cognitive dysfunction can be related to the duration and frequency of a migraine attack.
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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 | 0.000 | 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) | 0.002 | 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".