Fluctuation of primary motor cortex excitability during cataplexy in narcolepsy
Bibliographic record
Abstract
Objective: Cataplexy is a complicated and dynamic process in narcolepsy type 1 (NT1) patients. This study aimed to clarify the distinct stages during a cataplectic attack and identify the changes of the primary motor cortex (PMC) excitability during these stages. Methods: Thirty-five patients with NT1 and 29 healthy controls were recruited to this study. Cataplectic stages were distinguished from a cataplectic attack by video-polysomnogram monitoring. Transcranial magnetic stimulation motor-evoked potential (TMS-MEP) was performed to measure the excitability of PMC during quiet wakefulness, laughter without cataplexy, and each cataplectic stage. Results: Based on the video and electromyogram observations, a typical cataplectic attack (CA) process is divided into four stages: triggering (CA1), resisting (CA2), atonic (CA3), and recovering stages (CA4). Compared with healthy controls, NT1 patients showed significantly decreased intracortical facilitation during quiet wakefulness. During the laughter stage, both patients and controls showed increased MEP amplitude compared with quiet wakefulness. The MEP amplitude significantly increased even higher in CA1 and 2, and then dramatically decreased in CA3 accompanied with prolonged MEP latency compared with the laughter stage and quiet wakefulness. The MEP amplitude and latency gradually recovered during CA4. Interpretation: This study identifies four stages during cataplectic attack and reveals the existence of a resisting stage that might change the process of cataplexy. The fluctuation of MEP amplitude and MEP latency shows a potential participation of PMC and motor control pathway during cataplexy, and the increased MEP amplitude during CA1 and 2 strongly implies a compensatory mechanism in motor control that may resist or avoid cataplectic 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 | 0.000 |
| 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) | 0.001 | 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".