TMS Neuro-Cardiovascular Coupling in Vascular Compression Cranial Neuropathy
Bibliographic record
Abstract
BACKGROUND: Neurovascular compression (NVC) may cause cranial mononeuropathy but lacks a definitive diagnostic investigation. We hypothesized that the arterial pressure wave (APW) would interact at the neurovascular interface in NVC to inhibit transmission of transcranial magnetic stimulation (TMS) stimuli to affected muscles. METHODS: We report a novel neurophysiological method coupling cardiovascular physiology with TMS. The electrocardiogram (ECG) and arterial pressure wave (APW) were coupled to triggering of cortical TMS in a patient with NVC-induced spinal accessory (CNXI) mononeuropathy. Outcome measures included motor evoked potential (MEP) amplitudes and firing probabilities of normal and affected trapezieus (TPZ). Values at intervals in proximity to the APW (40/80/120/160 ms) were compared to baseline (800 ms) using ANOVA and student t-test. RESULTS: Electrocardiogram triggered TMS of CNXI pathways with 100% reliability. MEP amplitudes were decreased in proximity to the APW, particularly at 120 ms (0.21-0.04 mV versus 0.39 +/- 0.10 mV, p=0.003). TPZ firing probabilities were similarly inhibited (43.8% versus 88.2%, p=0.009). No effect of APW proximity was observed on the unaffected side (p=0.868). Procedures were well tolerated. CONCLUSIONS: Vascular compression causes CNXI mononeuropathy. Transcranial magnetic stimulation-cardiovascular coupling may evaluate neurovascular junction interactions and non-invasively diagnose NVC.
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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 | 0.000 |
| 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".