Distinct impacts of sodium channel blockers on the strength-duration properties of human motor cortex neurones
Bibliographic record
Abstract
ABSTRACT Voltage-gated sodium channels (VGSCs) are essential for regulating axonal excitability in the human brain. While sodium channel blockers are known to modulate neuronal excitability, their in vivo effects on the human cortex remain poorly understood. Here, we employed novel transcranial magnetic stimulation (TMS) measures to investigate the effects of sodium channel blockers, carbamazepine and lacosamide, on the strength-duration behaviour of human cortical neurones, serving as an index of sodium channel function. Our data showed that single doses of both medications elevated resting motor thresholds compared to placebo, indicating reduced excitability; however, their impacts varied according to TMS pulse width. Carbamazepine raised thresholds proportionally across all pulse widths, whereas lacosamide disproportionately influenced thresholds for long-duration pulses. Crucially, lacosamide reduced the strength-duration time constant and increased rheobase, while carbamazepine had minimal effects on both. These results reveal subtle and unexpected differences in cortical neurone behaviour following VGSC-blocking medication administration. Lacosamide’s response aligns with the proposed mechanism of sodium conductance blockade, while carbamazepine’s effects suggest distinct VGSC interactions or potential off-target effects. Our findings advance the understanding of VGSC-blocking medication interactions in the human cortex and underscore the importance of employing specific TMS measures to gain deeper insights into medication mechanisms of action in vivo. Such measures could serve as valuable adjuncts in medication development and patient monitoring, enhancing understanding of medication action in clinical settings.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: no | Bench or experimental | high |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".