Different intensities of transcranial magnetic stimulation result in dissociable pupil dilations
Bibliographic record
Abstract
The application of transcranial magnetic stimulation (TMS) most commonly relies on the estimation of the resting motor threshold (rMT), which serves as a proxy measure of cortical excitability. However, the rMT cannot always be estimated, as it relies on an intact pathway, travelling from the primary motor cortex (M1) to the periphery. In order to broaden the application of TMS, as well as to better understand the effects of TMS on the nervous system, there is an evident need for additional measures of cortical excitability. In this preliminary study, we provide evidence that pupil size dilation may serve as a potential measure of cortical excitability. In detail, 11 participants received 200 single pulses of either active or sham TMS at various intensities, while their pupil size was recorded. Bayesian evidence from a repeated measures ANOVA suggested that the maximum pupil size dilation as a response to TMS, was dissociable across intensities and between sham and active TMS (BF > 6). Post-hoc Bayesian paired t-tests provided further evidence of the different pupil responses between the various intensities and in sham versus active TMS. These findings show promise for the introduction of a new potential estimate of cortical excitability through measuring pupil responses.
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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 | 0.001 | 0.003 |
| 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) | 0.003 | 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".