Transcranial magnetic stimulation induced pupil dilations can serve as a cortical excitability measure
Bibliographic record
Abstract
Abstract The application of non-invasive brain stimulation (NIBS) often relies on proxy estimates of cortical excitability (CE), such as the resting motor threshold (rMT), measured through transcranial magnetic stimulation (TMS). However, estimating the rMT is not always possible, as it requires an intact corticospinal pathway for neural signals to travel from the cortex to the periphery. To broaden the application of NIBS there is a need for additional CE measures. In three experiments combining TMS, transcranial direct current stimulation (tDCS), and eye-tracking, we measured TMS-induced pupil dilations as a potential CE proxy. We present Bayesian evidence (Experiment 1: BF > 9; Experiment 2: BF > 46; Experiment 3: BFs > 6) that TMS-induced pupil dilations serve as an objective CE proxy, with larger pupil size reflecting higher CE. We also show that these effects are not due to auditory, muscle, or sensory confounds. The introduction of this novel measure paves the way for a deeper understanding of CE by enabling objective NIBS measures beyond the motor cortex. Moving away from the reliance on the motor cortex would allow NIBS research and therapy to become more inclusive, allowing access to populations that are affected by damage along the corticospinal pathway.
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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 | 0.002 | 0.006 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".