Neck muscle responses evoked by transcranial magnetic stimulation of the human frontal eye fields
Bibliographic record
Abstract
Transcranial magnetic stimulation (TMS) provides a non-invasive means of investigating brain function. Whereas TMS of the human frontal eye fields (FEFs) does not induce saccades, electrical stimulation of the monkey FEF evokes eye-head gaze shifts, with neck muscle responses evoked at stimulation levels insufficient to evoke a saccade. These animal results motivated us to examine whether TMS of the FEF (TMS-FEF) in humans evokes a neck muscle response. Subjects performed memory-guided saccades to the left or right while TMS (two pulses at 20 Hz) was delivered on 30% of trials to the left FEF coincident with saccade instruction. As reported previously, TMS-FEF decreased contralateral saccade reaction times. We simultaneously recorded the activity of splenius capitis (SPL) (an ipsilateral head turner). TMS-FEF evoked a lateralized increase in the activity of the right SPL but not the left SPL, consistent with the recruitment of a contralateral head-turning synergy. In some subjects, the evoked neck muscle response was time-locked to stimulation, whereas in others the evoked response occurred around the time of the saccade. Importantly, evoked responses were greater when TMS was applied to the FEF engaged in contralateral saccade preparation, with even greater evoked responses preceding shorter latency saccades. These results provide new insights into both the nature of TMS and the human oculomotor system, demonstrating that TMS-FEF engages brainstem oculomotor circuits in a manner consistent with a general role in eye-head gaze orienting. Our results also suggest that pairing neck muscle recordings with TMS-FEF provides a novel way of assaying the covert preparation of oculomotor plans.
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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".