Modulation of Antisaccades by Transcranial Magnetic Stimulation of the Human Frontal Eye Field
Bibliographic record
Abstract
It has been suggested that the frontal eye field (FEF), which is involved with the inhibition and generation of saccades, is engaged to a different degree in pro- and antisaccades. Pro- and antisaccades are often assessed in separate experimental blocks. In such cases, saccade inhibition is required for antisaccades but not for prosaccades. To more directly assess the role of the FEF in saccade inhibition and generation, a new paradigm was used in which inhibition was necessary on pro- and antisaccade trials. Participants looked in the direction indicated by a target ('<' or '>') that appeared in the left or right visual field. When the pointing direction and the location were congruent, prosaccades were executed; otherwise antisaccades were required. Saccadic latencies were measured in blocks without and with single pulse transcranial magnetic stimulation (TMS) to the right FEF or a right posterior control site. Results showed that antisaccades generated into the hemifield ipsilateral to the TMS were significantly delayed after TMS over the FEF, but not the posterior control site. This result is interpreted in terms of a modulation of saccade inhibition to the contralateral visual field due to disruption of processing in the FEF.
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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".