Recruitment of a contralateral head turning synergy by stimulation of monkey supplementary eye fields
Bibliographic record
Abstract
The supplementary eye fields (SEF) are thought to enable higher-level aspects of oculomotor control. The goal of the present experiment was to learn more about the SEF's role in orienting, specifically by examining neck muscle recruitment evoked by stimulation of the SEF. Neck muscle activity was recorded from multiple muscles in two monkeys during SEF stimulation (100 μA, 150-300 ms, 300 Hz, with the head restrained or unrestrained) delivered 200 ms into a gap period, before a visually guided saccade initiated from a central position (doing so avoids confounds between initial position and prestimulation neck muscle activity). SEF stimulation occasionally evoked overt gaze shifts and/or head movements but almost always evoked a response that invariably consisted of a contralateral head turning synergy by increasing activity on contralateral turning muscles and decreasing activity on ipsilateral turning muscles (when background activity was present). Neck muscle responses began well in advance of evoked gaze shifts (~30 ms after stimulation onset, leading gaze shifts by ~40-70 ms on average), started earlier and attained a larger magnitude when accompanied by progressively larger gaze shifts, and persisted on trials without overt gaze shifts. The patterns of evoked neck muscle responses resembled those evoked by frontal eye field (FEF) stimulation, except that response latencies from the SEF were ~10 ms longer. This basic description of the cephalomotor command evoked by SEF stimulation suggests that this structure, while further removed from the motor periphery than the FEF, accesses premotor orienting circuits in the brain stem and spinal cord in a similar manner.
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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 | 0.000 |
| 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, 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".