Recruitment of a Head-Turning Synergy by Low-Frequency Activity in the Primate Superior Colliculus
Bibliographic record
Abstract
Low-frequency activity within the oculomotor system helps bridge sensation and action. Given ocular stability, low-frequency activity sustained by some neurons within the intermediate and deep superior colliculus (dSC) is assumed to be separated from motor output. However, the dSC is an orienting structure and the influence of low-frequency dSC activity at other effectors remains untested. We studied this by simultaneously recording activity from saccade-related dSC neurons and electromyographic (EMG) activity from neck muscles that turn the head. Monkeys performed a gap-saccade paradigm with varying levels of reward expectancy. Despite head restraint and even for relatively small target eccentricities (<or=10 degrees ), increasing reward expectancy for a given target increased the level of low-frequency activity on dSC neurons encoding saccades to the rewarded target and increased the recruitment of a neck muscle synergy that would turn the head toward the target. The magnitude of neck muscle recruitment correlated positively on a trial-by-trial basis with the level of low-frequency dSC activity, and such correlations were optimized when neck muscle activity was shifted about 20 ms later to account for delays in the tecto-reticulo-spinal pathway. Further, dSC activity discriminated about the side of target presentation approximately 11 ms earlier than neck EMG activity. Considered alongside neck EMG responses evoked causally by SC stimulation, our results are consistent with low-frequency dSC activity recruiting a head-turning synergy. Our results support a brain stem circuit wherein the magnitude of neck muscle recruitment reflects the difference in comparative low-frequency activation across both dSCs, perhaps because of mutually inhibitory interactions within downstream head premotor circuits.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".