Superior Colliculus Inactivation Causes Stable Offsets in Eye Position during Tracking
Bibliographic record
Abstract
The primate superior colliculus (SC) is often viewed as composed of two distinct motor zones with complementary functions: a peripheral region that helps generate saccades to eccentric targets and a central one that maintains fixation by suppressing saccades. Here, we directly tested the alternative interpretation that topography in the SC is not strictly motor, nor does it form two distinct zones, but instead forms a single map of behaviorally relevant goal locations. Primates tracked the invisible midpoint between two moving stimuli, such that the stimuli guiding tracking were peripheral whereas the inferred movement goal was foveal and parafoveal. Temporary inactivation of neurons in the central portion of the topographic map of the SC, representing the invisible goal, caused stable offsets in eye position during tracking that were directed away from the retinotopic position encoded by the inactivated SC site. Critically, these offsets were not accompanied by a systematic inability to generate or suppress saccades, and they were not fully explained by motor deficits in saccades, smooth pursuit, or fixation. In addition, the magnitude of the offset depended on the eccentricity of the inactivated site as well as the degree of spatial uncertainty associated with the behavioral goal. These results indicate that gaze control depends on the balance of activity across a map of goal locations in the SC, and that by silencing some of the neurons in the normally active population representing the behavioral goal, focal inactivation causes a biased estimate of where to look.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".