Interaction between Sensory- and Goal-related Neuronal Signals on Saccade Trajectories in the Monkey
Bibliographic record
Abstract
Saccade trajectories are dynamic and may reflect the interaction between sensory- and goal-driven processes. In humans, saccades often deviate towards visually salient distractors, but saccades have also been shown to deviate away from spatially predictable distractors (Van der Stigchel & Theeuwes, 2006; Ludwig & Gilchrist, 2004). This has been attributed to spatially-local excitation versus inhibition at some neural site representing the distractor. We explored the relationship between saccade deviation and neuronal activity in the superior colliculus (SC), a crucial substrate for the integration of sensory- and goal-related signals for the production of saccades. Monkeys were trained to make a simple step-saccade to a peripheral target stimulus, and on a portion of the trials a salient distractor appeared at a nearby spatially predictable location (i.e., the same location on every trial). If the distractor appeared simultaneous with the target, correctly directed saccades (those whose end point was closest to the target) often deviated towards the distractor, but when the distractor appeared shortly before the target at various onset asynchronies (50–400 ms), saccades began to systematically deviate away from the distractor. We divided the trials based on the degree to which the trajectories deviated away from the distractor and found that greater deviation away was associated with reduced activity at the distractor-related site in the SC beginning approximately 30 ms prior to saccade onset. Conversely, we divided the trials based on the level of neuronal activity at the distractor-related site (from −30 ms to saccade onset) and found significantly greater deviation away when activity was lowest. This is consistent with the idea that spatially-local excitation versus inhibition at the distractor-related SC site causes saccades to deviate towards versus away from salient distractors. Results are discussed in terms of SC lateral interactions and inhibitory nigrotectal projections (Jiang et al., 2003).
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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) | 0.000 | 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 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".