Influence of Stimulus Eccentricity and Direction on Characteristics of Pro- and Antisaccades in Non-Human Primates
Bibliographic record
Abstract
The ability to inhibit reflexes in favor of goal-oriented behaviors is critical for optimal exploration and interaction with our environment. The antisaccade task can be used to investigate the ability of subjects to suppress a reflexive saccade (prosaccade) to a suddenly appearing visual stimulus and instead generate a voluntary saccade (antisaccade) to its mirror location. To understand the neural mechanisms required to perform this task, our lab has developed a non-human primate model. Two monkeys were trained on a task with randomly interleaved pro- and antisaccade trials, with the color of the central fixation point (FP) instructing the monkey to either make a prosaccade (red FP) or an antisaccade (green FP). In half of the trials, the FP disappeared 200 ms before stimulus presentation (gap condition) and in the remaining trials, the FP remained visible (overlap condition) during stimulus presentation. The effect of stimulus eccentricity and direction was examined by presenting the stimulus at one of eight different radial directions (0-360 degrees ) and five eccentricities (2, 4, 8, 10, and 16 degrees ). Antisaccades had longer saccadic reaction times (SRTs), more dysmetria, and lower peak velocities than prosaccades. Direction errors in the antisaccade task were more prevalent in the gap condition. The difference in mean SRT between correct pro- and antisaccades, the anti-effect, was greater in the overlap condition. The difference in mean SRT between the overlap and the gap condition, the gap effect, was larger for antisaccades than for prosaccades. The manipulation of stimulus eccentricity and direction influenced SRT and the proportion of direction errors. These results are comparable to human studies, supporting the use of this animal model for investigating the neural mechanisms subserving the generation of antisaccades.
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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".