Effects of reward on the accuracy and dynamics of smooth pursuit eye movements.
Bibliographic record
Abstract
Reward modulates behavioral choices and biases goal-oriented behavior, such as eye or hand movements, toward locations or stimuli associated with higher rewards. We investigated reward effects on the accuracy and timing of smooth pursuit eye movements in 4 experiments. Eye movements were recorded in participants tracking a moving visual target on a computer monitor. Before target motion onset, a monetary reward cue indicated whether participants could earn money by tracking accurately, or whether the trial was unrewarded (Experiments 1 and 2, n = 11 each). Reward significantly improved eye-movement accuracy across different levels of task difficulty. Improvements were seen even in the earliest phase of the eye movement, within 70 ms of tracking onset, indicating that reward impacts visual-motor processing at an early level. We obtained similar findings when reward was not precued but explicitly associated with the pursuit target (Experiment 3, n = 16); critically, these results were not driven by stimulus prevalence or other factors such as preparation or motivation. Numerical cues (Experiment 4, n = 9) were not effective.
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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 | 0.001 | 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".