Modulation of stimulus contrast on the human pupil orienting response
Bibliographic record
Abstract
The sudden appearance of a novel stimulus initiates a series of responses to orient the body for appropriate actions, including not only shifts of gaze and attention, but also transient pupil dilation. Modulation of pupil dynamics by stimulus properties is less understood, although its effects on other components of orienting have been extensively explored. Microstimulation of the superior colliculus evoked transient pupil dilation, and the initial component of pupil dilation evoked by microstimulation was similar to that elicited by the presentation of salient sensory stimuli, suggesting a coordinated role of the superior colliculus on this behavior, although evidence in humans is yet to be established. To examine pupil orienting responses in humans, we presented visual stimuli while participants fixated on a central visual spot. Transient pupil dilation in humans was elicited after presentation of a visual stimulus in the periphery. The evoked pupil responses were modulated systematically by stimulus contrast, with faster and larger pupil responses triggered by higher contrast stimuli. The pupil response onset latencies for high contrast stimuli were similar to those produced by the light reflex and significantly faster than the darkness reflex, suggesting that the initial component of pupil dilation is probably mediated by inhibition of the parasympathetic pathway. The contrast modulation was pronounced under different levels of baseline pupil size. Together, our results demonstrate visual contrast modulation on the orienting pupil response in humans.
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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".