Pupil-linked Arousal Signals in the Midbrain Superior Colliculus
Bibliographic record
Abstract
The orienting response evoked by the appearance of a salient stimulus is modulated by arousal; however, neural underpinnings for the interplay between orienting and arousal are not well understood. The superior colliculus (SC), causally involved in multiple components of the orienting response including gaze and attention shifts, receives not only multisensory and cognitive inputs but also arousal-regulated inputs from various cortical and subcortical structures. To investigate the impact of moment-by-moment fluctuations in arousal on orienting saccade responses, we used microstimulation of the monkey SC to trigger saccade responses, and we used pupil size and velocity to index the level of arousal at stimulation onset because these measures correlate with changes in brain states and locus coeruleus activity. Saccades induced by SC microstimulation correlated with prestimulation pupil velocity, with higher pupil velocities on trials without evoked saccades than with evoked saccades. In contrast, prestimulation absolute pupil size did not correlate with saccade behavior. Moreover, pupil velocity correlated with evoked saccade latency and metrics. Together, our results demonstrated that small fluctuations in arousal, indexed by pupil velocity, can modulate the saccade response evoked by SC microstimulation in awake behaving monkeys.
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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 | 0.000 |
| 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 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".