Global and selective effects of auditory attention on arousal: insights from pupil dilation
Bibliographic record
Abstract
Abstract Theoretical models of attention propose that norepinephrine (NE) can induce both a global boost of arousal and selective amplification of high-priority stimuli, yet few tasks have tested these dual effects in humans. Here, we used pupillometry in an auditory detection task, the Competitive Attention Test (CAT), previously performed in large cohort studies, to examine how task engagement (active vs. passive) and stimulus relevance (informative vs. uninformative cues) modulate arousal. Results showed that both relevant and irrelevant sounds elicited larger pupil dilation under active conditions, indicating a global arousal effect. Crucially, only relevant sounds benefited from an additional dilation when preceded by an informative cue, demonstrating a selective arousal mechanism associated to top-down attention. These findings illustrate the NE’s dual role in boosting overall alertness while selectively enhancing high-priority stimuli. Beyond theoretical implications, this work highlights that the CAT captures measurable arousal components, reinforcing its utility for clinical assessments of attention-arousal clinical disruptions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 | 0.001 |
| 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".