Cortical activation by a salient sound modulates visual temporal order judgments: An electrophysiological study of multisensory attentional processes
Bibliographic record
Abstract
Previous event-related potential (ERP) studies show that a salient lateral sound activates the visual cortex more strongly contralateral to the sound, observed as an auditory-evoked contralateral occipital positivity (ACOP). Studies showed that this activation enhances the early cortical processing of co-localized visual stimuli presented after, reflected by better detection rates, better discrimination, and sharper perceived contrast. We replicated the ACOP, using earphones, and tested whether auditory cuing can influence temporal order judgments (TOJ) for two visual stimuli (horizontal arrangement) as well as if the ACOP would predict the amplitude of this influence. A lateral salient sound was followed, after 150 or 630 ms, by the visual presentation of a pair of disks, one in left and one in right hemifield, with variable SOA. The TOJ task was to indicate which disk appeared first or which disk appeared second (controlling for response bias). We observed an ACOP at posterior electrode sites and confirmed our hypothesis that the lateral sound influenced TOJ by accelerating the perception of the disk presented on the cued side, even though the sound was irrelevant to the task. Furthermore, the ACOP amplitude was correlated to this visual perceptual change, indicating that a larger change in brain activity was associated with a faster processing of co-localized visual stimuli.
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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".