Altered multisensory integration in pilots: Examining susceptibility to fission and fusion sound-induced flash illusions
Bibliographic record
Abstract
Pilots show superior visual processing capabilities in many visual domain tasks. However, the extent to which this perceptual advantage extends to multisensory processing requires validation. In this study, we examined multisensory integration of auditory and visual information in both pilot and control groups, utilizing two sound-induced flash illusions (SIFI) tasks: the fission illusion, where one flash coupled with two beeps is perceived as two flashes; and the fusion illusion, where two flashes with a single beep are perceived as one flash. Sixty-six participants were instructed to discern whether they observed one or two flashes while discounting irrelevant auditory beeps, across six conditions: one flash (1F), two flashes (2F), one flash/one beep (1F1B), one flash/two beeps (1F2B), two flashes/one beep (2F1B), and two flashes/two beeps (2F2B). We varied six stimulus onset asynchronies (SOAs) between auditory and visual events (25-150 ms) to assess the participants' temporal binding window (TBW). Signal detection theory was employed to analyze the group differences in illusion reports. The findings suggest that, while pilots are less susceptible to SIFI in either fission or fusion conditions, they only exhibit narrower TBW in the fusion condition, where pilots demonstrated a more gradual change in their susceptibility as SOA increases. In the fission condition, the group difference was primarily driven by visual sensitivity, whereas in the fusion condition it also likely reflected pilots' distinct multisensory integration mechanisms. Two alternative possibilities are discussed to explain the group differences and the different multisensory integration patterns in fission and fusion conditions.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".