Timing the sound-induced flash illusion
Bibliographic record
Abstract
In the sound-induced flash illusion, when two beeps are presented simultaneously with a flash, a second illusory flash is perceived (Shams, Kamitani & Shimojo, 2000). Even though this phenomenon has been examined by a number of authors (e.g., Andersen, Tiippana & Sams, 2004; Berger, Martelli & Pelli, 2003; McCormick & Mamassian, 2008; Shams, Kamitani & Shimojo, 2002), little is known about the exact parameters driving the illusion. A recent study found that the effect is not as robust as it was previously thought, and there is a large disparity in the occurrence of the illusion from a subject to another (Mishra, Martinez, Sejnowski & Hillyard, 2007). A number of reasons might explain this variable occurrence of the illusion but one of them is that the parameters used to generate the illusion are suboptimal. It has been shown that timing is an important aspect of multisensory illusory effects, such as in the McGurk (Munhall, Gribble, Sacco & Ward, 1996) and the ventriloquist effects (Slutsky & Recanzone, 2001). Here, we investigated the temporal constraints of the sound-induced flash illusion. More specifically, we studied the effect of the variance in the timing of the flashes and the beeps using a classification image technique. Results will be given a Bayesian interpretation.
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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 | 0.005 |
| 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 | 0.001 |
| 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".