The Continuity Illusion Does Not Depend on Attentional State: fMRI Evidence from Illusory Vowels
Bibliographic record
Abstract
We investigate whether the neural correlates of the continuity illusion, as measured using fMRI, are modulated by attention. As we have shown previously, when two formants of a synthetic vowel are presented in an alternating pattern, the vowel can be identified if the gaps in each formant are filled with bursts of plausible masking noise, causing the illusory percept of a continuous vowel ("Illusion" condition). When the formant-to-noise ratio is increased so that noise no longer plausibly masks the formants, the formants are heard as interrupted ("Illusion Break" condition) and vowels are not identifiable. A region of the left middle temporal gyrus (MTG) is sensitive both to intact synthetic vowels (two formants present simultaneously) and to Illusion stimuli, compared to Illusion Break stimuli. Here, we compared these conditions in the presence and absence of attention. We examined fMRI signal for different sound types under three attentional conditions: full attention to the vowels; attention to a visual distracter; or attention to an auditory distracter. Crucially, although a robust main effect of attentional state was observed in many regions, the effect of attention did not differ systematically for the illusory vowels compared to either intact vowels or to the Illusion Break stimuli in the left STG/MTG vowel-sensitive region. This result suggests that illusory continuity of vowels is an obligatory perceptual process, and operates independently of attentional state. An additional finding was that the sensitivity of primary auditory cortex to the number of sound onsets in the stimulus was modulated by attention.
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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 | 0.001 |
| 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".