Auditory imagery in congenital amusia
Bibliographic record
Abstract
Congenital amusia is a neurogenetic disorder affecting various aspects of music and speech processing. Although perception and auditory imagery in the general population may share mechanisms, it is not known whether previously documented perceptual impairments in amusia are coupled with difficulties in imaging auditory objects. We employed the Bucknell Auditory Imagery Scale (BAIS) to assess participants’ self-perceived voluntary imagery and a short earworm questionnaire to gauge their subjective experience of involuntary musical imagery. A total of 32 participants with amusia and 34 matched controls, recruited based on their performance on the Montreal Battery of Evaluation of Amusia (MBEA), filled out the questionnaires in their own time. The earworm scores of amusic participants were not statistically significantly different from those of controls. By contrast, their scores on vividness and control of auditory imagery were significantly lower relative to controls. Overall, results suggest that the presence of amusia may not have an adverse effect on generating involuntary musical imagery—at the level of self-report—but still significantly reduces the individual’s self-rated voluntary imagery of musical, vocal, and environmental sounds. We discuss the findings in the light of previous research on explicit musical judgments and implicit engagement with music, while also touching on some statistical power considerations.
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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 | 0.004 |
| 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 | 0.000 |
| 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".