Earworms in the Amusic Mind? Questionnaire Investigation in Congenital Amusia
Bibliographic record
Abstract
Involuntary musical imagery, colloquially known as “earworms”, is a phenomenon hypothesized to reflect involuntary rehearsal of long-term memory representations. Here we investigated musical earworms with a questionnaire adapted from Halpern and Bartlett (2011, Music Perception, 28(4), 425–432), both in typical individuals and in participants with congenital amusia. Congenital amusics have impaired short- and long-term musical memory, yet with evidence for preserved implicit processing of music. Almost all participants in both groups reported experiencing musical earworms, however less frequently so in amusics than in controls. In both groups, musical earworms were reported being mostly familiar music with lyrics, and consisted of music liked by the participants. Some features distinguished earworms in amusics and controls, with more limited familiarity effects in amusics. Moreover, amusics were deploying less voluntary strategies to stop the earworms, in keeping with less stable music memories in this group. In addition, we investigated verbal earworms in the same participants. Verbal earworms occurred less frequently than musical earworms, and were more frequent in amusics than in controls. However, the two types of earworms showed similar features and their frequencies of occurrence were correlated, suggesting they rely in part on domain-general processes. Implications for the understanding of involuntary auditory imagery and congenital amusia are discussed.
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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 | 0.005 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".