Influence of Background Musical Emotions on Attention in Congenital Amusia
Bibliographic record
Abstract
Congenital amusia in its most common form is a disorder characterized by a musical pitch processing deficit. Although pitch is involved in conveying emotion in music, the implications for pitch deficits on musical emotion judgements is still under debate. Relatedly, both limited and spared musical emotion recognition was reported in amusia in conditions where emotion cues were not determined by musical mode or dissonance. Additionally, assumed links between musical abilities and visuo-spatial attention processes need further investigation in congenital amusics. Hence, we here test to what extent musical emotions can influence attentional performance. Fifteen congenital amusic adults and fifteen healthy controls matched for age and education were assessed in three attentional conditions: executive control (distractor inhibition), alerting, and orienting (spatial shift) while music expressing either joy, tenderness, sadness, or tension was presented. Visual target detection was in the normal range for both accuracy and response times in the amusic relative to the control participants. Moreover, in both groups, music exposure produced facilitating effects on selective attention that appeared to be driven by the arousal dimension of musical emotional content, with faster correct target detection during joyful compared to sad music. These findings corroborate the idea that pitch processing deficits related to congenital amusia do not impede other cognitive domains, particularly visual attention. Furthermore, our study uncovers an intact influence of music and its emotional content on the attentional abilities of amusic individuals. The results highlight the domain-selectivity of the pitch disorder in congenital amusia, which largely spares the development of visual attention and affective systems.
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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 | 0.002 |
| 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 | 0.000 |
| 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".