Congenital amusia: An auditory-motor feedback disorder?
Bibliographic record
Abstract
PURPOSE: Congenital amusia (tone deafness) is a disorder in which those affected typically complain of or are identified by their inability to sing in tune. A psychophysical and possibly surrogate marker of this condition is the inability to recognize deviations in pitch that are one semitone (100 cents) or less. The aim of our study was to identify candidate brain regions that might be associated with this disorder. METHODS: We used Voxel-Based-Morphometry (VBM) to correlate performance on a commonly used assessment tool, the Montreal Battery for the Evaluation of Amusia (MBEA), with local inter-individual variations in gray matter volumes across a large group of individuals (n=51) to identify brain regions potentially involved in the expression of this disorder. RESULTS: The analysis across the entire brain space revealed significant covariations between performance on the MBEA and inter-individual gray matter volume variations in the left superior temporal sulcus (BA 22) and the left inferior frontal gyrus (BA 47). The regression analyses identified subregions within the inferior frontal gyrus, and inferior portion of BA47 that correlated with performance on melodic subtests, while gray matter volume variations in a more superior subregion of BA47 correlated with performance on rhythmic subtests. CONCLUSIONS: Our analyses demonstrate the existence of a left fronto-temporal network that appears to be involved in the melodic and rhythmic discrimination skills measured by the MBEA battery. These regions could also be part of a network that enable subjects to map motor actions to sounds including a feedback loop that allows for correction of motor actions (i.e., singing) based on perceptual feedback. Thus, it is conceivable that individuals with congenital amusia, or the inability to sing in tune, may actually have an impairment of the auditory-motor feedback loop and/or auditory-motor mapping system.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".