Functional MRI Evidence of an Abnormal Neural Network for Pitch Processing in Congenital Amusia
Bibliographic record
Abstract
Congenital amusia (tone deafness) is a lifelong disorder that prevents typically developing individuals from acquiring basic musical skills. Electrophysiological evidence indicates that congenital amusia is related to a musical pitch deficit that does not seem to arise from a dysfunction of the auditory cortex but rather from an anomaly along a frontotemporal auditory pathway. In order to better localize the neural basis of this pitch disorder, here we conducted a functional magnetic resonance imaging (fMRI) study. Congenital amusic adults and "musically intact" controls were scanned while passively listening to pure-tone melodic-like sequences in which the pitch distance between consecutive tones was varied parametrically. In both amusics and controls, brain activity increased as a function of increasing pitch distance, even for fine pitch changes, in both the left and right auditory cortices. These results support prior electrophysiological work showing that the auditory cortex of amusic individuals responds normally to pitch. In contrast, the right inferior frontal gyrus showed an abnormal deactivation in the amusic group, as well as reduced connectivity with the auditory cortex as compared with controls. These fMRI data are highly consistent with previous gray and white matter anomalies found in amusics in the auditory and inferior frontal cortices, as well as reduced white matter connections between these 2 regions.
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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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".