Specialized neural dynamics for verbal and tonal memory: fMRI evidence in congenital amusia
Bibliographic record
Abstract
Behavioral and neuropsychological studies have suggested that tonal and verbal short-term memory are supported by specialized neural networks. To date however, neuroimaging investigations have failed to confirm this hypothesis. In this study, we investigated the hypothesis of distinct neural resources for tonal and verbal memory by comparing typical nonmusician listeners to individuals with congenital amusia, who exhibit pitch memory impairments with preserved verbal memory. During fMRI, amusics and matched controls performed delayed-match-to-sample tasks with tones and words and perceptual control tasks with the same stimuli. For tonal maintenance, amusics showed decreased activity in the right auditory cortex, inferior frontal gyrus (IFG) and dorso-lateral-prefrontal cortex (DLPFC). Moreover, they exhibited reduced right-lateralized functional connectivity between the auditory cortex and the IFG during tonal encoding and between the IFG and the DLPFC during tonal maintenance. In contrasts, amusics showed no difference compared with the controls for verbal memory, with activation in the left IFG and left fronto-temporal connectivity. Critically, we observed a group-by-material interaction in right fronto-temporal regions: while amusics recruited these regions less strongly for tonal memory than verbal memory, control participants showed the reversed pattern (tonal > verbal). By benefitting from the rare condition of amusia, our findings suggest specialized cortical systems for tonal and verbal short-term memory in the human brain.
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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) | 0.001 | 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".