Electrical Brain Responses to Beat Irregularities in Two Cases of Beat Deafness
Bibliographic record
Abstract
Beat deafness, a recently documented form of congenital amusia, provides a unique window into functional specialization of neural circuitry for the processing of musical stimuli: Beat-deaf individuals exhibit deficits that are specific to the detection of a regular beat in music and the ability to move along with a beat. Studies on the neural underpinnings of beat processing in the general population suggest that the auditory system is capable of pre-attentively generating a predictive model of upcoming sounds in a rhythmic pattern, subserved largely within auditory cortex and reflected in mismatch negativity (MMN) and P3 event-related potential (ERP) components. The current study examined these neural correlates of beat perception in two beat-deaf individuals, Mathieu and Marjorie, and a group of control participants under conditions in which auditory stimuli were either attended or ignored. Compared to control participants, Mathieu demonstrated reduced behavioral sensitivity to beat omissions in metrical patterns, and Marjorie showed a bias to identify irregular patterns as regular. ERP responses to beat omissions reveal an intact pre-attentive system for processing beat irregularities in cases of beat deafness, reflected in the MMN component, and provide partial support for abnormalities in later cognitive stages of beat processing, reflected in an unreliable P3b component exhibited by Mathieu-but not Marjorie-compared to control participants. P3 abnormalities observed in the current study resemble P3 abnormalities exhibited by individuals with pitch-based amusia, and are consistent with attention or auditory-motor coupling accounts of deficits in beat perception.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".