Music Lexical Networks
Bibliographic record
Abstract
Successful recognition of a familiar tune depends on a selection procedure that takes place in a memory system that contains all the representations of the specific musical phrases to which one has been exposed during one's lifetime. We refer to this memory system as the musical lexicon. The goal of the study was to identify its neural correlates. The brains of students with little musical training were scanned with functional magnetic resonance imaging (fMRI) while the student listened to familiar musical themes, unfamiliar music, and random tones. The familiar themes were selected from instrumental pieces well-known to the participants; the unfamiliar music was the retrograde version of the familiar themes, which the participants did not recognize; and the random sequences contained the same musical tones but in a random order. All stimuli were synthesized and played with the sound of a piano, thereby keeping low-level acoustical factors similar across conditions. The comparison of cerebral responses to familiar versus unfamiliar music reveals focal activation in the right superior temporal sulcus (STS). Re-analysis of the data obtained in a previous study by Plailly et al. also points to the STS as the critical region involved in musical memories. The neuroimaging data further suggest that these auditory memories are tightly coupled with action (singing), by showing left activation in the planum temporale, in the supplementary motor area (SMA), and in the inferior frontal gyrus. Such a cortical organization of music recognition is analogous to the dorsal stream model of speech processing proposed by Hickok and Poeppel.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 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".