The neural bases of familiar music listening in healthy individuals: An activation likelihood estimation meta-analysis
Bibliographic record
Abstract
Accumulating evidence suggests that the neural activations during music listening differs as a function of familiarity with the excerpts. However, the implicated brain areas are unclear. After an extensive literature search, we conducted an Activation Likelihood Estimation analysis on 23 neuroimaging studies (232 foci, 364 participants) to identify consistently activated brain regions when healthy adults listen to familiar music, compared to unfamiliar music or an equivalent condition. The results revealed a left cortical-subcortical co-activation pattern comprising three significant clusters localized to the supplementary motor areas (BA 6), inferior frontal gyrus (IFG, BA 44), and the claustrum/insula. Our results are discussed in a predictive coding framework, whereby temporal expectancies and familiarity may drive motor activations, despite any overt movement. Though conventionally associated with syntactic violation, our observed activation in the IFG may support a recent proposal of its involvement in a network that subserves both violation and prediction. Finally, the claustrum/insula plays an integral role in auditory processing, functioning as a hub that integrates sensory and limbic information to (sub)cortical structures.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.010 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".