Surprise-related activation in the nucleus accumbens interacts with music-induced pleasantness
Bibliographic record
Abstract
How can music-merely a stream of sounds-be enjoyable for so many people? Recent accounts of this phenomenon are inspired by predictive coding models, hypothesizing that both confirmation and violations of musical expectations associate with the hedonic response to music via recruitment of the mesolimbic system and its connections with the auditory cortex. Here we provide support for this model, by revealing associations of music-induced pleasantness with musical surprises in the activity and connectivity patterns of the nucleus accumbens (NAcc)-a central component of the mesolimbic system. We examined neurobehavioral responses to surprises in three naturalistic musical pieces using fMRI and subjective ratings of valence and arousal. Surprises were associated with changes in reported valence and arousal, as well as with enhanced activations in the auditory cortex, insula and ventral striatum, relative to unsurprising events. Importantly, we found that surprise-related activation in the NAcc was more pronounced among individuals who experienced greater music-induced pleasantness. These participants also exhibited stronger surprise-related NAcc-auditory cortex connectivity during the most pleasant piece, relative to participants who found the music less pleasant. These findings provide a novel demonstration of a direct link between musical surprises, NAcc activation and music-induced pleasantness.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| 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".