Emotional responses to unpleasant music correlates with damage to the parahippocampal cortex
Bibliographic record
Abstract
Music is typically a pleasurable experience. But under certain circumstances, music can also be unpleasant, for example, when a young child randomly hits piano keys. Such unpleasant musical experiences have been shown to activate a network of brain structures involved in emotion, mostly located in the medial temporal lobe: the parahippocampal gyrus, amygdala, hippocampus and temporal pole. However, the differential roles of these regions remain largely unknown. In this study, pleasant and unpleasant music was presented to 17 patients with variable excisions of the medial temporal lobe, as well as to 19 matched controls. The pleasant music corresponded to happy and sad selections taken from the classical instrumental repertoire; the unpleasant music was the dissonant arrangement of the same selections. Only patients with substantial resections of the left or right parahippocampal cortex (PHC) gave highly abnormal judgements to dissonant music; they rated dissonant music as slightly pleasant while controls found it unpleasant. This indifference to dissonance was correlated with the remaining volume in the PHC, but was unrelated to the volume of the surrounding structures. The impairment was specific: the same patients judged consonant music to be pleasant, and were able to judge music as happy or sad. Furthermore, this lack of responsiveness to unpleasantness was not due to a perceptual disorder, because all patients were able to detect intentional errors in the musical excerpts. Moreover, the impairment differed from that induced by amygdala damage alone. These findings are consistent with a two-dimensional model of defensive responses to aversive stimuli, in which the PHC and the amygdala subserve different roles.
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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) | 0.002 | 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".