Beyond the emotional impact of dissonance: Inharmonic music elicits greater cognitive interference than does harmonic music
Bibliographic record
Abstract
The present research evaluates whether task-irrelevant inharmonic music produces greater interference with cognitive performance than task-irrelevant harmonic music. Participants completed either an auditory (Experiments 1 and 2) or a visual (Experiment 3) version of the cognitively demanding 2-back task in which they were required to categorize each digit in a sequence of digits as either being a target (a digit also presented two positions earlier in the sequence) or a distractor (all other items). They were concurrently exposed to task-irrelevant harmonic music (judged to be consonant), task-irrelevant inharmonic music (judged to be dissonant), or no music at all as a distraction. The main finding across all three experiments was that performance on the 2-back task was worse when participants were exposed to inharmonic music than when they were exposed to harmonic music. Interestingly, performance on the 2-back task was generally the same regardless of whether harmonic music or no music was played. I suggest that inharmonic, dissonant music interferes with cognitive performance by requiring greater cognitive processing than harmonic, consonant music, and speculate about why this might be.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".