Unveiling the Causal Role of Auditory Theta Rhythms in Musical Pleasure: A Transcranial Alternating Current Stimulation/Electroencephalogram Study
Bibliographic record
Abstract
The enjoyment of music involves a complex interplay between brain perceptual areas and the reward network. While previous studies have shown that musical liking is related to an enhancement of synchronization between the right temporal and frontal brain regions via theta frequency band oscillations, the underlying mechanisms of this interaction remain elusive. Specifically, a causal relationship between theta oscillations and musical pleasure has yet to be shown. In the present study, we address this question by using transcranial alternating current stimulation (tACS). Twenty-four participants underwent three different sessions where they received tACS over the right auditory cortex before listening to and rating a set of melodies selected to vary in familiarity and complexity. In the target session, participants received theta stimulation, while in the other two sessions, they received beta and sham stimulation, serving as controls. We recorded brain activity using EEG during task performance to confirm the effects of tACS on oscillatory activity. Results revealed that compared with sham, theta, but not beta, stimulation resulted in higher liking ratings specifically for unfamiliar music with low complexity. In addition, we found increased theta connectivity between the right temporal and frontal electrodes for these stimuli when they were most liked after theta stimulation but not after beta stimulation. These findings support a causal and frequency-specific relationship between music hedonic judgments and theta oscillatory mechanisms that synchronize the right temporal and frontal areas. These mechanisms play a crucial role in different cognitive processes supported by frontotemporal loops, such as auditory working memory and predictive processing, which are fundamental to music reward processing.
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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".