Evidence map›Paper›PMID 39133721›Full record

ArticlePLoS biology2024

State-dependent connectivity in auditory-reward networks predicts peak pleasure experiences to music.

Kazuma Mori, Robert Zatorre

Abstract read
In one paragraph

Article in PLoS biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Trial
  2. Review
  3. Article
  4. Review
  5. Article
  6. Article
  7. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Kazuma MoriInstitute for Quantum Life Science, National Institutes for Quantum Science and Technology, Chiba, Japan.ORCID 0000-0002-0212-1039
Robert ZatorreMontréal Neurological Institute, McGill University, Montréal, Canada.

Funding

CIHRFonds de Recherche du QuébecFostering Joint International Research AJapan Society for the Promotion of Science (JSPS)
6 · The paper itself

Abstract

Music can evoke pleasurable and rewarding experiences. Past studies that examined task-related brain activity revealed individual differences in musical reward sensitivity traits and linked them to interactions between the auditory and reward systems. However, state-dependent fluctuations in spontaneous neural activity in relation to music-driven rewarding experiences have not been studied. Here, we used functional MRI to examine whether the coupling of auditory-reward networks during a silent period immediately before music listening can predict the degree of musical rewarding experience of human participants (N = 49). We used machine learning models and showed that the functional connectivity between auditory and reward networks, but not others, could robustly predict subjective, physiological, and neurobiological aspects of the strong musical reward of chills. Specifically, the right auditory cortex-striatum/orbitofrontal connections predicted the reported duration of chills and the activation level of nucleus accumbens and insula, whereas the auditory-amygdala connection was associated with psychophysiological arousal. Furthermore, the predictive model derived from the first sample of individuals was generalized in an independent dataset using different music samples. The generalization was successful only for state-like, pre-listening functional connectivity but not for stable, intrinsic functional connectivity. The current study reveals the critical role of sensory-reward connectivity in pre-task brain state in modulating subsequent rewarding experience.

Indexed as

Auditory PerceptionMagnetic Resonance ImagingMusicPleasureRewardAcoustic StimulationAdultAuditory CortexBrainBrain MappingFemaleHumansMachine LearningMaleNerve NetYoung Adult

Identifiers

PMID39133721
PMCPMC11318860

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.