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Record W7048878551

Music, emotion, and the reward system: investigations with [11C] raclopride positron emission tomography, functional magnetic resonance imaging, and psychophysiological methods

2013· dissertation· en· W7048878551 on OpenAlexfundno aff

Bibliographic record

VenueeScholarship@McGill (McGill) · 2013
Typedissertation
Languageen
FieldPhysics and Astronomy
TopicCrystallography and Radiation Phenomena
Canadian institutionsnot available
FundersCanadian Institutes of Health ResearchRéseau en Bio-Imagerie du QuebecNatural Sciences and Engineering Research Council of CanadaCentre for Interdisciplinary Research in Music Media and TechnologyMcGill University
KeywordsPleasureFunctional magnetic resonance imagingAnticipation (artificial intelligence)DopaminergicArousalDopamineRacloprideBrain activity and meditationBrain mapping
DOInot available

Abstract

fetched live from OpenAlex

Music is arguably one of the most potent natural rewards. In this thesis, we examine the brain's response to music through different imaging methods to investigate how musical sounds can be interpreted as pleasurable by a listener. First, we examine the hypothesis that rewarding responses to music are related to emotional arousal. Using self-selected "chill-inducing" music, we measure emotional arousal objectively through psychophysiological measures of autonomic nervous system activity, revealing a robust and direct positive relationship between increases in emotion and self-reported pleasure. Next, we investigate the hypothesis that the intense emotional responses to music may be targeting the brain's reward systems (mesostriatal dopamine circuitry), which have evolved to reinforce highly adaptive behaviours. We use [11C]raclopride positron emission tomography to measure dopamine activity during music listening, and functional magnetic resonance imaging (fMRI) to examine the temporal dynamics of activity in mesostriatal regions. The results provide the first evidence for dopamine release in the ventral striatal regions (specifically, the nucleus accumbens; NAcc) during peak moments of pleasure to music (objectively marked by experience of chills). Furthermore, we demonstrate a temporal distinction in dopaminergic activity as dopamine is released in the dorsal striatal regions in anticipation of the peak pleasure responses, suggesting that expectations and anticipation play an important role in musical pleasure. Finally, in the third study we use fMRI to take a closer look at the dynamic interactions between different brain regions that give rise to musical pleasure when a piece of music is novel, but considered desirable by an individual. The findings of this study reveal that activity in the NAcc during initial listening of music can predict whether that piece of music will be considered rewarding to an individual and subsequently purchased. Moreover, while increased activity in sensory and valuation areas of the brain does not predict reward value of the music, the connectivity of these regions, namely the auditory cortices, ventromedial and orbitofrontal cortices, and amygdala, with the NAcc predicts whether a piece of music will be subsequently purchased. These findings suggest that musical pleasure is a complex process involving highly integrated connectivity between ancient reward circuits in the brain and more recently evolved cortical areas involved in higher-order cognitive processes.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.009
GPT teacher head0.226
Teacher spread0.217 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2013
Admission routes1
Has abstractyes

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