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Record W1872709213

Neural Correlates of Boredom in Music Perception.

2014· article· en· W1872709213 on OpenAlexaff
Ashkan Fakhr Tabatabaie, Mohammad Reza Azadehfar, Negin Mirian, Maryam Noroozıan, Ahmad Yoonessi, Mohammad Reza Saebipour, Ali Yoonessi

Bibliographic record

VenuePubMed · 2014
Typearticle
Languageen
FieldNeuroscience
TopicMind wandering and attention
Canadian institutionsMcGill University
Fundersnot available
KeywordsBoredomNeural correlates of consciousnessElectroencephalographyPerceptionRhythmPsychologyActive listeningBrain activity and meditationMusicalNeural activityAudiologyCognitive psychologySpeech recognitionCommunicationComputer scienceCognitionNeuroscienceArtAestheticsSocial psychologyVisual artsMedicine
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: Music can elicit powerful emotional responses, the neural correlates of which have not been properly understood. An important aspect about the quality of any musical piece is its ability to elicit a sense of excitement in the listeners. In this study, we investigated the neural correlates of boredom evoked by music in human subjects. METHODS: We used EEG recording in nine subjects while they were listening to total number of 10 short-length (83 sec) musical pieces with various boredom indices. Subjects evaluated boringness of musical pieces while their EEG was recording. RESULTS: Using short time Fourier analysis, we found that beta 2 rhythm was (16-20 Hz) significantly lower whenever the subjects rated the music as boring in comparison to non-boring. DISCUSSION: The results demonstrate that the music modulates neural activity of various parts of the brain and can be measured using EEG.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.835
Threshold uncertainty score0.152

Codex and Gemma teacher scores by category

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

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 head0.038
GPT teacher head0.217
Teacher spread0.179 · 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 teacher head, 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

Citations29
Published2014
Admission routes1
Has abstractyes

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