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Record W2140617940 · doi:10.1080/0269993004200187

Frontal brain electrical activity (EEG) distinguishes valence and intensity of musical emotions

2001· article· en· W2140617940 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueCognition & Emotion · 2001
Typearticle
Languageen
FieldNeuroscience
TopicNeuroscience and Music Perception
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologyElectroencephalographyValence (chemistry)Brain activity and meditationMusicalCognitive psychologyEmotional valenceAudiologyCognitionNeuroscienceChemistryArt

Abstract

fetched live from OpenAlex

Using recent regional brain activation/emotion models as a theoretical framework, we examined whether the pattern of regional EEG activity distinguished emotions induced by musical excerpts which were known to vary in affective valence (i.e., positive vs. negative) and intensity (i.e., intense vs. calm) in a group of undergraduates. We found that the pattern of asymmetrical frontal EEG activity distinguished valence of the musical excerpts. Subjects exhibited greater relative left frontal EEG activity to joy and happy musical excerpts and greater relative right frontal EEG activity to fear and sad musical excerpts. We also found that, although the pattern of frontal EEG asymmetry did not distinguish the intensity of the emotions, the pattern of overall frontal EEG activity did, with the amount of frontal activity decreasing from fear to joy to happy to sad excerpts. These data appear to be the first to distinguish valence and intensity of musical emotions on frontal electrocortical measures. Despite the fact that music is a powerful elicitor of emotion (Goldstein, 1980; Panksepp, 1995; Sloboda, 1991), and musicologists believe that the meaning of

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.892
Threshold uncertainty score0.511

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.052
GPT teacher head0.288
Teacher spread0.236 · 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