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Record W4225117881 · doi:10.1177/03057356221091313

Alpha oscillations related to self-other integration and distinction during live orchestral performance: A naturalistic case study

2022· article· en· W4225117881 on OpenAlexafffund
Justin Christensen, Lauren Slavik, Jennifer J. Nicol, Janeen D. Loehr

Bibliographic record

VenuePsychology of Music · 2022
Typearticle
Languageen
FieldPsychology
TopicAction Observation and Synchronization
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for Innovation
KeywordsPsychologyRepertoireInterpersonal communicationMusicalAction (physics)Context (archaeology)Cognitive psychologyCommunicationCognitive scienceSocial psychologyVisual artsArt

Abstract

fetched live from OpenAlex

Ensemble music performance requires musicians to achieve precise interpersonal coordination while maintaining autonomous control over their own actions. To do so, musicians dynamically shift between integrating other performers' actions into their own action plans and maintaining a distinction between their own and others' actions. Research in laboratory settings has shown that this dynamic process of self-other integration and distinction is indexed by sensorimotor alpha oscillations. The purpose of the current descriptive case study was to examine oscillations related to self-other integration and distinction in a naturalistic performance context. We measured alpha activity from four violinists during a concert hall performance of a 60-musician orchestra. We selected a musical piece from the orchestra's repertoire and, before analyzing alpha activity, performed a score analysis to divide the piece into sections that were expected to strongly promote self-other integration and distinction. In line with previous laboratory findings, performers showed suppressed and enhanced alpha activity during musical sections that promoted self-other integration and distinction, respectively. The current study thus provides preliminary evidence that findings from carefully controlled laboratory experiments generalize to complex real-world performance. Its findings also suggest directions for future research and potential applications of interest to musicians, music educators, and music therapists.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.250
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.047
GPT teacher head0.344
Teacher spread0.297 · 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.

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

Citations9
Published2022
Admission routes2
Has abstractyes

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