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Record W2625461043 · doi:10.1111/psyp.12902

Stability and reliability of error‐related electromyography over the corrugator supercilii with increasing trials

2017· article· en· W2625461043 on OpenAlexafffund
Nathaniel Elkins‐Brown, Blair Saunders, Frank F. H. He, Michael Inzlicht

Bibliographic record

VenuePsychophysiology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsFacial electromyographyPsychologyReliability (semiconductor)CognitionTask (project management)AudiologyElectromyographyCognitive psychologyNeuroscience

Abstract

fetched live from OpenAlex

Electromyographic activity over the corrugator supercilii (cEMG), the primary facial muscle involved in negative emotions, is increased during the commission of errors on speeded reaction-time tasks. In the present paper, data from two previously published studies were reanalyzed to investigate the reliability and stability of error-related, correct-related, and difference cEMG across increasing numbers of trials. For a modified go/no-go and a flanker task, we found that error-related cEMG was highly stable and reliable in 14 trials, and correct-related cEMG between 56 and 82 trials, respectively. Given the typical number of trials used in studies of cognitive control, these findings suggest that many investigations of error monitoring are already sufficient to obtain acceptable error- and correct-related cEMG signals. Error-related cEMG activity is relatively easy to measure and, as such, it shows great promise for future research investigating the cognitive and affective mechanisms of error monitoring.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
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 score0.683
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
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 head0.148
GPT teacher head0.395
Teacher spread0.247 · 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 designBench or experimental
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

Citations13
Published2017
Admission routes2
Has abstractyes

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