MétaCan
Menu
Back to cohort
Record W2164130671 · doi:10.1111/psyp.12556

Error‐related electromyographic activity over the corrugator supercilii is associated with neural performance monitoring

2015· article· en· W2164130671 on OpenAlex
Nathaniel Elkins‐Brown, Blair Saunders, Michael Inzlicht

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

VenuePsychophysiology · 2015
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFacial electromyographyPsychologyElectromyographyAffect (linguistics)Facial musclesFacial expressionAudiologyCognitionCognitive psychologyCommunicationNeuroscience

Abstract

fetched live from OpenAlex

Emerging research in social and affective neuroscience has implicated a role for affect and motivation in performance monitoring and cognitive control. No study, however, has investigated whether facial electromyography (EMG) over the corrugator supercilii-a measure associated with negative affect and the exertion of effort-is related to neural performance monitoring. Here, we explored these potential relationships by simultaneously measuring the error-related negativity, error positivity (Pe), and facial EMG over the corrugator supercilii muscle during a punished, inhibitory control task. We found evidence for increased facial EMG activity over the corrugator immediately following error responses, and this activity was related to the Pe for both between- and within-subject analyses. These results are consistent with the idea that early, avoidance-motivated processes are associated with performance monitoring, and that such processes may also be related to orienting toward errors, the emergence of error awareness, or both.

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)0.000
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 score0.682
Threshold uncertainty score0.702

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.124
GPT teacher head0.348
Teacher spread0.224 · 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