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Record W2620382756 · doi:10.7717/peerj.3363

Rituals decrease the neural response to performance failure

2017· article· en· W2620382756 on OpenAlexaff
Nicholas Hobson, Devin Bonk, Michael Inzlicht

Bibliographic record

VenuePeerJ · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsError-related negativityTask (project management)AnxietyPsychologyElectroencephalographyBrain functionCognitive psychologyMechanism (biology)MorningWorking memoryCognitionMedicineAnterior cingulate cortexNeurosciencePsychiatry

Abstract

fetched live from OpenAlex

Rituals are found in all types of performance domains, from high-stakes athletics and military to the daily morning preparations of the working family. Yet despite their ubiquity and widespread importance for humans, we know very little of ritual's causal basis and how (if at all) they facilitate goal-directed performance. Here, in a fully pre-registered pre/post experimental design, we examine a candidate proximal mechanism, the error-related negativity (ERN), in testing the prediction that ritual modulates neural performance-monitoring. Participants completed an arbitrary ritual-novel actions repeated at home over one week-followed by an executive function task in the lab during electroencephalographic (EEG) recording. Results revealed that relative to pre rounds, participants showed a reduced ERN in the post rounds, after completing the ritual in the lab. Despite a muted ERN, there was no evidence that the reduction in neural monitoring led to performance deficit (nor a performance improvement). Generally, the findings are consistent with the longstanding view that ritual buffers against uncertainty and anxiety. Our results indicate that ritual guides goal-directed performance by regulating the brain's response to personal failure.

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)0.002
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 score0.651
Threshold uncertainty score1.000

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.166
GPT teacher head0.400
Teacher spread0.234 · 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

Citations32
Published2017
Admission routes1
Has abstractyes

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