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Record W2753678779 · doi:10.1080/87565641.2017.1355917

Neural Correlates of Response Inhibition in Early Childhood: Evidence From a Go/No-Go Task

2017· article· en· W2753678779 on OpenAlexafffund
Aishah Abdul Rahman, Daniel J. Carroll, Kimberly Andrews Espy, Sandra A. Wiebe

Bibliographic record

VenueDevelopmental Neuropsychology · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of AlbertaWomen and Children’s Health Research Institute
FundersNational Institute of Mental HealthNational Institutes of HealthNational Institute on Drug AbuseNatural Sciences and Engineering Research Council of CanadaWellcome Trust
KeywordsGo/no goResponse inhibitionNeural correlates of consciousnessScalpElectroencephalographyPsychologyNeural activityAudiologyTask (project management)NeuroscienceDevelopmental psychologyMedicineCognitionComputer scienceAnatomy

Abstract

fetched live from OpenAlex

We examined the neural correlates underlying response inhibition in early childhood. Five-year-old children completed a Go/No-go task with or without time pressure (Fast vs. Slow condition) while scalp EEG was recorded. On No-go trials where inhibition was required, the left frontal N2 and posterior P3 were enhanced relative to Go trials. Time pressure was detrimental to behavioral performance and modulated the early-occurring P1 component. The topography of ERPs related to response inhibition differed from patterns typically seen in adults, and may indicate a compensatory mechanism to make up for immature inhibition networks in children.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.095
GPT teacher head0.350
Teacher spread0.255 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations42
Published2017
Admission routes2
Has abstractyes

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