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Record W1967359191 · doi:10.1080/87565641.2014.973497

The Temporal Dynamic of Response Inhibition in Early Childhood: An ERP Study of Partial and Successful Inhibition

2014· article· en· W1967359191 on OpenAlexaff
Nicolas Chevalier, Kathleen M. Kelsey, Sandra A. Wiebe, Kimberly Andrews Espy

Bibliographic record

VenueDevelopmental Neuropsychology · 2014
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsUniversity of Alberta
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute on Drug AbuseNational Institute of Mental Health
KeywordsResponse inhibitionPsychologyLatency (audio)Negativity effectEvent-related potentialDevelopmental psychologyNeuroscienceAudiologyElectroencephalographyCognitionMedicine

Abstract

fetched live from OpenAlex

Event-related potentials were recorded while five-year-old children completed a Go/No-Go task that distinguished between partial inhibition (i.e., response is initiated but cancelled before completion) and successful inhibition (i.e., response is inhibited before it is initiated). Partial inhibition trials were characterized by faster response initiation and later latency of the lateral frontal negativity than successful Go and successful inhibition trials. The speed of response initiation was influenced by the response speed on previous trials and influenced the response speed on subsequent trials. Response initiation and action decision dynamically influenced each other, and their temporal interplay determined response inhibition success.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.039
GPT teacher head0.329
Teacher spread0.290 · 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

Citations17
Published2014
Admission routes1
Has abstractyes

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