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Record W2041201894 · doi:10.1097/wnr.0b013e328010a216

Event-related potential measures of emotion regulation in early childhood

2007· article· en· W2041201894 on OpenAlexaff
Marc D. Lewis, Rebecca M. Todd, Michael J.M. Honsberger

Bibliographic record

VenueNeuroreport · 2007
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsMcGill UniversityUniversity of Toronto
Fundersnot available
KeywordsP3bPsychologyEvent-related potentialAngerDevelopmental psychologyAnxietyCognitive psychologyElectroencephalographyNeuroscienceAudiologySocial psychology

Abstract

fetched live from OpenAlex

Emotion regulation in adults may be mediated by frontal cortical activities that adjust attention in response to challenging emotions. We examined event-related potentials across emotional conditions to assess normative patterns and individual differences in cortical mechanisms of emotion regulation in 4-6-year-olds. The children viewed pictures of angry, neutral, and happy faces during a Go/No-go task. Angry faces generated the greatest (frontocentral) N2 amplitudes and fastest N2 latencies, and happy faces produced the smallest amplitudes and slowest latencies. Frontal electrodes showed larger N2s to angry faces in the Go condition. The P3b was also largest for angry faces. More fearful children showed faster latency N2s to angry faces. These results are interpreted in terms of early-developing mechanisms for regulating anxiety and processing emotional information.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.079
GPT teacher head0.334
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

Citations65
Published2007
Admission routes1
Has abstractyes

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