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Record W2156790091 · doi:10.1080/87565640903526553

Attentional Control Moderates Relations Between Negative Affect and Neural Correlates of Action Monitoring in Adolescence

2010· article· en· W2156790091 on OpenAlexfundno aff
Cecile D. Ladouceur, Anne Conway, Ronald E. Dahl

Bibliographic record

VenueDevelopmental Neuropsychology · 2010
Typearticle
Languageen
FieldNeuroscience
TopicNeural and Behavioral Psychology Studies
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental HealthCanadian Institutes of Health Research
KeywordsPsychologyAffect (linguistics)Neural correlates of consciousnessAction (physics)Developmental psychologyNeural activityCognitionNeuroscienceCommunication

Abstract

fetched live from OpenAlex

This study examined the moderating role of attentional control on relations between negative affect and action monitoring event related potentials (ERPs) (error-related negativity (ERN) and N2) in a group of healthy adolescents (9 to 17 years old). These ERPs were recorded while participants completed a modified flanker task. Participants also completed the negative affect subscale of the Positive and Negative Affect Schedule for Children (PANAS-C) and the attentional control subscale of the Early Adolescent Temperament Questionnaire-Revised (EATQ-R). Regression analyses revealed negative affect by attentional control interactions, suggesting that youth high in attentional control and high in negative affect show increased N2 amplitude and a trend toward increased ERN amplitude. These findings are discussed with regard to the interface of attention and emotion processes that are implicated in action monitoring and relevance to the study of self-regulation during adolescence.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.381
Threshold uncertainty score0.643

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
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 head0.105
GPT teacher head0.369
Teacher spread0.264 · 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.

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

Citations23
Published2010
Admission routes1
Has abstractyes

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