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Record W4205447455 · doi:10.1016/j.actpsy.2022.103507

The influence of peripheral emotions on inhibitory control among children

2022· article· en· W4205447455 on OpenAlexaff
Sophia Czapka, John W. Schwieter, Julia Festman

Bibliographic record

VenueActa Psychologica · 2022
Typearticle
Languageen
FieldPsychology
TopicChild and Animal Learning Development
Canadian institutionsWilfrid Laurier University
Fundersnot available
KeywordsSalience (neuroscience)PsychologyInhibitory controlPerceptionCognitionTask (project management)Valence (chemistry)Cognitive psychologyEmotional valenceInformation processingAudiologyDevelopmental psychologyNeuroscienceMedicine

Abstract

fetched live from OpenAlex

In this study, we investigated the cognitive-emotional interplay by measuring the effects of executive competition (Pessoa, 2013), i.e., how inhibitory control is influenced when emotional information is encountered. Sixty-three children (8 to 9 years of age) participated in an inhibition task (central task) accompanied by happy, sad, or neutral emoticons (displayed in the periphery). Typical interference effects were found in the main task for speed and accuracy, but in general, these effects were not additionally modulated by the peripheral emoticons indicating that processing of the main task exhausted the limited capacity such that interference from the task-irrelevant, peripheral information did not show (Pessoa, 2013). Further analyses revealed that the magnitude of interference effects depended on the order of congruency conditions: when incongruent conditions preceded congruent ones, there was greater interference. This effect was smaller in sad conditions, and particularly so at the beginning of the experiment. These findings suggest that the bottom-up perception of task-irrelevant emotional information influenced the top-down process of inhibitory control among children in the sad condition when processing demands were particularly high. We discuss if the salience and valence of the emotional stimuli as well as task demands are the decisive characteristics that modulate the strength of this relation.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.999

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.009
GPT teacher head0.261
Teacher spread0.252 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

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