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Record W2803206602 · doi:10.1037/emo0000456

Neurodevelopmental differences to social exclusion: An event-related neural oscillation study of children, adolescents, and adults.

2018· article· en· W2803206602 on OpenAlexafffund
Alva Tang, Ayelet Lahat, Michael J. Crowley, Jia Wu, Louis A. Schmidt

Bibliographic record

VenueEmotion · 2018
Typearticle
Languageen
FieldPsychology
TopicDeath Anxiety and Social Exclusion
Canadian institutionsMcMaster University
FundersSocial Sciences and Humanities Research Council of CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsPreadolescencePsychologyDevelopmental psychologySocial rejectionPsycINFOElectroencephalographyDistressYoung adultSocial exclusionEvent-related potentialNeural correlates of consciousnessSocial relationClinical psychologyCognitionPsychiatrySocial psychologyMEDLINE

Abstract

fetched live from OpenAlex

Although the neural correlates of social exclusion have been well-documented, most studies have examined single age groups. No studies have directly compared specific age-related differences in social exclusion across children, adolescents, and adults using event-related oscillatory electroencephalogram (EEG) dynamics. The authors examined event-related theta EEG power and phase coherence in fair play and social exclusion conditions during the Cyberball task in 166 participants: 42 children (ages 10-12), 56 adolescents (ages 14-17), and 68 adults (ages 18-28). Children and adolescents displayed the greatest theta power to rejection events, whereas adults displayed the greatest theta power to "not my turn" events. Moreover, the functional link between theta power to rejection and self-reported distress was strongest among the adolescents. These findings suggest that an enhanced neural response to social exclusion is present by preadolescence, but the association between neural and subjective responses is most prominent during adolescence. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

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 score0.264
Threshold uncertainty score0.481

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 integrity0.0000.000
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 head0.017
GPT teacher head0.295
Teacher spread0.278 · 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

Citations35
Published2018
Admission routes2
Has abstractyes

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