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The acute effects of intranasal oxytocin on automatic and effortful attentional shifting to emotional faces

2011· article· en· W2101839115 on OpenAlexaff
Mark A. Ellenbogen, Anne‐Marie Linnen, Robin Grumet, Christopher Cardoso, Ridha Joober

Bibliographic record

VenuePsychophysiology · 2011
Typearticle
Languageen
FieldPsychology
TopicNeuroendocrine regulation and behavior
Canadian institutionsMcGill UniversityDouglas Mental Health University InstituteConcordia University
Fundersnot available
KeywordsDisengagement theoryPsychologyOxytocinAttentional biasAngerDevelopmental psychologyCognitive psychologyAnxietyNeuroscienceClinical psychologyPsychiatry

Abstract

fetched live from OpenAlex

Oxytocin is known to promote social affiliation. The mechanism by which this occurs is unknown, but it may involve changes in social information processing. In a placebo-controlled study, we examined the influence of intranasal oxytocin on effortful and automatic attentional shifting in 57 participants using a spatial cueing task with emotional and neutral faces. For effortful processing, oxytocin decreased the speed of shifting attention to sad faces presented for 750 ms and facilitated disengagement from right hemifield sad and angry faces presented for 200 ms. For automatic processing, symptoms of depression moderated the relationship between drug and disengagement. Oxytocin attenuated an attentional bias to masked angry faces on disengagement trials in persons with high depression scores. Oxytocin's influence on social behavior may occur, in part, by eliciting flexible attentional shifting in the early stages of information processing.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.022
GPT teacher head0.315
Teacher spread0.293 · 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

Citations81
Published2011
Admission routes1
Has abstractyes

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