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Record W4383872878 · doi:10.1111/psyp.14376

Neural response to rewards moderates the within‐person association between daily positive events and positive affect during a period of stress exposure

2023· article· en· W4383872878 on OpenAlexafffund
Héléna Renault, Clara Freeman, Iulia Banica, Aislinn Sandre, Paige Ethridge, Juhyun Park, Anna Weinberg

Bibliographic record

VenuePsychophysiology · 2023
Typearticle
Languageen
FieldPsychology
TopicMental Health Research Topics
Canadian institutionsMcGill University
FundersCanada Research Chairs
KeywordsPsychologyAssociation (psychology)Affect (linguistics)Period (music)Developmental psychologyFight-or-flight responseStress (linguistics)Clinical psychologySocial psychologyCommunicationPsychotherapist

Abstract

fetched live from OpenAlex

Stress and neural responses to reward can interact to predict psychopathology, but the mechanisms of this interaction are unclear. One possibility is that the strength of neural responses to reward can affect the ability to maintain positive affect during stress. In this study, 105 participants completed a monetary reward task to elicit the reward positivity (RewP), an event-related potential sensitive to rewards. Subsequently, during a stressful period, participants reported on their affect nine times a day and on daily positive and negative events for 10 days. Even during heightened stress, experiencing more positive events was associated with increased positive affect. The RewP significantly moderated this association: Individuals with a larger RewP reported greater increases in positive affect when they experienced more positive events, relative to individuals with a smaller RewP. A blunted RewP might contribute to stress susceptibility by affecting how much individuals engage in positive emotion regulation during stress.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.693
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.038
GPT teacher head0.387
Teacher spread0.349 · 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

Citations8
Published2023
Admission routes2
Has abstractyes

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