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Record W1537459746 · doi:10.1111/psyp.12197

Prefrontal‐posterior coupling while observing the suffering of other people, and the development of intrusive memories

2014· article· en· W1537459746 on OpenAlexfundno aff
Eva M. Reiser, Elisabeth M. Weiss, Günter Schulter, Emily A. Holmes, Andréas Fink, Ilona Papousek

Bibliographic record

VenuePsychophysiology · 2014
Typearticle
Languageen
FieldPsychology
TopicAnxiety, Depression, Psychometrics, Treatment, Cognitive Processes
Canadian institutionsnot available
FundersMedical Research CouncilNational Institute for Health and Care ResearchUniversity of OxfordLupina FoundationWellcome Trust
KeywordsPsychologyPrefrontal cortexElectroencephalographyCognitive psychologyNeuroscienceCognition

Abstract

fetched live from OpenAlex

Witnessing the suffering of others, for instance, in hospital emergency rooms but also through televised images in news or reality programs, may be associated with the occurrence of later intrusive memories. The factors contributing to why some people develop intrusive memories and others do not are still poorly understood. N = 121 healthy women were exposed to film scenes showing the suffering of dying, severely injured, and mourning people while their EEG was recorded. Individuals showing greater decreases of functional coupling between prefrontal and posterior cortices (greater decreases of EEG beta coherences) reported more intrusive memories of the witnessed events. This was shown for intrusions in the short term (immediately after viewing the film) as well as in the medium term (intrusive memories over 1 week). The findings illuminate brain mechanisms involved in the encoding of information in ways that make intrusive memories more likely.

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 score0.712
Threshold uncertainty score0.625

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.025
GPT teacher head0.294
Teacher spread0.269 · 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

Citations13
Published2014
Admission routes1
Has abstractyes

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