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Record W2753046055 · doi:10.1037/emo0000356

Neurophysiological traces of interpersonal pain: How emotional autobiographical memories affect event-related potentials.

2017· article· en· W2753046055 on OpenAlexaff
Kristina Rohde, Franz Caspar, Thomas Koenig, Antonio Pascual‐Leone, Maria Stein

Bibliographic record

VenueEmotion · 2017
Typearticle
Languageen
FieldNeuroscience
TopicMemory and Neural Mechanisms
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPsychologyAutobiographical memoryPsycINFOCognitive psychologyInterpersonal communicationAffect (linguistics)PerceptionRecallNeuroscienceSocial psychologyCommunicationMEDLINE

Abstract

fetched live from OpenAlex

The automatic, involuntary reactivation of disturbing emotional memories, for example, of interpersonal pain, causes psychological discomfort and is central to many psychopathologies. This study aimed at elucidating the automatic brain processes underlying emotional autobiographical memories by investigating the neurophysiological dynamics within the first second after memory reactivation. Pictures of different individualized familiar faces served as cues for different specific emotional autobiographical memories, for example, for memories of interpersonal pain and grievances or for memories of appreciation in interpersonal relationships. Nineteen subjects participated in a passive face-viewing task while multichannel electroencephalogram was recorded. Analyses of event-related potentials demonstrated that emotional memories elicited an early posterior negativity and a stronger late positive potential, which tended to be particularly enhanced for painful memories. Source estimations attributed this stronger activation to networks including the posterior cingulate and ventrolateral prefrontal cortices. The findings suggest that the reactivation of emotional autobiographical memories involves privileged automatic attention at perceptual processing stages, and an enhanced recruitment of neural network activity at a postperceptual stage sensitive to emotional-motivational processing. (PsycINFO Database Record

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.077
Threshold uncertainty score0.598

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 integrity0.0000.000
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 head0.066
GPT teacher head0.303
Teacher spread0.238 · 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 designBench or experimental
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

Citations6
Published2017
Admission routes1
Has abstractyes

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