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Record W2152783797 · doi:10.1037/a0028924

Mismatched expressions decrease face recognition and corresponding ERP old/new effects in schizophrenia.

2012· article· en· W2152783797 on OpenAlexafffund
Fabrice Guillaume, François Guillem, Guy Tiberghien, Émmanuel Stip

Bibliographic record

VenueNeuropsychology · 2012
Typearticle
Languageen
FieldNeuroscience
TopicFace Recognition and Perception
Canadian institutionsInstitut universitaire en santé mentale de Montréal
FundersCanadian Institutes of Health Research
KeywordsPsychologySchizophrenia (object-oriented programming)Facial expressionExpression (computer science)NeurosciencePsychosisCognitive psychologyAudiologyRecognition memoryDevelopmental psychologyCognitionPsychiatryCommunication

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective was to investigate the electrophysiological (ERP) correlates of mismatched expression on face recognition in schizophrenia. METHOD: Expression-change effects and associated ERPs were explored in patients with schizophrenia (n = 20) and paired comparison participants (n = 20) on a long-term face-recognition task. RESULTS: A facial-expression change decreased discriminability for patients with schizophrenia than for healthy participants. The patients' recognition deficit was accompanied by the absence of the midfrontal FN400 and late parietal ERP old/new effects in the mismatched-expression condition. By contrast, preserved midfrontal FN400 and late parietal ERP old/new effects were found in both groups in the unchanged-expression condition. Thus, the preserved parietal old/new effect previously observed in schizophrenia was no longer found here in the situation in which expression changes took place between the study and recognition phases. CONCLUSIONS: These findings suggest that, when they are not supposed to take the change of expression into account, the recognition deficit observed here in patients with schizophrenia resulted from an impairment in the mechanisms underlying the emergence, assessment, or utilization of familiarity--as indexed by the ERP old/new effects. In these natural conditions, the impact of the expression change on the implementation of retrieval processes offers new insight into schizophrenia-linked deficits in face recognition, with substantial phenomenological differences with respect to the emergence of familiarity.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.733
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0000.001

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 head0.075
GPT teacher head0.321
Teacher spread0.246 · 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.

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

Citations15
Published2012
Admission routes2
Has abstractyes

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