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Record W1757967451 · doi:10.1167/15.12.1223

Emotion perception or social cognitive complexity: What drives face processing deficits in autism spectrum disorder?

2015· article· en· W1757967451 on OpenAlexaff
M. D. Rutherford, Jennifer A. Walsh, Sarah E. Creighton

Bibliographic record

VenueJournal of Vision · 2015
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPsychologyFacial expressionCognitionCognitive psychologyPerceptionEmotional expressionInformation processingExpression (computer science)Social cognitionVisual processingFace perceptionEmotion perceptionAutism spectrum disorderSensory processingAutismDevelopmental psychologySensory systemNeuroscienceCommunicationComputer science

Abstract

fetched live from OpenAlex

Faces convey information about sex, identity, age, ethnic group, and internal emotional state, and typical individuals are expert at encoding and interpreting facial information. Individuals with ASD have difficulties with social perception and cognition, and there has been a great deal of scientific focus on the ability of those individuals with ASD’s to processing facial information. Still, there is not a clear consensus as to what the core deficits in face processing are characteristic of ASD. The current study examined whether the anomalies in face processing seen in adults with ASD are better explained as a deficit in processing emotions, or a deficit in processing the complexity of social stimuli. Participants completed a battery of four face processing tasks: identity discrimination, basic expression perception, complex emotion expression, and trustworthiness perception. The tasks either did or did not involve processing facial expressions, and also varied in the level of social cognitive complexity. If the deficits in face processing in ASD are driven by a core deficit in processing emotional expression information, participants with ASD would perform worse on the basic and complex expression perception tasks. In contrast, if their deficit is related to processing socially complex facial information, they would show poorer performance on the complex expression and trustworthiness perception tasks. Results revealed that ASD participants showed worse performance on basic expression recognition task (t(44) = 3.06, p = .004) and the complex expression recognition task t(44) = 4.26, p < .001 compared to typical participants. In contrast, there were no significant group differences in performance on the identification task (t(44) = 1.33, p = .19) or the trustworthy perception task t(44) = .93, p = .36. These results support an emotion processing rather than a social complexity explanation for face processing deficits in ASD. Meeting abstract presented at VSS 2015

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.095
GPT teacher head0.382
Teacher spread0.287 · 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".

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Citations1
Published2015
Admission routes1
Has abstractyes

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