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Record W2043038916 · doi:10.1503/jpn.090085

Neural circuitry of emotional face processing in autism spectrum disorders

2010· article· en· W2043038916 on OpenAlexvenueno aff
Christopher S. Monk, Shih-Jen Weng, Jillian Lee Wiggins, Nikhil Kurapati, Hugo M.C. Louro, Melisa Carrasco, Julie Maslowsky, Susan Risi, Catherine Lord

Bibliographic record

VenueJournal of Psychiatry and Neuroscience · 2010
Typearticle
Languageen
FieldNeuroscience
TopicAutism Spectrum Disorder Research
Canadian institutionsnot available
FundersEunice Kennedy Shriver National Institute of Child Health and Human DevelopmentNational Institute of Mental Health
KeywordsVentromedial prefrontal cortexPsychologyAmygdalaFunctional magnetic resonance imagingPrefrontal cortexFacial expressionAutism spectrum disorderAutismCognitionAudiologyCognitive psychologyNeuroscienceDevelopmental psychologyCommunicationMedicine

Abstract

fetched live from OpenAlex

BACKGROUND: Autism spectrum disorders (ASD) are associated with severe impairments in social functioning. Because faces provide nonverbal cues that support social interactions, many studies of ASD have examined neural structures that process faces, including the amygdala, ventromedial prefrontal cortex and superior and middle temporal gyri. However, increases or decreases in activation are often contingent on the cognitive task. Specifically, the cognitive domain of attention influences group differences in brain activation. We investigated brain function abnormalities in participants with ASD using a task that monitored attention bias to emotional faces. METHODS: Twenty-four participants (12 with ASD, 12 controls) completed a functional magnetic resonance imaging study while performing an attention cuing task with emotional (happy, sad, angry) and neutral faces. RESULTS: In response to emotional faces, those in the ASD group showed greater right amygdala activation than those in the control group. A preliminary psychophysiological connectivity analysis showed that ASD participants had stronger positive right amygdala and ventromedial prefrontal cortex coupling and weaker positive right amygdala and temporal lobe coupling than controls. There were no group differences in the behavioural measure of attention bias to the emotional faces. LIMITATIONS: The small sample size may have affected our ability to detect additional group differences. CONCLUSION: When attention bias to emotional faces was equivalent between ASD and control groups, ASD was associated with greater amygdala activation. Preliminary analyses showed that ASD participants had stronger connectivity between the amygdala ventromedial prefrontal cortex (a network implicated in emotional modulation) and weaker connectivity between the amygdala and temporal lobe (a pathway involved in the identification of facial expressions, although areas of group differences were generally in a more anterior region of the temporal lobe than what is typically reported for emotional face processing). These alterations in connectivity are consistent with emotion and face processing disturbances in ASD.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.020
GPT teacher head0.298
Teacher spread0.278 · 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".

Quick stats

Citations238
Published2010
Admission routes1
Has abstractyes

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