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Record W4405643974 · doi:10.1177/17470218241311582

Atypical implicit and explicit sense of agency in autism: A complete characterization using the cue integration approach

2024· article· en· W4405643974 on OpenAlexafffund
Alexis Lafleur, Vicky Caron, Baudouin Forgeot d’Arc, Isabelle Soulières

Bibliographic record

VenueQuarterly Journal of Experimental Psychology · 2024
Typearticle
Languageen
FieldNeuroscience
TopicFree Will and Agency
Canadian institutionsUniversité de MontréalCentre Hospitalier Universitaire Sainte-JustineUniversité du Québec à Montréal
FundersFonds de Recherche du Québec - Santé
KeywordsNeurotypicalAutismPsychologyAgency (philosophy)Cognitive psychologySense of agencyDevelopmental psychologyAutism spectrum disorderSocial psychology

Abstract

fetched live from OpenAlex

There exist indications that sense of agency (SoA), the experience of being the cause of one's own actions and actions' outcomes, is altered in autism. However, no studies in autism have simultaneously investigated the integration mechanisms underpinning both implicit and explicit SoA, the two levels of agency proposed by the innovative cue integration approach. Our study establishes a first complete characterization of SoA functioning in autism, by comparing age- and IQ-matched samples of autistic versus neurotypical adults. Intentional binding and judgments of agency were used to assess implicit and explicit SoA over pinching movements with visual outcomes. Sensorimotor and contextual cues were manipulated using feedback alteration and induced belief about the cause of actions' outcome. Implicit SoA was altered in autism, as showed by an overall abolished intentional binding effect and greater inter-individual heterogeneity. At the explicit level, we observed under-reliance on retrospective sensorimotor cues. The implicit-explicit dynamic was also altered in comparison to neurotypical individuals. Our results show that both implicit and explicit levels of SoA, as well as the dynamic between the two levels, present atypicalities in autism.

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)0.000
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 score0.223
Threshold uncertainty score0.329

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.072
GPT teacher head0.353
Teacher spread0.281 · 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

Citations0
Published2024
Admission routes2
Has abstractyes

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