Evidence map›Paper›PMID 35951205›Full record

ArticleJournal of autism and developmental disorders2023

Probabilistic Learning of Cue-Outcome Associations is not Influenced by Autistic Traits.

Jia Hoong Ong, Fang Liu

Abstract read
In one paragraph

Article in Journal of autism and developmental disorders, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

Jia Hoong OngSchool of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
Fang LiuSchool of Psychology and Clinical Language Sciences, University of Reading, Reading, UK. f.liu@reading.ac.uk.ORCID http://orcid.org/0000-0002-7776-0222

Funding

H2020 European Research Council 678733)H2020 European Research Council Starting Grant (CAASDH2020 Marie Skłodowska-Curie Actions 887283
6 · The paper itself

Abstract

According to Bayesian/predictive coding models of autism, autistic individuals may have difficulties learning probabilistic cue-outcome associations, but empirical evidence has been mixed. The target cues used in previous studies were often straightforward and might not reflect real-life learning of such associations which requires learners to infer which cue(s) among many to track. Across two experiments, we compared adult learners with varying levels of autistic traits on their ability to infer the correct cue to learn probabilistic cue-outcome associations when explicitly instructed to do so or when exposed implicitly. We found no evidence for the effect of autistic traits on probabilistic learning accuracy, contrary to the predictions of Bayesian/predictive coding models. Implications for the current Bayesian/predictive coding models are discussed.

Indexed as

Autism Spectrum DisorderAutistic DisorderAdultBayes TheoremCuesHumansLearningAutistic traitsBayesianPredictionPredictive codingProbabilisticStatistical learning

Identifiers

PMID35951205
PMCPMC9366807

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.