CoChat
Sign Up
Cited by 885Autism Spectrum Disorder ResearchChild and Animal Learning DevelopmentAction Observation and Synchronization

Precise minds in uncertain worlds: Predictive coding in autism.

Open access
Van de Cruys, Sander, Evers, Kris, Van der Hallen, Ruth, Van Eylen, Lien, Boets, Bart, de-Wit, Lee, Wagemans, Johan·2014·Psychological Review
DOI 10.1037/a0037665
Open this paper in CoChat — free accountOpen PDF

Abstract

There have been numerous attempts to explain the enigma of autism, but existing neurocognitive theories often provide merely a refined description of 1 cluster of symptoms. Here we argue that deficits in executive functioning, theory of mind, and central coherence can all be understood as the consequence of a core deficit in the flexibility with which people with autism spectrum disorder can process violations to their expectations. More formally we argue that the human mind processes information by making and testing predictions and that the errors resulting from violations to these predictions are given a uniform, inflexibly high weight in autism spectrum disorder. The complex, fluctuating nature of regularities in the world and the stochastic and noisy biological system through which people experience it require that, in the real world, people not only learn from their errors but also need to (meta-)learn to sometimes ignore errors. Especially when situations (e.g., social) or stimuli (e.g., faces) become too complex or dynamic, people need to tolerate a certain degree of error in order to develop a more abstract level of representation. Starting from an inability to flexibly process prediction errors, a number of seemingly core deficits become logically secondary symptoms. Moreover, an insistence on sameness or the acting out of stereotyped and repetitive behaviors can be understood as attempts to provide a reassuring sense of predictive success in a world otherwise filled with error. (PsycINFO Database Record (c) 2014 APA, all rights reserved).

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1037/a0037665

Cites

307 of 307 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • By extension, all Bayesian accounts suggest that, beyond one ambiguous sensory event, learning about structural regularities-forming priors-is probably impaired in ASD.

    “However, by logical extension, beyond a single ambiguous sensory event, all Bayesian accounts imply that dynamic learning about structural regularities (i.e. the formation of priors) is likely impaired in ASD 2–7.”

    From Adults with autism overestimate the volatility of the sensory environment (2017) · cites this paper as [3]

    In “Predictive Coding in ASD” (page unavailable), the paper locates an ASD impairment in meta-learning when cue reliability changes in volatile environments, supporting a qualified claim about learning regularities. But it says people with ASD can learn new contingencies in relatively unambiguous situations, and “Attention and Executive Functioning” says they can learn fixed contingencies. It therefore does not support the broader assertion that all Bayesian accounts imply impaired formation of priors. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

  • The influential theory by Pellicano and Burr posits that autistic individuals form unusually weak priors, and this has been extended into predictive coding accounts that highlight atypical inference processes in ASD.

    “The influential theory by Pellicano and Burr (40) posits that autistic individuals form unusually weak priors, and this has been extended into predictive coding accounts that highlight atypical inference processes in ASD (41).”

    From Predictive coding and neurocomputational psychiatry: a mechanistic framework for understanding mental disorders (2026) · cites this paper as [41]

    The paper’s “Predictive Coding in ASD” section proposes atypical inference in autism through unusually high, inflexible precision assigned to prediction errors. But “Other Information Processing Accounts of ASD” distinguishes this proposal from Pellicano and Burr’s weak-priors account rather than presenting it as an extension of that account. (LLM, conf=0.84)

    Experimental — accuracy not yet measured

  • Bayesian accounts of perception in ASD propose that underweighting prior expectations relative to sensory input produces the condition's perceptual atypicalities.

    “Bayesian theories of perception in ASD1 propose that reduced weighting of prior expectations, relative to sensory inputs, leads to the perceptual atypicalities associated with the condition2–7”

    From Adults with autism overestimate the volatility of the sensory environment (2017) · cites this paper as [3]

    Experimental — accuracy not yet measured

  • Conservative readings of non-hierarchical Bayesian models of ASD and of predictive processing models that posit uniformly high, inflexible sensory precision entail this explanation.

    “Such an explanation is implied by conservative interpretations of non-hierarchical Bayesian accounts of ASD 2 and predictive processing accounts that emphasise “uniform” inflexibly high precision in sensory processing 3.”

    From Adults with autism overestimate the volatility of the sensory environment (2017) · cites this paper as [3]

  • More recently, theories have been proposed that combine, integrate and extend these theories, e.g., the Predictive Coding account and the Polyvagal Theory.

    “More recently, theories have been proposed that combine, integrate and extend these theories, e.g. the Predictive Coding account (PC; e.g., Van de Cruys et al., 2014) and the Polyvagal Theory (PT; e.g., Brown, 2020).”

    From Innovations of the ICD-11 in the Field of Autism Spectrum Disorder: A Psychological Approach (2022) · cites this paper as Van de Cruys et al., 2014

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

1 retracted

Flagged first, then by citations

Research works printed but not linked: 3

  1. [22]22. Bauman, M. L., & Kemper, T. L. (1994). Neuroanatomic observations of the brain in autism. In M. L. Bauman & T. L. Kemper (Eds.), The neurobiology of autism (pp. 119 -145). Baltimore, MD: Johns Hopkins Press.
  2. [207]207. Pellicano, E., Gibson, L., Maybery, M., Durkin, K., & Badcock, D. (2005). disorder. Current Biology, 17, 1508 -1512. doi:10.1016/j.cub.2007.07 .065 · DOI
  3. [265]265. Valentine, T. (1991). A unified account of the effects of distinctiveness, inversion, and race. Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 43(A), 161-204.

Cited by

Sorted by citations

Related

Authors
Van de Cruys, S., Evers, K., Van der Hallen, R., Van Eylen, L., Boets, B., de-Wit, L., & Wagemans, J.
Affiliations
KU Leuven (BE)
ORCID
Venue
Psychological Review
Publisher
American Psychological Association (APA)
Published
2014
Volume
121
Issue
4
Pages
649-675
ISSN
  • 0033-295X (ISSN-L)
  • 1939-1471
DOI
10.1037/a0037665
OpenAlex
W2098533845
Semantic Scholar
60c6614872c60b9708488f47521c1c59eda1b9ff
Cited by
885
References
297
Citations by year
2026: 102 · 2025: 81 · 2024: 80 · 2023: 109 · 2022: 85 · 2021: 106 · 2020: 74 · 2019: 76 · 2018: 53 · 2017: 51 · 2016: 35 · 2015: 30 · 2014: 3
FWCI
22.13
Type
journal article
Language
en
Open access
Licence
other-oa
Locations
  • Psychological Review (publishedVersion)
  • PubMed (publishedVersion)
  • Lirias (submittedVersion, other-oa)
Funders
Flemish Government (METH/08/02)
Topics
  • Life Sciences › Neuroscience › Cognitive Neuroscience › Autism Spectrum Disorder Research
  • Social Sciences › Psychology › Developmental and Educational Psychology › Child and Animal Learning Development
  • Social Sciences › Psychology › Social Psychology › Action Observation and Synchronization
Keywords
autism spectrum disorder, predictive coding, prediction error, executive function, theory of mind, central coherence, meta-learning, error tolerance, sameness, stereotypy, social cognition
MeSH terms
Autism Spectrum Disorder, Humans, Mental Processes

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review