ArticleeLife2022
Aberrant causal inference and presence of a compensatory mechanism in autism spectrum disorder.
Article in eLife, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
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Who cites it
24 citing papers in PubMed, 36 citations in OpenAlex.
- Article
- Distilling noise characteristics and prior expectations in multisensory causal inference.PLoS computational biology · 2026Article
- Atypical integration of temporal evidence and priors in causality judgment along the autism-schizotypy continuum.iScience · 2026Article
- Autistic children sample costly information with increased variability due to inflexible updating.Communications psychology · 2026Article
- Shedding light on the dynamic interplay of positive and negative symptoms of psychosis with Behavioral Tractography.NPJ digital medicine · 2025Article
- Intact Audiovisual Spatial Integration in Autistic Children.Journal of autism and developmental disorders · 2025Article
- Scikit-NeuroMSI: A Generalized Framework for Modeling Multisensory Integration.Neuroinformatics · 2025Article
- A common computational and neural anomaly across mouse models of autism.Nature neuroscience · 2025Article
- Review
- Predictive Processing in Autism Spectrum Disorder: The Atypical Iterative Prior Updating Account.Biological psychiatry global open science · 2025Article
- Identifying Distinct Developmental Patterns of Brain Complexity in Autism: A Cross-Sectional Cohort Analysis Using the Autism Brain Imaging Data Exchange.Psychiatry and clinical neurosciences · 2025Article
- Increasing the Construct Validity of Computational Phenotypes of Mental Illness Through Active Inference and Brain Imaging.Brain sciences · 2024Review
- Functional Neurological Disorder and Autism Spectrum Disorder: A Complex and Potentially Significant Relationship.Brain and behavior · 2024Review
- BCI Toolbox: An open-source python package for the Bayesian causal inference model.PLoS computational biology · 2024Article
- Heterogeneity in strategy use during arbitration between experiential and observational learning.Nature communications · 2024Article
- Disentangling sensory precision and prior expectation of change in autism during tactile discrimination.NPJ science of learning · 2023Article
- Introspective inference counteracts perceptual distortion.Nature communications · 2023Article
- Causal inference during closed-loop navigation: parsing of self- and object-motion.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Article
- Multisensory decisions from self to world.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
- Multisensory integration in the mammalian brain: diversity and flexibility in health and disease.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2023Review
Corrections and comments
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Authors and funding
5 authors at 3 institutions in 1 country.
Funding
Abstract
Autism spectrum disorder (ASD) is characterized by a panoply of social, communicative, and sensory anomalies. As such, a central goal of computational psychiatry is to ascribe the heterogenous phenotypes observed in ASD to a limited set of canonical computations that may have gone awry in the disorder. Here, we posit causal inference - the process of inferring a causal structure linking sensory signals to hidden world causes - as one such computation. We show that audio-visual integration is intact in ASD and in line with optimal models of cue combination, yet multisensory behavior is anomalous in ASD because this group operates under an internal model favoring integration (vs. segregation). Paradoxically, during explicit reports of common cause across spatial or temporal disparities, individuals with ASD were less and not more likely to report common cause, particularly at small cue disparities. Formal model fitting revealed differences in both the prior probability for common cause (p-common) and choice biases, which are dissociable in implicit but not explicit causal inference tasks. Together, this pattern of results suggests (i) different internal models in attributing world causes to sensory signals in ASD relative to neurotypical individuals given identical sensory cues, and (ii) the presence of an explicit compensatory mechanism in ASD, with these individuals putatively having learned to compensate for their bias to integrate in explicit reports.
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Registered trials
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.