Aberrant causal inference and presence of a compensatory mechanism in Autism Spectrum Disorder

  1. Jean-Paul Noel
  2. Sabyasachi Shivkumar
  3. Kalpana Dokka
  4. Ralf M Haefner
  5. Dora E Angelaki  Is a corresponding author
  1. New York University, United States
  2. University of Rochester, United States
  3. Baylor College of Medicine, United States

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.

Data availability

Data and code are available at https://osf.io/6xbzt.

The following data sets were generated

Article and author information

Author details

  1. Jean-Paul Noel

    Center for Neural Science, New York University, New York City, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5297-3363
  2. Sabyasachi Shivkumar

    Brain and Cognitive Sciences, University of Rochester, Rocchester, United States
    Competing interests
    The authors declare that no competing interests exist.
  3. Kalpana Dokka

    Department of Neuroscience, Baylor College of Medicine, Houston, United States
    Competing interests
    The authors declare that no competing interests exist.
  4. Ralf M Haefner

    Brain and Cognitive Sciences, University of Rochester, Rochester, United States
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5031-0379
  5. Dora E Angelaki

    Center for Neural Science, New York University, New York, United States
    For correspondence
    da93@nyu.edu
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-9650-8962

Funding

National Institutes of Health (NIH U19NS118246)

  • Dora E Angelaki

National Institutes of Health (NIH U19NS118246)

  • Ralf M Haefner

Simons Foundation Autism Research Initiative (396921)

  • Dora E Angelaki

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Reviewing Editor

  1. Xiang Yu, Peking University, China

Ethics

Human subjects: The study was approved by the Institutional Review Board at the Baylor College of Medicine (protocol number H-29411) and written consent/assent was obtained.

Version history

  1. Received: July 1, 2021
  2. Accepted: May 15, 2022
  3. Accepted Manuscript published: May 17, 2022 (version 1)
  4. Version of Record published: June 6, 2022 (version 2)

Copyright

© 2022, Noel et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

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  1. Jean-Paul Noel
  2. Sabyasachi Shivkumar
  3. Kalpana Dokka
  4. Ralf M Haefner
  5. Dora E Angelaki
(2022)
Aberrant causal inference and presence of a compensatory mechanism in Autism Spectrum Disorder
eLife 11:e71866.
https://doi.org/10.7554/eLife.71866

Share this article

https://doi.org/10.7554/eLife.71866

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