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Cognitive Mechanisms Underlying Action Prediction in Children and Adults with Autism Spectrum Condition

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Abstract

Recent research suggests that impaired action prediction is at the core of social interaction deficits in autism spectrum condition (ASC). Here, we targeted two cognitive mechanisms that are thought to underlie the prediction of others’ actions: statistical learning and efficiency considerations. We measured proactive eye movements of 10-year-old children and adults with and without ASC in anticipation of an agent’s repeatedly presented action. Participants with ASC showed a generally weaker tendency to generate action predictions. Further analyses revealed that statistical learning led to systematic accurate action predictions in the control groups. Participants with ASC were impaired in their ability to use frequency information for action predictions. Our findings inform etiological models of impaired social interaction in ASC.

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Notes

  1. In a previous version of this paradigm, the agent less explicitly stated its desire for lettuce, that it is hungry and that it wants to get more lettuce as fast as possible. A pilot study showed this material did not sufficiently trigger anticipatory gaze behavior. We therefore added the respective statements as described.

  2. We opted to analyze the first fixation score this way to be consistent with procedures reported in previous paper (Paulus et al. 2011a, b; Schuwerk and Paulus 2016). Specifically, this decision was based on the following reasons: First, this allowed us to analyze first fixations for repeated trials in one score. Second, nonparametric analyses with recoded variables would have caused the problem of having too many missing values (those trials in which participants fixated neither AOI). Third, the DLS results, the complementary GEE analyses, and the Bayesian statistics are all converging with the first fixation results. Fourth, we re-checked the first fixation results by running nonparametric statistics and found the same pattern of results. In other words, across different measures and analyses we found the same results. This provided converging evidence that our findings are reliable and robust.

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Acknowledgments

We are grateful to all participants and parents who took part in the study. We thank Nicosia Nieß and Gertrud Niggemann (Autismus Oberbayern e.V.), Martina Schabert (Autismuszentrum Oberbayern), and Martin Sobanski (Heckscher-Klinikum gGmbH) for their continuous help with recruiting participants. We further thank the whole LMU Babylab for help in data acquisition. Thanks are due to Irina Jarvers for her help in preprocessing gaze data.

Author Contributions

Conceptualization, TS and MP; Methodology, TS and MP; Formal Analysis, TS; Investigation, TS; Resources, BS; Writing-Original Draft, TS; Writing-Review & Editing, TS, MP and BS; Visualization, TS; Supervision, MP and BS; Funding Acquisition, BS.

Funding

This study was funded by a grant from VolkswagenStiftung.

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Authors and Affiliations

  1. Department of Psychology, Ludwig-Maximilians-University, Leopoldstr. 13, 80802, Munich, Germany

    Tobias Schuwerk, Beate Sodian & Markus Paulus

  2. Department of Psychiatry and Psychotherapy, University of Regensburg, Regensburg, Germany

    Tobias Schuwerk

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  1. Tobias Schuwerk
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Correspondence to Tobias Schuwerk.

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Schuwerk, T., Sodian, B. & Paulus, M. Cognitive Mechanisms Underlying Action Prediction in Children and Adults with Autism Spectrum Condition. J Autism Dev Disord 46, 3623–3639 (2016). https://doi.org/10.1007/s10803-016-2899-x

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