Decoding Social Information from Biological Motion in the Broad Autism Phenotype: An Eye-Tracking Study

Authors

  • Elena L. Gavrilova HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
  • Anna I. Izmalkova HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
  • Ksenia I. Novoselova HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation
  • Andriy V. Myachykov HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation; University of Macau, Avenida da Universidade, Taipa, Macau, 999078, China
  • Yury Y. Shtyrov HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation; Aarhus University, Nordre Ringgade, Aarhus, 8000, Danmark

DOI:

https://doi.org/10.17323/1813-8918-2026-3-498-511

Keywords:

social cognition, motion perception, eye-tracking, broad autism phenotype

Abstract

The term broad autism phenotype (BAP) refers to individuals who do not meet the diagnostic criteria for autism but share some of its features, including social difficulties and atypicalities in visual perception and attention that have been linked to a detail-oriented cognitive style. To examine both the cognitive and social aspects of BAP, we employed a biological motion paradigm combined with eye-tracking technology. Participants with high (n = 20) and low (n = 22) levels of autistic traits, grouped by their Autism Spectrum Quotient scores, viewed point-light displays depicting emotional expressions and dyadic interactions and identified them by keypress in a forced-choice task. Although both groups performed with near-ceiling accuracy (>90%), high-trait individuals responded significantly slower in both tasks. No group differences emerged in global eye-movement metrics such as the number and characteristics of fixations and saccades. However, the spatial allocation of attention revealed more finegrained effects: high-trait individuals made more fixations on non-social background regions in the emotion task and showed a less centralized gaze pattern when viewing dyadic interactions. These findings suggest that individuals with elevated autistic traits process the social information carried by biological motion with reduced efficiency relative to their low-trait counterparts, which is reflected in slower responses and less focused attention to socially relevant regions of the display. The results are consistent with a graded, efficiency-based account of social perception in the broad autism phenotype.

Author Biographies

  • Elena L. Gavrilova, HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation

    Junior Research Fellow, Cognitive Health and Intelligence Center, Institute for Cognitive Neuroscience, HSE University.

    Research Area: experimental psychology, neurodevelopmental disorders, eyetracking.

  • Anna I. Izmalkova, HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation

    Research Fellow, Cognitive Health and Intelligence Center, Institute for Cognitive Neuroscience, HSE University.

    Research Area: cognitive strategies, working memory, eye-tracking.

  • Ksenia I. Novoselova, HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation

    Research Assistant, Cognitive Health and Intelligence Center, Institute for Cognitive Neuroscience, HSE University.

    Research Area: cognitive functioning, neurodevelopmental disorders.

  • Andriy V. Myachykov, HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation; University of Macau, Avenida da Universidade, Taipa, Macau, 999078, China

    Lead Research Fellow, Cognitive Health and Intelligence Center, Institute for Cognitive Neuro science, HSE University; Professor, University of Macau (China).

    Research Area: embodied cognition, bilingualism, cognitive aging.

  • Yury Y. Shtyrov, HSE University, 20 Myasnitskaya Str., Moscow, 101000, Russian Federation; Aarhus University, Nordre Ringgade, Aarhus, 8000, Danmark

    Lead Research Fellow, Cognitive Health and Intelligence Center, Institute for Cognitive Neuroscience, HSE University; Professor, Aarhus University (Danmark).

    Research Area: neurophysiology, experimental psychology, language studies.

References

Alink, A., & Charest, I. (2020). Clinically relevant autistic traits predict greater reliance on detail for image recognition. Scientific Reports, 10(1), Article 14239. https://doi.org/10.1038/s41598-020-70953-8

Atherton, G., & Cross, L. (2022). Reading the mind in cartoon eyes: Comparing human versus cartoon emotion recognition in those with high and low levels of autistic traits. Psychological Reports, 125(3), 1380–1396. https://doi.org/10.1177/0033294120988135

Bachmann, J., Zabicki, A., Munzert, J., & Krüger, B. (2020). Emotional expressivity of the observer mediates recognition of affective states from human body movements. Cognition and Emotion, 34(7), 1370–1381. https://doi.org/10.1080/02699931.2020.1747990

Bailey, A., Palferman, S., Heavey, L., & Le Couteur, A. (1998). Autism: The phenotype in relatives. Journal of Autism and Developmental Disorders, 28(5), 369–392. https://doi.org/10.1023/A:1026048320785

Baron-Cohen, S., & Hammer, J. (1997). Parents of children with Asperger syndrome: What is the cognitive phenotype? Journal of Cognitive Neuroscience, 9(4), 548–554. https://doi.org/10.1162/jocn.1997.9.4.548

Baron-Cohen, S., Wheelwright, S., Skinner, R., Martin, J., & Clubley, E. (2001). The Autism-Spectrum Quotient (AQ): Evidence from Asperger syndrome/high-functioning Autism, males and females, scientists and mathematicians. Journal of Autism and Developmental Disorders, 31(1), 5–17. https://doi.org/10.1023/A:1005653411471

Bidet-Ildei, C., Francisco, V., Decatoire, A., Pylouster, J., & Blandin, Y. (2022). PLAViMoP database: A new continuously assessed and collaborative 3D point-light display dataset. Behavior Research Methods, 55(2), 694–715. https://doi.org/10.3758/s13428-022-01850-3

Buehler, R., Potocar, L., Mikus, N., & Silani, G. (2025). Autistic traits relate to reduced reward sensitivity in learning from point-light displays (PLDs). Royal Society Open Science, 12(3), Article 241349. https://doi.org/10.1098/rsos.241349

Burghoorn, F., Dingemanse, M., Van Lier, R., & Van Leeuwen, T. M. (2020). The relation between autistic traits, the degree of synaesthesia, and local/global visual perception. Journal of Autism and Developmental Disorders, 50(1), 12–29. https://doi.org/10.1007/s10803-019-04222-7

Cross, L., Piovesan, A., & Atherton, G. (2022). Autistic people outperform neurotypicals in a cartoon version of the Reading the Mind in the Eyes. Autism Research, 15(9), 1603–1608. https://doi.org/10.1002/aur.2782

Davis, J., McKone, E., Zirnsak, M., Moore, T., O’Kearney, R., Apthorp, D., & Palermo, R. (2017). Social and attention to detail subclusters of autistic traits differentially predict looking at eyes and face identity recognition ability. British Journal of Psychology, 108(1), 191–219. https://doi.org/10.1111/bjop.12188

De Groot, K., & Van Strien, J. W. (2017). Evidence for a broad autism phenotype. Advances in Neurodevelopmental Disorders, 1(3), 129–140. https://doi.org/10.1007/s41252-017-0021-9

Decatoire, A., Beauprez, S.-A., Pylouster, J., Lacouture, P., Blandin, Y., & Bidet-Ildei, C. (2019). PLAViMoP: How to standardize and simplify the use of point-light displays. Behavior Research Methods, 51(6), 2573–2596. https://doi.org/10.3758/s13428-018-1112-x

Federici, A., Parma, V., Vicovaro, M., Radassao, L., Casartelli, L., & Ronconi, L. (2020). Anomalous perception of biological motion in autism: A conceptual review and meta-analysis. Scientific Reports, 10(1), Article 4576. https://doi.org/10.1038/s41598-020-61252-3

Goold, S., Murphy, M. J., Goodale, M. A., Crewther, S. G., & Laycock, R. (2022). Faster social attention disengagement in individuals with higher autism traits. Journal of Clinical and Experimental Neuropsychology, 44(10), 755–767. https://doi.org/10.1080/13803395.2023.2167943

Greene, C. M., Suess, E., & Kelly, Y. (2020). Autistic traits do not affect emotional face processing in a general population sample. Journal of Autism and Developmental Disorders, 50(8), 2673–2684. https://doi.org/10.1007/s10803-020-04375-w

Hudson, M., Nijboer, T. C. W., & Jellema, T. (2012). Implicit social learning in relation to autistic-like traits. Journal of Autism and Developmental Disorders, 42(12), 2534–2545. https://doi.org/10.1007/s10803-012-1510-3

Jacob, P., & Alexander, G. (2023). Impaired biological motion processing and motor skills in adults with autistic traits. Journal of Autism and Developmental Disorders, 53(8), 2998–3011. https://doi.org/10.1007/s10803-022-05572-5

Johansson, G. (1973). Visual perception of biological motion and a model for its analysis. Perception & Psychophysics, 14(2), 201–211. https://doi.org/10.3758/BF03212378

Karakale, Ö., Nelson, N., Gredelj, A., Ryan, K. J., & Bayindir, A. (2025). Prior contextual information and autistic traits influence eye gaze behaviour and emotional valence ratings for facial expressions. Scientific Reports, 15(1), Article 27574. https://doi.org/10.1038/s41598-025-13507-0

Laycock, R., Chan, D., & Crewther, S. G. (2017). Attention orienting in response to non-conscious hierarchical arrows: Individuals with higher autistic traits differ in their global/local bias. Frontiers in Psychology, 8, Article 23. https://doi.org/10.3389/fpsyg.2017.00023

Lindor, E. R., van Boxtel, J. J. A., Rinehart, N. J., & Fielding, J. (2019). Motor difficulties are associated with impaired perception of interactive human movement in autism spectrum disorder: A pilot study. Journal of Clinical and Experimental Neuropsychology, 41(8), 856–874. https://doi.org/10.1080/13803395.2019.1634181

Miu, A. C., Pan , S. E., & Avram, J. (2012). Emotional face processing in neurotypicals with autistic traits: Implications for the broad autism phenotype. Psychiatry Research, 198(3), 489–494. https://doi.org/10.1016/j.psychres.2012.01.024

Nackaerts, E., Wagemans, J., Helsen, W., Swinnen, S. P., Wenderoth, N., & Alaerts, K. (2012). Recognizing biological motion and emotions from point-light displays in autism spectrum disorders. PLoS ONE, 7(9), Article 44473. https://doi.org/10.1371/journal.pone.0044473

Nagase, K. (2025). The association of autistic traits on cognitive emotion regulation strategies in a non-clinical sample. Psychological Reports, 128(6), 4449–4469. https://doi.org/10.1177/00332941231214172

Nitzan-Tamar, O., Kramarski, B., & Vakil, E. (2016). Eye movement patterns characteristic of cognitive style: Wholistic versus analytic. Experimental Psychology, 63(3), 159–168. https://doi.org/10.1027/1618-3169/a000323

Sevgi, M., Diaconescu, A. O., Henco, L., Tittgemeyer, M., & Schilbach, L. (2020). Social bayes: Using bayesian modeling to study autistic trait–related differences in social cognition. Biological Psychiatry, 87(2), 185–193. https://doi.org/10.1016/j.biopsych.2019.09.032

Shen, L., Yang, X., Jiang, Y., & Wang, Y. (2025). Understanding biological motion through the lens of animate motion processing. Frontiers in Psychology, 16, Article 1630742. https://doi.org/10.3389/fpsyg.2025.1630742

Stavropoulos, K. K. M., Viktorinova, M., Naples, A., Foss-Feig, J., & McPartland, J. C. (2018). Autistic traits modulate conscious and nonconscious face perception. Social Neuroscience, 13(1), 40–51. https://doi.org/10.1080/17470919.2016.1248788

Stevenson, R. A., Sun, S. Z., Hazlett, N., Cant, J. S., Barense, M. D., & Ferber, S. (2018). Seeing the forest and the trees: Default local processing in individuals with high autistic traits does not come at the expense of global attention. Journal of Autism and Developmental Disorders, 48(4), 1382–1396. https://doi.org/10.1007/s10803-016-2711-y

Sucksmith, E., Roth, I., & Hoekstra, R. A. (2011). Autistic traits below the clinical threshold: Reexamining the broader autism phenotype in the 21st century. Neuropsychology Review, 21(4), 360–389. https://doi.org/10.1007/s11065-011-9183-9

Tassini, S. C. V., Melo, M. C., Bueno, O. F. A., & De Mello, C. B. (2024). Weak central coherence in adults with ASD: Evidence from eye-tracking and thematic content analysis of social scenes. Applied Neuropsychology: Adult, 31(4), 657–668. https://doi.org/10.1080/23279095.2022.2060105

Todorova, G. K., Hatton, R. E. M., & Pollick, F. E. (2019). Biological motion perception in autism spectrum disorder: A meta-analysis. Molecular Autism, 10(1), Article 49. https://doi.org/10.1186/s13229-019-0299-8

Van Boxtel, J. J. A., & Lu, H. (2013). Impaired global, and compensatory local, biological motion processing in people with high levels of autistic traits. Frontiers in Psychology, 4, Article 209. https://doi.org/10.3389/fpsyg.2013.00209

Van Boxtel, J. J. A., Peng, Y., Su, J., & Lu, H. (2017). Individual differences in high-level biological motion tasks correlate with autistic traits. Vision Research, 141, 136–144. https://doi.org/10.1016/j.visres.2016.11.005

Von der Lühe, T., Manera, V., Barisic, I., Becchio, C., Vogeley, K., & Schilbach, L. (2016). Interpersonal predictive coding, not action perception, is impaired in autism. Philosophical Transactions of the Royal Society B: Biological Sciences, 371(1693), Article 20150373. https://doi.org/10.1098/rstb.2015.0373

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Published

2026-09-20

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Section

The Human Mind Across Scales: a Neurobiological, Cognitive, and Social Perspecti

How to Cite

Decoding Social Information from Biological Motion in the Broad Autism Phenotype: An Eye-Tracking Study. (2026). Psychology. Journal of the Higher School of Economics, 23(3), 498-511. https://doi.org/10.17323/1813-8918-2026-3-498-511