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Causal inference shapes crossmodal postdiction in multisensory integration
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  • Published: 21 February 2026

Causal inference shapes crossmodal postdiction in multisensory integration

  • G. Günaydın  ORCID: orcid.org/0009-0000-0320-46051,2,3,4,
  • J. K. Moran  ORCID: orcid.org/0000-0003-2880-30781,
  • T. Rohe  ORCID: orcid.org/0000-0001-9713-37125,6 na1 &
  • …
  • D. Senkowski  ORCID: orcid.org/0000-0002-1467-82641,4 na1 

Scientific Reports , Article number:  (2026) Cite this article

We are providing an unedited version of this manuscript to give early access to its findings. Before final publication, the manuscript will undergo further editing. Please note there may be errors present which affect the content, and all legal disclaimers apply.

Subjects

  • Neuroscience
  • Psychology

Abstract

In our environment, stimuli from different sensory modalities are initially processed within a temporal window of multisensory integration spanning several hundred milliseconds. During this window, stimulus processing is influenced not only by preceding and current information, but also by input that follows the stimulus. The computational mechanisms underlying crossmodal backward processing, which we refer to as crossmodal postdiction, are not well understood. We examined crossmodal postdiction in the Illusory Audiovisual (AV) Rabbit and Invisible AV Rabbit Illusions, in which postdiction occurs when flash-beep pairs are presented shortly before and shortly after a single flash or a single beep. We collected behavioral data from 32 participants and fitted four competing models: Bayesian Causal Inference (BCI), forced-fusion, forced-segregation, and non-postdictive BCI. The BCI model fit the data well and outperformed all other models. Building on previous findings that demonstrate causal inference during non-postdictive multisensory integration, our results show that the BCI framework can also explain crossmodal postdiction phenomena. Our findings suggest that the brain performs causal inference not only across concurrent sensory inputs but also across temporal windows, integrating information from past, present, and subsequent events across modalities to construct a unified percept.

Data availability

The collected data and generated datasets of this study are available upon reasonable request.

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Acknowledgements

This research was supported by grants from the Deutsche Forschungsgemeinschaft (DFG) to TR (RO 5587/5 − 1) and DS (SE1859/10 − 1).

Funding

Open Access funding enabled and organized by Projekt DEAL.

Author information

Author notes
  1. T. Rohe and D. Senkowski contributed equally to this work.

Authors and Affiliations

  1. Department of Psychiatry and Neurosciences, Charité Campus Mitte (CCM), Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin and Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany

    G. Günaydın, J. K. Moran & D. Senkowski

  2. Bernstein Center for Computational Neuroscience Berlin, Humboldt-Universität Zu Berlin, Philippstr. 13, Haus 6, 10115, Berlin, Germany

    G. Günaydın

  3. Department of Psychology, Humboldt-Universität Zu Berlin, 10099, Berlin, Germany

    G. Günaydın

  4. Einstein Center for Neurosciences Berlin, Berlin Institute of Health, Charité – Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität Zu Berlin, Charitéplatz 1, 10117, Berlin, Germany

    G. Günaydın & D. Senkowski

  5. Sensory Analytics and Technologies, Fraunhofer Institute for Process Engineering and Packaging (IVV), Giggenhauser Str. 35, 85354, Freising, Germany

    T. Rohe

  6. Institute of Psychology, Friedrich-Alexander-Universität, 91054, Erlangen-Nürnberg, Germany

    T. Rohe

Authors
  1. G. Günaydın
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  2. J. K. Moran
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  4. D. Senkowski
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Contributions

D.S., T.R., G.G., and J.M. contributed to the conception and design of the study. G.G. was responsible for data collection. T.R., G.G., and D.S. performed the data analysis and interpretation. D.S. led the drafting of the manuscript. All authors contributed to manuscript revision, read, and approved the final version. D.S. and T.R. supervised the project.

Corresponding author

Correspondence to D. Senkowski.

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The authors declare no competing interests.

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Cite this article

Günaydın, G., Moran, J.K., Rohe, T. et al. Causal inference shapes crossmodal postdiction in multisensory integration. Sci Rep (2026). https://doi.org/10.1038/s41598-026-36884-6

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  • Received: 27 August 2025

  • Accepted: 16 January 2026

  • Published: 21 February 2026

  • DOI: https://doi.org/10.1038/s41598-026-36884-6

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