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Multisensory Causal Inference in the Brain

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  • Christoph Kayser
  • Ladan Shams

Abstract

At any given moment, our brain processes multiple inputs from its different sensory modalities (vision, hearing, touch, etc.). In deciphering this array of sensory information, the brain has to solve two problems: (1) which of the inputs originate from the same object and should be integrated and (2) for the sensations originating from the same object, how best to integrate them. Recent behavioural studies suggest that the human brain solves these problems using optimal probabilistic inference, known as Bayesian causal inference. However, how and where the underlying computations are carried out in the brain have remained unknown. By combining neuroimaging-based decoding techniques and computational modelling of behavioural data, a new study now sheds light on how multisensory causal inference maps onto specific brain areas. The results suggest that the complexity of neural computations increases along the visual hierarchy and link specific components of the causal inference process with specific visual and parietal regions.How does our brain organize and merge multisensory information? A new study localizes the brain regions underlying sensory fusion and causal inference by combining neuroimaging and computational modelling.

Suggested Citation

  • Christoph Kayser & Ladan Shams, 2015. "Multisensory Causal Inference in the Brain," PLOS Biology, Public Library of Science, vol. 13(2), pages 1-7, February.
  • Handle: RePEc:plo:pbio00:1002075
    DOI: 10.1371/journal.pbio.1002075
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    References listed on IDEAS

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    1. David R Wozny & Ulrik R Beierholm & Ladan Shams, 2010. "Probability Matching as a Computational Strategy Used in Perception," PLOS Computational Biology, Public Library of Science, vol. 6(8), pages 1-7, August.
    2. Konrad P Körding & Ulrik Beierholm & Wei Ji Ma & Steven Quartz & Joshua B Tenenbaum & Ladan Shams, 2007. "Causal Inference in Multisensory Perception," PLOS ONE, Public Library of Science, vol. 2(9), pages 1-10, September.
    3. Marc O. Ernst & Martin S. Banks, 2002. "Humans integrate visual and haptic information in a statistically optimal fashion," Nature, Nature, vol. 415(6870), pages 429-433, January.
    4. Mattia Rigotti & Omri Barak & Melissa R. Warden & Xiao-Jing Wang & Nathaniel D. Daw & Earl K. Miller & Stefano Fusi, 2013. "The importance of mixed selectivity in complex cognitive tasks," Nature, Nature, vol. 497(7451), pages 585-590, May.
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    1. Renan Schiavolin Recio & André Mascioli Cravo & Raphael Yokoingawa de Camargo & Virginie van Wassenhove, 2019. "Dissociating the sequential dependency of subjective temporal order from subjective simultaneity," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-10, October.

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