Multisensory causal inference is feature-specific, not object-based

Stephanie Badde, Michael S. Landy, Wendy J. Adams

Research output: Contribution to journalArticlepeer-review


Multisensory integration depends on causal inference about the sensory signals. We tested whether implicit causal-inference judgements pertain to entire objects or focus on task-relevant object features. Participants in our study judged virtual visual, haptic and visual-haptic surfaces with respect to two features - slant and roughness - against an internal standard in a two-alternative forced-choice task. Modelling of participants' responses revealed that the degree to which their perceptual judgements were based on integrated visual-haptic information varied unsystematically across features. For example, a perceived mismatch between visual and haptic roughness would not deter the observer from integrating visual and haptic slant. These results indicate that participants based their perceptual judgements on a feature-specific selection of information, suggesting that multisensory causal inference proceeds not at the object level but at the level of single object features. This article is part of the theme issue 'Decision and control processes in multisensory perception'.

Original languageEnglish (US)
Article number20220345
JournalPhilosophical Transactions of the Royal Society B: Biological Sciences
Issue number1886
StatePublished - Sep 25 2023


  • causal inference
  • cue integration
  • roughness
  • slant
  • visual-haptic

ASJC Scopus subject areas

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences


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