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Reflections on Cross-Modal Correspondences: Current Understanding and Issues for Future Research.

Kosuke Motoki1, Lawrence E Marks2,3, Carlos Velasco4

  • 1Department of Management, The University of Tokyo, Tokyo, 981-0935, Japan.

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|November 14, 2023
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Summary
This summary is machine-generated.

Cross-modal correspondences link sensory features across senses, with shared associations often rooted in physiological, semantic, statistical, or affective factors. Further research is needed to unify understanding of these perceptual links.

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Area of Science:

  • Psychology and Neuroscience
  • Sensory Perception Research

Background:

  • Cross-modal correspondences involve associations between sensory features across different senses.
  • Research interest has grown across diverse fields like psychology, neuroscience, music, and art.
  • The scope of cross-modal correspondences has broadened significantly over the past two decades.

Purpose of the Study:

  • To review and define cross-modal correspondences.
  • To explore the origins and underlying mechanisms of these associations.
  • To categorize different types of cross-modal correspondences.

Main Methods:

  • Narrative review of existing research on cross-modal correspondences.
  • Analysis of sensory dimensions (quantity/quality) and features (perceptual/cognitive).
  • Examination of two perspectives: phenomenal (subjective experience) and behavioral (observable responses).

Main Results:

  • Cross-modal correspondences are relative associations between sensory stimuli, often shared across individuals.
  • A taxonomy includes four types: physiological, semantic, statistical, and affective.
  • These correspondences link sensory dimensions and features, measurable via subjective perception or behavioral responses.

Conclusions:

  • Cross-modal correspondences are complex associations with shared and individual components.
  • Further research must clarify the relationship between phenomenal and behavioral measures.
  • Investigating whether different correspondence types share underlying mechanisms is crucial for a unified framework.