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Human trimodal perception follows optimal statistical inference

Wozny, DR; Beierholm, UR; Shams, L; (2008) Human trimodal perception follows optimal statistical inference. J VISION , 8 (3) , Article 24. 10.1167/8.3.24. Gold open access

Abstract

Our nervous system typically processes signals from multiple sensory modalities at any given moment and is therefore posed with two important problems: which of the signals are caused by a common event, and how to combine those signals. We investigated human perception in the presence of auditory, visual, and tactile stimulation in a numerosity judgment task. Observers were presented with stimuli in one, two, or three modalities simultaneously and were asked to report their percepts in each modality. The degree of congruency between the modalities varied across trials. For example, a single. ash was paired in some trials with two beeps and two taps. Cross-modal illusions were observed in most conditions in which there was incongruence among the two or three stimuli, revealing robust interactions among the three modalities in all directions. The observers' bimodal and trimodal percepts were remarkably consistent with a Bayes-optimal strategy of combining the evidence in each modality with the prior probability of the events. These findings provide evidence that the combination of sensory information among three modalities follows optimal statistical inference for the entire spectrum of conditions.

Type:Article
Title:Human trimodal perception follows optimal statistical inference
Open access status:An open access publication
DOI:10.1167/8.3.24
Keywords:multisensory integration, cross modal, Bayesian inference, ideal observer, cross-modal illusion, trimodal perception, causal inference, NUMERICAL ABILITIES, VISUAL ILLUSION, INTEGRATION, MODEL, INFORMATION, TOUCH, REPRESENTATIONS, NUMBERS, MOTION, CORTEX
UCL classification:UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neuroscience Unit

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