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Causal Inference in Multisensory Perception

Kording, KP; Beierholm, U; Ma, WJ; Quartz, S; Tenenbaum, JB; Shams, L; (2007) Causal Inference in Multisensory Perception. PLOS ONE , 2 (9) , Article e943. 10.1371/journal.pone.0000943. Green and gold open access

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Abstract

Perceptual events derive their significance to an animal from their meaning about the world, that is from the information they carry about their causes. The brain should thus be able to efficiently infer the causes underlying our sensory events. Here we use multisensory cue combination to study causal inference in perception. We formulate an ideal-observer model that infers whether two sensory cues originate from the same location and that also estimates their location(s). This model accurately predicts the nonlinear integration of cues by human subjects in two auditory-visual localization tasks. The results show that indeed humans can efficiently infer the causal structure as well as the location of causes. By combining insights from the study of causal inference with the ideal-observer approach to sensory cue combination, we show that the capacity to infer causal structure is not limited to conscious, high-level cognition; it is also performed continually and effortlessly in perception.

Type:Article
Title:Causal Inference in Multisensory Perception
Open access status:An open access publication. A version is also available from UCL Discovery.
DOI:10.1371/journal.pone.0000943
Publisher version:http://dx.doi.org/10.1371/journal.pone.0000943
Language:English
Additional information:© 2007 Körding et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. KPK was supported by a DFG Heisenberg Stipend. UB and SQ were supported by the David and Lucille Packard Foundation as well as by the Moore Foundation. JBT was supported by the P. E. Newton Career Development Chair. LS was supported by UCLA Academic senate and Career development grants.
UCL classification:UCL > School of Life and Medical Sciences > Faculty of Life Sciences > Gatsby Computational Neuroscience Unit

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