The DOI matches its Crossref record; 43 of the 43 references it cites were found in a registry or an index.
Bayesian multisensory integration and cross-modal spatial links.
Abstract
Our perception of the word is the result of combining information between several senses, such as vision, audition and proprioception. These sensory modalities use widely different frames of reference to represent the properties and locations of object. Moreover, multisensory cues come with different degrees of reliability, and the reliability of a given cue can change in different contexts. The Bayesian framework--which we describe in this review--provides an optimal solution to deal with this issue of combining cues that are not equally reliable. However, this approach does not address the issue of frames of references. We show that this problem can be solved by creating cross-modal spatial links in basis function networks. Finally, we show how the basis function approach can be combined with the Bayesian framework to yield networks that can perform optimal multisensory combination. On the basis of this theory, we argue that multisensory integration is a dialogue between sensory modalities rather that the convergence of all sensory information onto a supra-modal area.
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“According to recent statistical models of perception, the interpretation of multisensory signals could be sped up and made more precise by incorporating memory information (‘priors’) in the decision process [44], [45], [46].”
From If I were you: Perceptual illusion of body swapping (2008) · cites this paper as [44]
Citations
Cites
Humans integrate visual and haptic information in a statistically optimal fashion
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Integration of Proprioceptive and Visual Position-Information: An Experimentally Supported Model
van Beers, R. J., Sittig, A. C., & Gon, J. J. D. V. D. (1999) · Journal of Neurophysiology · doi:10.1152/jn.1999.81.3.1355 · Cited by 742
Reach Plans in Eye-Centered Coordinates
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Spatial invariance of visual receptive fields in parietal cortex neurons
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Cited by
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Daw, N. D., Niv, Y., & Dayan, P. (2005) · Nature Neuroscience · doi:10.1038/nn1560 · Cited by 2,533
Interactions between number and space in parietal cortex
Hubbard, E. M., Manuela Piazza, A., Pinel, P., & Dehaene, S. (2005) · Nature reviews. Neuroscience · doi:10.1038/nrn1684 · Cited by 1,324
Vestibular System: The Many Facets of a Multimodal Sense
Angelaki, D. E., & Cullen, K. E. (2008) · Annual Review of Neuroscience · doi:10.1146/annurev.neuro.31.060407.125555 · Cited by 966
If I were you: Perceptual illusion of body swapping
Petkova, V. I., & Ehrsson, H. H. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003832 · Cited by 953
Behavioral, Neural, and Computational Principles of Bodily Self-Consciousness
Blanke, O., Slater, M., & Serino, A. (2015) · Neuron · doi:10.1016/j.neuron.2015.09.029 · Cited by 698
Metadata
- Authors
- Deneve, S., & Pouget, A.
- Affiliations
- University of Rochester (US)
- ORCID
- Pouget, Alexandre
- Venue
- Journal of Physiology-Paris
- Publisher
- Elsevier BV
- Published
- 2004-01
- Volume
- 98
- Issue
- 1-3
- Pages
- 249-258
- ISSN
- 0928-4257 (ISSN-L)
- OpenAlex
- W2013752524
- Cited by
- 230
- References
- 43
- Citations by year
- 2026: 4 · 2025: 13 · 2024: 7 · 2023: 14 · 2022: 6 · 2021: 10 · 2020: 8 · 2019: 13 · 2018: 13 · 2017: 10 · 2016: 10 · 2015: 8 · 2014: 14 · 2013: 15 · 2012: 15
- FWCI
- 1.34
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Physiology-Paris (publishedVersion)
- PubMed (publishedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- Alfred P. Sloan Foundation
- Office of Naval Research
- Topics
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Multisensory perception and integration
- Life Sciences › Neuroscience › Cognitive Neuroscience › Tactile and Sensory Interactions
- Life Sciences › Neuroscience › Cognitive Neuroscience › Visual perception and processing mechanisms
- Keywords
- multisensory integration, Bayesian inference, cue reliability, word perception, speech perception, audiovisual integration
- MeSH terms
- Animals, Bayes Theorem, Humans, Space Perception, Touch
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