Show Reference: "Bayesian Inference Explains Perception of Unity and Ventriloquism Aftereffect: Identification of Common Sources of Audiovisual Stimuli"

Bayesian Inference Explains Perception of Unity and Ventriloquism Aftereffect: Identification of Common Sources of Audiovisual Stimuli Neural Computation, Vol. 19, No. 12. (December 2007), pp. 3335-3355, doi:10.1162/neco.2007.19.12.3335 by Yoshiyuki Sato, Taro Toyoizumi, Kazuyuki Aihara
@article{sato-et-al-2007,
    abstract = {We study a computational model of audiovisual integration by setting a Bayesian observer that localizes visual and auditory stimuli without presuming the binding of audiovisual information. The observer adopts the maximum a posteriori approach to estimate the physically delivered position or timing of presented stimuli, simultaneously judging whether they are from the same source or not. Several experimental results on the perception of spatial unity and the ventriloquism effect can be explained comprehensively if the subjects in the experiments are regarded as Bayesian observers who try to accurately locate the stimulus. Moreover, by adaptively changing the inner representation of the Bayesian observer in terms of experience, we show that our model reproduces perceived spatial frame shifts due to the audiovisual adaptation known as the ventriloquism aftereffect.},
    author = {Sato, Yoshiyuki and Toyoizumi, Taro and Aihara, Kazuyuki},
    doi = {10.1162/neco.2007.19.12.3335},
    issn = {0899-7667},
    journal = {Neural Computation},
    keywords = {auditory, bayes, decision-making, model, ventriloquism-effect, visual},
    month = dec,
    number = {12},
    pages = {3335--3355},
    pmid = {17970656},
    posted-at = {2014-05-22 16:25:17},
    priority = {2},
    title = {Bayesian Inference Explains Perception of Unity and Ventriloquism Aftereffect: Identification of Common Sources of Audiovisual Stimuli},
    url = {http://dx.doi.org/10.1162/neco.2007.19.12.3335},
    volume = {19},
    year = {2007}
}

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If it is not given that an auditory and a visual stimulus belong together, then integrating them (binding) unconditionally is not a good idea. In that case, causal inference and model selection are better.

The a-priori belief that there is one stimulus (the `unity assumption') can then be seen as a prior for one model—the one that assumes a single, cross-modal stimulus.

Sato et al. modeled multisensory integration with adaptation purely computationally. In their model, two localizations (one from each modality) were bound or not bound and localized according to a maximum a-posteriory decision rule.

The unity assumption can be interpreted as a prior (if interpreted as an expectation of a forthcoming uni- or cross-sensory stimulus) or a mediator variable in a Bayesian inference model of multisensory integration.