Comparing Bayesian models for multisensory cue combination without mandatory integration
Authors: Ladan Shams, Wei J. Ma, Konrad Koerding Ulrik Beierholm
Published in: Advances in Neural Information Processing Systems 20  (NIPS 2007) (Main Conference Track), 2007

Abstract: Bayesian models of multisensory perception traditionally address the problem of estimating an underlying variable that is assumed to be the cause of the two sen- sory signals. The brain, however, has to solve a more general problem: it also has to establish which signals come from the same source and should be integrated, and which ones do not and should be segregated. In the last couple of years, a few models have been proposed to solve this problem in a Bayesian fashion. One of these has the strength that it formalizes the causal structure of sensory signals. We ﬁrst compare these models on a formal level. Furthermore, we conduct a psy- chophysics experiment to test human performance in an auditory-visual spatial localization task in which integration is not mandatory. We ﬁnd that the causal Bayesian inference model accounts for the data better than other models. Keywords: causal inference, Bayesian methods, visual perception.
1 Multisensory perception
In the ventriloquist illusion, a performer speaks without moving his/her mouth while moving a puppet’s mouth in synchrony with his/her speech. This makes the puppet appear to be speaking. This illusion was ﬁrst conceptualized as ”visual capture”, occurring when visual and auditory stimuli exhibit a small conﬂict ([1, 2]). Only recently has it been demonstrated that the phenomenon may be seen as a byproduct of a much more ﬂexible and nearly Bayes-optimal strategy ([3]), and therefore is part of a large collection of cue combination experiments showing such statistical near-optimality [4, 5]. In fact, cue combination has become the poster child for Bayesian inference in the nervous system. In previous studies of multisensory integration, two sensory stimuli are presented which act as cues about a single underlying source. For instance, in the auditory-visual localization experiment by Alais and Burr [3], observers were asked to envisage each presentation of a light blob and a sound click as a single event, like a ball hitting the screen. In many cases, however, the brain is not only posed with the problem of identifying the position of a common source, but also of determining whether there was a common source at all. In the on-stage ventriloquist illusion, it is indeed primar- ily the causal inference process that is being fooled, because veridical perception would attribute independent causes to the auditory and the visual stimulus.
1
To extend our understanding of multisensory perception to this more general problem, it is necessary to manipulate the degree of belief assigned to there being a common cause within a multisensory task. Intuitively, we expect that when two signals are very different, they are less likely to be per- ceived as having a common source. It is well-known that increasing the discrepancy or inconsistency between stimuli reduces the inﬂuence that they have on each other [6, 7, 8, 9, 10, 11]. In auditory- visual spatial localization, one variable that controls stimulus similarity is spatial disparity (another would be temporal disparity). Indeed, it has been reported that increasing spatial disparity leads to a decrease in auditory localization bias [1, 12, 13, 14, 15, 16, 17, 2, 18, 19, 20, 21]. This decrease also correlates with a decrease in the reports of unity [19, 21]. Despite the abundance of experimental data on this issue, no general theory exists that can explain multisensory perception across a wide range of cue conﬂicts.