Part of Advances in Neural Information Processing Systems 20 (NIPS 2007)
Ulrik Beierholm, Ladan Shams, Wei J., Konrad Koerding
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 (), 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 , 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.
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.