Multisensory mechanisms for perceptual disambiguation. A classification image study on the stream–bounce illusion

In: Multisensory Research
Cesare V. PariseMax Planck Institute for Biological Cybernetics, Germany
Department of Cognitive Neuroscience, University of Bielefeld, Germany

Search for other papers by Cesare V. Parise in
Current site
Google Scholar
Marc O. ErnstDepartment of Cognitive Neuroscience, University of Bielefeld, Germany

Search for other papers by Marc O. Ernst in
Current site
Google Scholar
Download Citation Get Permissions

Access options

Get access to the full article by using one of the access options below.

Institutional Login

Log in with Open Athens, Shibboleth, or your institutional credentials

Login via Institution


Buy instant access (PDF download and unlimited online access):


Sensory information is inherently ambiguous, and a given signal can in principle correspond to infinite states of the world. A primary task for the observer is therefore to disambiguate sensory information and accurately infer the actual state of the world.

Here, we take the stream–bounce illusion as a tool to investigate perceptual disambiguation from a cue-integration perspective, and explore how humans gather and combine sensory information to resolve ambiguity.

In a classification task, we presented two bars moving in opposite directions along the same trajectory meeting at the centre. We asked observers to classify such ambiguous displays as streaming or bouncing. Stimuli were embedded in dynamic audiovisual noise, so that through a reverse correlation analysis, we could estimate the perceptual templates used for the classification. Such templates, the classification images, describe the spatiotemporal statistical properties of the noise, which are selectively associated to either percept. Our results demonstrate that the features of both visual and auditory noise, and interactions thereof, strongly biased the final percept towards streaming or bouncing.

Computationally, participants’ performance is explained by a model involving a matching stage, where the perceptual systems cross-correlate the sensory signals with the internal templates; and an integration stage, where matching estimates are linearly combined to determine the final percept. These results demonstrate that observers use analogous MLE-like integration principles for categorical stimulus properties (stream/bounce decisions) as they do for continuous estimates (object size, position, etc.).

Finally, the time-course of the classification images reveal that most of the decisional weight for disambiguation is assigned to information gathered before the physical crossing of the stimuli, thus highlighting a predictive nature of perceptual disambiguation.

Content Metrics

All Time Past Year Past 30 Days
Abstract Views 86 10 0
Full Text Views 16 2 0
PDF Views & Downloads 17 6 0