Sensory reliability shapes perceptual inference via two mechanisms.

By Tim Rohe, Uta Noppeney. 2015

124 citations recorded by the source corpus.

To obtain a coherent percept of the environment, the brain should integrate sensory signals from common sources and segregate those from independent sources. Recent research has demonstrated that humans integrate audiovisual information during spatial localization consistent with Bayesian Causal Inference (CI). However, the decision strategies that human observers employ for implicit and explicit CI remain unclear. Further, despite the key role of sensory reliability in multisensory integration, Bayesian CI has never been evaluated across a wide range of sensory reliabilities. This psychophysics study presented participants with spatially congruent and discrepant audiovisual signals at four levels of visual reliability. Participants localized the auditory signals (implicit CI) and judged whether auditory and visual signals came from common or independent sources (explicit CI). Our results demonstrate that humans employ model averaging as a decision strategy for implicit CI; they report an auditory spatial estimate that averages the spatial estimates under the two causal structures weighted by their posterior probabilities. Likewise, they explicitly infer a common source during the common-source judgment when the posterior probability for a common source exceeds a fixed threshold of 0.5. Critically, sensory reliability shapes multisensory integration in Bayesian CI via two distinct mechanisms: First, higher sensory reliability sensitizes humans to spatial disparity and thereby sharpens their multisensory integration window. Second, sensory reliability determines the relative signal weights in multisensory integration under the assumption of a common source. In conclusion, our results demonstrate that Bayesian CI is fundamental for integrating signals of variable reliabilities.

Subfields: Cognitive Neuroscience, Experimental and Cognitive Psychology

Citations in the corpus

• The Brain’s Tendency to Bind Audiovisual Signals Is Stable but Not General (2016, unknown): “…make explicit predictions about the locations of unisensory and multisensory processing areas in the brain, one recent study using functional MRI and a spatial localization task made progress in this area by mapping estimates from this model onto different cortical areas (Rohe & Noppeney, 2015a).”
• Distinct Computational Principles Govern Multisensory Integration in Primary Sensory and Association Cortices. (2016, unknown): “This interaction results from a larger spatial window of integration for less-reliable sensory signals (see [16]).”
• The Curious Incident of Attention in Multisensory Integration: Bottom-up vs. Top-down (2016, unknown): “The development of new theoretical and mathematical approaches (e.g. Bayesian causal inference, Rohe and Noppeney, 2015a) will help us with the interpretation of these neuronal effects.”