without mandatory integration

) has been highly successful in modelling how the human brain combines information from a variety of different sensory modalities. However, in various recent experiments involving multisensory stimuli of uncertain correspondence, MLI breaks down as a successful model of sensory combination. Within

Comparing Bayesian models for multisensory cuecombination without mandatory integration

Responses of multisensory neurons to combinations of sensory cues are generally enhanced or depressed relative to single cues presented alone, but the rules that govern these interactions have remained unclear. We examined integration of visual and vestibular self-motion cues in macaque area MSTd

presented alone, were greatly reduced in combination. Evaluation of alternative models of sensory integration showed that the state of the visual bistable percept could not be accounted for by probability summation among cues, as might occur at the level of decision processes. Instead, the state

Abstract—Bayesian inference techniques have been used to understand the performance of human subjects on a large number of sensory tasks. Particularly, it has been shown that humans integrate sensory inputs from multiple cues in an optimal way in many conditions. Recently it has also been proposed

their pointing variability. One explanation for poorer group-level cue weighting at 10–12 years is that this ages represents a period of relatively rapid physical growth. An existing Bayesian model of hand localization did not describe either adults ’ or children’s data well, but the results suggest future

Although children with autism spectrum disorder (ASD) show atypical sensory processing, evidence for impaired inte-gration of multisensory information has been mixed. In this study, we took a Bayesian model-based approach to assess within-modality integration of congruent and incongruent texture

without experimental evidence. We set out to generate a general model of multisensory information extraction by aquatic animals. For our model we chose to analyze the hierarchical, integrative, and sometimes alternate use of various sensory systems during the feeding sequence in three species of sharks

compare two weighted integration models, a linear model and a sum of weighted likelihoods model based on a Bayesian observer. While qualitatively these models are similar, quantitatively they predict different cue validity effects as the signal-to-noise ratios (SNR) increase. To test these models, 3