Date: Wednesday, 13.12.2023 15:20-17:00 CET
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Abstract:
Our senses are constantly bombarded with a myriad of diverse signals. Transforming this sensory cacophony into a coherent percept of our environment relies on solving two computational challenges: First, we need to solve the causal inference or binding problem— deciding whether signals come from a common cause and thus should be integrated or come from different sources and should be treated independently. Second, when there is a common cause, we should integrate signals across the senses weighted in proportion to their sensory precisions. In this talk, I discuss our recent research at the behavioural, computational, and neural systems level that investigates how the brain addresses these two computational challenges in multisensory perception. Combining Bayesian modelling and fMRI/EEG our research has shown that the brain solves the causal inference problem by dynamically encoding multiple perceptual estimates along the visual and auditory processing pathways.
