Temporal context in perception: serial dependence and rhythmic oscillations

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This project aims to uncover how the brain uses knowledge and predictions about the world to interpret incoming sensory input. The project intends to study how recent sensory history influences current perception (serial dependence) and how rhythmic neural oscillations modulate perception. Project outcomes include a major advance in theories of how the brain achieves optimal predictive perception, and a model that can guide new applications in intelligent machines and sensing robots. Understanding predictive perception has a clinical benefit, as it is prone to dysfunction (as in autism), and an applied benefit, as it will generate a predictive model to guide new practical applications in sensing robots.